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High-priority first dynamic wavelength and bandwidth allocation algorithm in TWDM-PON
Optical Fiber Technology 48 (2019) 165–172
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Optical Fiber Technology journal homepage: www.elsevier.com/locate/yofte
High-priority first dynamic wavelength and bandwidth allocation algorithm in TWDM-PON
T
⁎
Lincong Zhanga, Jifeng Qia, Kefeng Weib,c, Wenbo Zhanga, , Yongxin Fenga, Weigang Houa a
School of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, China School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China c Shen Kan Engineering and Technology Corporation, MCC., Shenyang 110169, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: TWDM-PON Wavelength selection Dynamic bandwidth allocation T-CONT
Time and wavelength division multiplexing passive optical network (TWDM-PON) is the mainstream scheme of the next generation access network, and it possesses a number of unique characteristics such as high-bandwidth, long-distance data transmission, and connecting lots of users. As the difference among user traffic demands increases, in order to effectively decrease the network delay and improve resource utilization, a high-priority first dynamic wavelength and bandwidth allocation (HF-DWBA) algorithm in TWDM-PON system is proposed in this study. According to the service-level agreement (SLA), in order to determine the priority of an optical network unit (ONU), the proposed algorithm ensures the high-level ONU traffic distribution in terms of wavelength assignment and bandwidth allocation, and it can execute five types of transmission containers (T-CONTs) as well as four kinds of bandwidth allocation strategies. The results of simulation show that in comparison with traditional algorithms, the proposed HF-DWBA algorithm can effectively reduce end-to-end time delay and improve bandwidth utilization ratio, while making fairness among different types of bandwidth allocation strategies.
1. Introduction In order to meet a growing demand for high-bandwidth and traffic perceived by users, a number of new high-bandwidth services have been developed (e.g., network disk and cloud computing), possessing some challenges to network access control. Traditional optical access networks [1,2], such as Ethernet passive optical network (EPON) and gigabit passive optical network (GPON), have not still fully satisfied the users’ demands. Thus, full service access network (FSAN) commenced to operate on the basis of next generation-passive optical network (NGPON), in which some requirements in 2011, indicating the time of beyond 10 Gbps is coming [3,4]. In 2012, some studies reported that time and wavelength division multiplexed passive optical network (TWDM-PON) is a primary solution to NG-PON [5–7]. In TWDM-PON, resource scheduling strategy indicates the system performances (e.g., bandwidth utilization, throughput, delay, etc.). Since four wavelengths are used in TWDM-PON and if there is no reasonable scheduling strategy for the network, on the one hand, some wavelengths may be over-use and therefore lead to large delay; on the other hand, other wavelengths may be bare and lead to unbalance on bandwidth usage. Therefore, designing a robust approach to effectively
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and reasonably realize the resource scheduling on wavelength and bandwidth is significant. Some previous studies have developed a twodimensional (2D) resource scheduling method by using the dual flexibility (i.e., wavelength and bandwidth flexibilities) of TWDM-PON [8–11]. In resource scheduling issue, in order to support differentiated QoS, TWDM-PON divides bandwidth into four types, namely, fixed bandwidth, guaranteed bandwidth, non-guaranteed bandwidth, and the best effort bandwidth [12]. In TWDM-PON, the monitoring and control of the upstream traffic convergence process of all ONUs are centralized by OLT. In other words, each ONU continuously reports the respective load status of their transmission containers (T-CONTs) to OLT. As a central core of transmission convergence (TC) layer, OLT subsequently monitors the status of all T-CONTs and adjusts their location in time. Simultaneously, OLT processes two important functions, involving media access control for upstream direction and dynamic bandwidth adjustment. In the mentioned process, both of basic monitoring and basic traffic scheduling units are T-CONTs [13–15]. T-CONT is generally divided into five types, each ONU has five queues corresponding to TCONT-1, 2, 3, 4, 5. T-CONT-1 corresponds to a fixed bandwidth allocation, and its delay requirement is strictly controlled. T-CONT-2
Corresponding author. E-mail address: [email protected] (W. Zhang).
https://doi.org/10.1016/j.yofte.2018.12.029 Received 11 September 2018; Received in revised form 9 December 2018; Accepted 26 December 2018 1068-5200/ © 2019 Elsevier Inc. All rights reserved.
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TWDM-PON resource allocation, mainly take into account the ONU as a tunable transceiver, bandwidth allocation for a fixed network data traffic, and 2D resource scheduling problem based on EPON. Wang et al. [16] proposed a dynamic wavelength and bandwidth allocation (DWBA) algorithm based on a linear prediction method to schedule resources. The algorithm not only dynamically allocates the bandwidth resources in one wavelength channel, but also statistically provides multiplexing among various wavelength channels, allowing bandwidth to be effectively allocated. However, this algorithm has not considered different types of traffic and ONU priorities. Xiong et al. [17] proposed a user-behavior aware dynamic resource allocation strategy in TWDM-PON. According to the dynamic traffic status presented by user-behaviors, the ONU polling mechanism is adjusted in real-time to effectively reduce the network delay and promote the fairness of resource allocation, while this algorithm is not applicable for XG-PON. Dixit et al. [18] presented a dynamic bandwidth allocation algorithm with optimal wavelength switching in TWDM-PONs, improving network delay and channel utilization. Das et al. [19] proposed a novel architecture and medium access control (MAC) protocol for fully flexible hybrid WDM/TDM PON. This algorithm possesses a low queuing delay; however, it cannot fully exploit the advantages of multiwavelength channels. Some previous studies [20–22] proposed a resource allocation strategy based on the service level. This algorithm reduces the traffic queuing delay; however, it may cause a greater waste of bandwidth because few wavelengths sharing among ONUs. Han [23] assessed the performance of a dynamic bandwidth allocation algorithm for TWDM-PON system. Zhang et al. [24] developed a dynamic resource scheduling algorithm in ring-tree TWDM-PON system and proposed a maximum bandwidth utilization ratio algorithm as well as minimum tuning time algorithm. Cheng et al. [25] and Bi et al. [26] attempted to propose a flexible TWDM-PON system with pluggable optical transceiver modules by using two or more transceivers in one system, as well as combination of bandwidth schedule among ONUs to realize simultaneously the dynamic scheduling for both wavelengths and time slots. However, this approach requires high-cost of ONUs and does not take bandwidth allocation within ONUs into account. Wang et al. [27] developed a new method for dynamic bandwidth scheduling in WDM EPON system, without consideration of traffic diversity. There are also some researches on software defined TWDM-PON [28–30], Gu et al. [28] used software defined technology to provide the flexibility on wavelength assignment according to traffic statistics dynamically. Gu et al. [29] also proposed a software-defined passive optical network architecture with network coding (NC) to reduce downstream bandwidth consumption and thus increase the throughput and network efficiency. Kondepu et al. [30] proposed an SDN node controller architecture and a proper scheduling priority to preserve the overall service level. However, the mentioned studies often encountered two key problems. First, the developed TWDM-PON scheduling algorithms have mainly focused on EPON system and neglected performing studies on XG-PON system. Actually, EPON and XG-PON use different protocols in media access control. Besides, on the basis of XG-PON system, few twodimensional dynamic allocation algorithms for the wavelength and bandwidth flexibility were yet developed. Second, most of the previous researches have not taken into account the users’ priority and diversity of different types of traffic, meaning inadequate attention to the resource scheduling fairness in addition to different requirements of QoS. Thus, this study attempts to overcome these two main problems.
Table 1 Different types of bandwidth corresponding to different types of T-CONTs. Bandwidth Type
T-CONT Type 1
Reserved Bandwidth Extra Bandwidth
Fixed Bandwidth Guaranteed Bandwidth Non-guaranteed Bandwidth Best Effort Bandwidth
2
3
√
√ √
4
5
√
√ √ √ √
√
represents a guaranteed bandwidth allocation (i.e., bandwidth required within a specific range to meet a certain delay). T-CONT-2 is typically used for voice over Internet protocol (VoIP). T-CONT-3 provides guaranteed and non-guaranteed bandwidths, which is applicable to both services of assurance requirements and network traffic “bursting”. The main characteristic of T-CONT-4 is that there is no bandwidth guarantee, and the system congestion directly affects the bandwidth allocation, which is appropriate for network traffic with low requirements of packet loss, delay, and jitter. Moreover, T-CONT-5 is a combination of these four kinds of T-CONT, and it presents all types of bandwidth and supports all kinds of traffic as well. Table 1 lists the types of bandwidth allocation supported by different types of T-CONTs, and time delay sensitivity for different traffic flows. To assure the fairness of wavelength assignment scheme among ONUs and bandwidth allocation for different types of T-CONTs innerONUs, a high-priority first dynamic wavelength and bandwidth allocation (HF-DWBA) algorithm is proposed. This algorithm indicates the priority of ONUs based on service level agreement (SLA) [27], performing through a resource scheduling strategy both at OLT and ONU sides. This algorithm implements five types of T-CONTs as well as four kinds of bandwidth allocation and can effectively reduce the network delay and improve resource utilization. The performance of the proposed algorithm can be summarized as follows. 1) In order to take into account actual demands of different users and ensure the fairness of resource scheduling, the priority of the ONUs is defined based on SLA. Allocate bandwidth for high-level ONUs at first, and then for low-level ONUs. 2) To make the selection of wavelength be more efficient, a singlequeue multi-service stations queuing model is developed based on the characteristic of simultaneous transmission at multiple wavelengths in TWDM-PON. This model can reduce the queuing delay of each ONU and average delay of each packet. 3) In order to avoid network congestion caused by network traffic bursting, which will result in a remarkable time delay, a threshold is set for each wavelength. When the network traffic on a certain wavelength reaches 90% of the maximum capacity, this wavelength stops allocating bandwidth to the next ONUs. This can guarantee QoS for diverse services. 4) During bandwidth allocation, different bandwidth demands of five types of T-CONT are taken into account, and bandwidth allocation is on the basis of XG-PON structure to satisfy requirements for different traffic flows, delay, jitter, rate of packet loss, and various QoS. The rest of this paper is organized as follows. Section 2 elaborates previous studies on resource allocation in PON. Section 3 contains the problems’ definition in terms of wavelength assignment and bandwidth allocation. Section 4 presents the proposed HF-DWBA algorithm in detail. The results of numerical simulation are shown in Section 5. Section 6 summarizes the findings achieved in this study.
3. Problem formulation In this section, first of all, the notations used in the paper are presented, and then it will be attempted to describe how we aim to overcome the wavelength assignment problem and bandwidth allocation problem.
2. Related works Currently the on-going researches, with the aim of studying the 166
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3.1. Notations Notations in Wavelength Assignment Problem:
• M: Number of wavelengths in the whole network. • N: Number of ONUs in TWDM-PON. • λ : Maximum capacity of a single wavelength. • Req : The bandwidth request of ONUs. x : In period t , the status of ONU in the active wavelength m is • inquired. Herein, x =1 denotes that ONU is in the active wavelim
t im
i
Fig. 1. Schematic illustration of a multi-service single queue model.
i
t im
i
length m .
In TWDM-PON system, there are no restrictions for the request of the upstream direction, and each request is independent as well. In a certain period, the number of ONUs obeys the Poisson distribution of a stationary arrival rate. The internal queuing of ONUs is a single queue; the time of responding the signal receiver at OLT side to each ONU is independent; the request arrival time interval and processing time per request are independent; the duration of signal processing for each signal receiver is the same as well. The queuing model used in this study is shown in Fig. 1. According to the established model, the wavelength assignment problem can be formulated as follows:
• y : In period t , the activation of wavelength m is inquire d. Besides, y =1 represents that the wavelength m is active. ρ : The status of bandwidth allocation on current period is in• quired. When the i ONU is assigned to the m wavelength, ρ = 1 t m t m
i, m
th
th
i, m
otherwise, ρi,m = 0 . Notations in Bandwidth Allocate Problem:
• ONU : Set of ONUs in the network. • B: Total distributable bandwidth per polling cycle. • B (i, j): Fixed bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 1, 5. • B (i, j): Guaranteed bandwidth obtained by T-CONT of type j in the i H-ONU, i = 1, 2, …, N, j = 2, 3, 5. • B (i, j): Guaranteed bandwidth obtained by T-CONT of type j in the i L-ONU, i = 1, 2, …, N, j = 2, 3, 5. • B (i, j): Guaranteed bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 2, 3, 5. • B (i, j): Non-guaranteed bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 3, 5. • B (i, j): Best-effort bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 4, 5. • B : Total bandwidth required for each T-CONT in the ONU. • B : Minimum guaranteed bandwidth obtained by per ONU. • B : Default fixed bandwidth allocated to each ONU. • B : Fixed bandwidth required for ONUs. • B : Guaranteed bandwidth required for ONUs. • B : Total bandwidth allocated to ONUs. • B : Guaranteed bandwidth allocated to ONUs. • B : Non-guaranteed bandwidth allocated to ONUs. • B : Best-effort bandwidth allocated to ONUs. • B : Remaining bandwidth. • B : Guaranteed bandwidth required for each ONU. • B : Non-guaranteed bandwidth required for each ONU. • B : Best-effort bandwidth required for each ONU. • n: The number of L-ONUs at the time of allocating guaranteed bandwidth. • n : The number of H-ONUs that have not been yet met the bandth
f
M
Maximize
Ha
N
∑ ∑ ρi,m Reqi m=1 i=1
(1)
th
Subjected to
La
th
N
∑ ρi,m Reqi ≤ λlim, ∀ m ∈ {1, 2, ⋯, m}
a
th
i=1
(2)
na
∑ ximt = 1, ximt , ymt ∈ {0, 1}, ∀ i, t
th
m
ba
th
Eq. (1) calculates optimization target for the wavelength selection model to find out the optimal assignment method, satisfying the maximum bandwidth request. The available constraint in Eq. (2) represents that the single wavelength capacity does not exceed the maximum threshold to efficiently guarantee QoS. The constraint in Eq. (3) demonstrates that an ONU at a certain time only belongs to an active wavelength. The wavelength selection for TWDM-PON system can be formulated by the above-mentioned model. Although AMPL/CPLEX optimization modeling language can be used to achieve an optimal allocation scheme, an optimal solution cannot be applied to the actual network. As wavelength selection belongs to a NP-hard problem [31], an optimal solution cannot guarantee the fairness among different ONUs. Thus, a heuristic algorithm is developed to obtain an approximate optimal solution for wavelength assignment.
R
ensure fix A fix R assure R
A assure A na A be A
k a R na R be R
1
•
(3)
3.3. The bandwidth allocation problem
width requirements at the time of allocating non-guaranteed bandwidth. n2 : The number of H-ONUs that do not satisfy the current bandwidth requirements at the time of allocating the best-effort bandwidth.
When an ONU is assigned to an available wavelength, the bandwidth allocation mechanism to this wavelength channel and the number of time slots to be used to send a message are great challenges. In order to gain the best experience by users, as well as realize the maximization and efficient and fairness resource allocation, an optimal dynamic bandwidth allocation algorithm not only should effectively allocate the channel resources, but also must ensure the fairness among ONUs. In this paper, a reasonable and efficient dynamic bandwidth allocation algorithm is proposed for different types of T-CONT traffic in the ONUs. For this purpose, the bandwidth allocation problem is formulated as follows:
3.2. The wavelength assignment problem In wavelength assignment process, all ONUs are arrayed in one queue, waiting for OLT to assign the signal receiver. In other words, the number of receivers is M (that is the number of wavelengths in TWDMPON system), while there is only one ONU queue. In TWDM-PON system, ONUs are assumed as the customer sources in queuing theory. A signal receiver at OLT side is assumed as a service station in queuing theory. We suppose that the number of wavelengths supported by the TWDM-PON system is equal to “c”, which is assumed as the number of service stations in the queuing theory as well. Thus, the M/M/c queuing model is utilized to select the wavelength.
N
5
Maximize ∑ ∑ (Bf (i, j ) + Bna (i, j ) + Bbe (i, j )) i=1 j=1
Subjected to 167
(4)
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B−
∑
stops allocating the bandwidth to the next arriving ONUs. After that, bandwidth is sequentially allocated to the next arriving ONUs on the remaining wavelengths. (d) After completing the wavelength selection for H-ONUs, the available wavelength is assigned to L-ONUs according to the above-mentioned procedure. (e) If all the wavelengths are saturated, the remaining ONUs are assigned to each wavelength based on their traffic capacity ranging from small to large order until all ONUs are allocated. (2) When BRtotal > BAtotal :
Bf (i, j ) ≥ 0, j = 1, 5 (5)
1≤i≤N
Bensure ≥ Ba (i, j ), ∀ i ∈ ONU , j = 2, 3, 5
(6)
Bf (i, j ) = BAfix , ∀ i ∈ ONU , j = 1, 5
(7)
BRa, BR ≤ Beasure BHa (i, j ) = ⎧ , ∀ i ∈ ONU , j = 2, 3, 5 ⎨ Beasure − BAfix , BR > Beasure ⎩
(8)
BLa (i, j ) =
min{BRa,
Bna (i, j ) =
min{BRna,
Bk / n}, ∀ i ∈ ONU , j = 2, 3, 5
(9)
Bk / n1}, ∀ i ∈ ONU , j = 3, 5
(10)
Bba (i, j ) = min{BRbe , Bk / n2}, ∀ i ∈ ONU , j = 4, 5
(11)
Each wavelength sequentially assigns the minimum guaranteed bandwidth Beasure to all ONUs. To ensure that each ONU can be allocated to a certain bandwidth, H-ONU is firstly assigned, and then LONU is assigned. Afterwards, the required bandwidth is allocated to each ONU according to the proposed bandwidth allocation algorithm at ONU side. Due to the burstiness of a traffic stream, in a polling cycle, some ONUs may have a small demand of traffic, leading to a surplus of minimum guaranteed bandwidth. In order to avoid unbalance and bandwidth wastes during bandwidth allocation, we recycle excess bandwidth into the next bandwidth allocation loop. For making simplicity in presentation, the notations of wavelength assignment parameters are presented as follows. Ocur is the traffic of ONUs, BH − ONUi denotes the bandwidth required for high-level ONUs, BL − ONUi represents the bandwidth required for low-level ONUs, Buti is the utilization of upstream bandwidth, Bthr denotes the upstream network throughput, and Tave is the average packet delay. The pseudo-code of wavelength assignment is described in Algorithm 1.
Eq. (4) calculates an optimization target for the bandwidth allocation model, aiming to find out the optimal bandwidth allocation method, satisfying the requirements of each type of bandwidth within each ONU. The constraint available in Eq. (5) demonstrates that the total allocable bandwidth is larger than that of the fixed allocated bandwidth. In addition, the constraint existed in Eq. (6) illustrates that there is enough bandwidth to be allocated for guaranteed bandwidth. The constraints in Eqs. (7)–(11) show the allocation equations for fixed bandwidth, guaranteed bandwidth, non-guaranteed bandwidth, and best-effort bandwidth. To develop an optimal bandwidth allocation algorithm, we can map the traffic of various priorities and kinds to different T-CONTs by this algorithm. On the other hand, we can also differentiate traffic and ensure different types of traffic with diverse requirements of QoS based on the proposed bandwidth allocation algorithm, regarding T-CONT as a control unit.
Algorithm 1: Wavelength assignment approach in TWDM-PON 4. HF-DWBA algorithm
Input: M, N, λlim , Ocur , BH − ONUi , BL − ONUi ; topology of the TWDM-PON; caching queue of ONU set Oi ={1, 2, 3, …, N}, H-ONU set OH = {0, 2, 3, …, N}, LONU set OL ={0, 2, 3, …, N}; Output: Buti , Bthr , Tave . 1: the number of upstream packets sent by each ONU follows Poisson distribution: Ocur ∈ Oi ; 2: OLT collects all ONUs’ information, put H-ONUs in OH , put L-ONUs in OL ; 3: while BH − ONUi < λlim do 4: assign H − ONUi to the wavelength λ1, λ2 , λ3 , λ 4 sequentially; 5: ifBH − ONUi > λlim then 6: this wavelength stops allocating bandwidth, then allocate bandwidth to the next arriving ONUs by the next wavelength; 7: end if 8: end while 9: while BL − ONUi < λlim do 10: assign L − ONUi to the wavelength λ1, λ2 , λ3 , λ 4 sequentially; 11: if BL − ONUi > λlim then 12: this wavelength stops allocating bandwidth, then allocate bandwidth to the next arriving ONUs by the next wavelength; 13: end if 14: end while 15: calculate Buti , Bthr , Tave ; 16: Output Buti , Bthr , Tave .
In this paper, the proposed HF-DWBA algorithm dynamically allocates the resources at the OLT and ONU sides. After wavelength selection at the OLT side, the bandwidth is allocated at the ONU side. In a network packet, due to different requirements of QoS of various traffic, some kinds of traffic are sensitive to the delay (e.g., voice and video), while others are only sensitive to the cell loss rate (e.g., file transfer protocol (FTP) and E-mail). Therefore, it is necessary to distinguish different types of traffic before performs the bandwidth allocation. 4.1. Wavelength assignment algorithm The proposed algorithm assigns different weight coefficients for ONUs based on user’s SLA [29], and then divides ONUs into high- and low-priority levels. According to the characteristics of multi-wavelength simultaneous transmission of TWDM-PON, a queuing model is developed representing a multi-service single queue system. When we assign wavelengths to ONUs, we should first meet the requirements of high-level ONUs, and then satisfy the requirements of low-level ONUs to ensure a fair scheduling process among ONUs. In order to avoid congestion and increase of delay caused by gusty traffic flow when the network is busy, as well as ensuring the QoS, the proposed algorithm assigns the maximum capacity threshold for each wavelength. For making simplicity in presentation, BAtotal denotes the total available bandwidth, and BRtotal is total request bandwidth for all ONUs. The whole process of the proposed wavelength assignment algorithm is described as follows:
4.2. Bandwidth allocation algorithm In the internal of ONUs, ONU allocates bandwidth to different types of T-CONTs. The TWDM-PON system can support five types of TCONTs, as well as four different types of bandwidth. Before algorithm description, the required parameters are defined as follows: The whole process for the proposed bandwidth allocation algorithm is described as follows:
(1) When BRtotal ≤ BAtotal (a) OLT collects all ONUs’ information and classifies them into high-level ONUs (H-ONUs) and low-level ONUs (L-ONUs); (b) According to the developed multi-service single queue model, the wavelength assignment for H-ONUs on all wavelengths is transformed into packing problem. (c) When the traffic of a wavelength reaches 90%, this wavelength
(1) When BR ≤ BA , allocate bandwidth to each ONU according to the requirement of T-CONT. (2) When BR > BA , allocate bandwidth according to the following methods: 168
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Step 1: Allocate fixed bandwidth BAfix to T-CONT-1 and T-CONT-5 of each ONU. Step 2: Allocate guaranteed bandwidth BAassure to T-CONT-2, TCONT-3, and T-CONT-5 of each ONU. At the first stage, allocate bandwidth to H-ONUs. When BR > Bensure , BR ≤ Bensure , BAassure BAassure (H − ONUi ) = Bensure − BAfix ; when (H − ONUi) = BRassure ; and recycle the remaining bandwidth Bk . Secondly, allocate bandwidth to L-ONUs. Then, count the remaining BAassure (L − ONUi ) = Bk > 0 , bandwidth If Bk . assure min{BR (L − ONUi ), Bk / n} (n is the number of L-ONUs at this time); and then, recycle the remaining bandwidth Bk . Step 3: Allocate non-guaranteed bandwidth BAna to T-CONT-3 and TCONT-5 of each ONU. Count the remaining bandwidth Bk . If Bk > 0 , BAna (H − ONUi ) = min{BRna (H − ONUi ), Bk / n1} (n1 is the number of H-ONUs that have not been yet satisfied the bandwidth requirements); and then, recycle the remaining bandwidth Bk . Step 4: Allocate best-effort bandwidth BAbe to T-CONT-4 and T-CONT5 of each ONU. Count the remaining bandwidth Bk . If Bk > 0 , BAbe (H − ONUi ) = min{BRbe (H − ONUi ), Bk /n2} (n2 is the number of HONUs that do not meet the current bandwidth requirements); then, recycle the remaining bandwidth Bk . Step 5: If Bk > 0 , according to the above-mentioned methods, allocate non-guaranteed bandwidth as well as best-effort bandwidth to L-ONUs whose bandwidth requirements are not satisfied, until all the bandwidth is allocated.
Fig. 2. Bandwidth utilization of different numbers of wavelengths.
5. Performance evaluation 5.1. Parameter setting of simulation environment In this section, we compare the performance of the proposed HFDWBA algorithm with LP-DWBA [3] and UBA-DRAS [4]. LP-DWBA is a linear prediction scheme and showed advances in average packet delay. To solve the problem that the differences between users’ behavior increase, UBA-DRAS divides one cycle into several sub-cycles to alternatively send different level business. Some parameters in simulations are assumed. We assumed that the grade of ONUs is divided into two categories: H-ONU and L-ONU. The distance between OLT and ONUs is 20 km. The number of ONUs, N, is 32, the number of wavelengths, M, is 2, 4, 6, 8, respectively; the bit-rate of each wavelength is 2.5 Gbps [7], the maximum cycle time is 2 ms, and the guard time is 1 μs [32]. ONU data source follows the Poisson distribution. Packet sizes are uniformly distributed between 64 and 1518 bytes.
According to the specific steps required for execution of the bandwidth allocation algorithm, a detailed description of the pseudo-code is illustrated in Algorithm 2. Herein, T denotes the number of T-CONTs in each ONU, D represents the number of bandwidth types, Uti4 is the utilization of different types of bandwidth in the ONU, and Tt _ave represents the average delay of T-CONT. Algorithm 2: Bandwidth allocation approach in ONU Input: M, N, T, D, B; H-ONU set OH ={0, 1, 2, 3, …, N}, L-ONU set OL ={0, 1, 2, 3, …, N}; Output: Uti4 , Tt _ave ; 1:if BR ≤ BA then 2: while T-CONT whose bandwidth cannot be satisfied do 3: allocate bandwidth to each ONU according to the requirement of T-CONT; 4: end while 5: else 6: judge the number of H-ONUs and L-ONUs, put H-ONUs in OH , put L-ONUs in OL ; 7: allocate bandwidth to T-CONT-1, and T-CONT-5 of all ONUs according to Eq.
5.2. The analysis of simulation results Fig. 2 shows the effect of different loads on the utilization of upstream bandwidth when HF-DWBA allocates the resources at different wavelengths. It can be seen that as the load increases, the utilization of upstream bandwidth increases, especially linearly rises when M is equal to 6 and 8. This is due to the increase of the traffic at each wavelength as well as gradually reducing the idle time. When M is 2, the utilization of bandwidth gradually trends stably after the load 0.6, indicating that the wavelength capacity tends to saturation. Fig. 2 demonstrates that the more the number of wavelengths, the lower the utilization of upstream bandwidth under the same load. The reason is that the total bandwidth is larger when the number of wavelengths is remarkable, thus the idle time becomes longer at each wavelength. It can be seen that the greater the number of wavelengths, the larger the capacity of the system to carry the traffic. In order to obtain a higher utilization of upstream bandwidth and avoid wasting the resource overhead, the number of wavelengths should be chosen based on traffic situations. Fig. 3 displays the effect of different loads on the upstream network throughput when HAF-DWBA allocates resources at different wavelengths. Obviously, upstream network throughput increases with the increasing load. When the load is small, the upstream network throughput for different numbers of wavelengths doesn’t remarkably vary. However, with the increasing load, the network capacity for different numbers of wavelengths shows a great difference. It is mainly attributed to smaller numbers of wavelengths, which are easy to reach the maximum traffic capacity.
(5)→ BAfix ; 8: recycle the remaining bandwidth Bk ← Bk ; 9: allocate bandwidth to T-CONT-2, T-CONT-3, and T-CONT-5 of all ONUs according to Eqs. (6) and (7) →BAassure ; 10: recycle the remaining bandwidth Bk ← Bk ; 11: allocate bandwidth to T-CONT-3, and T-CONT-5 of all H-ONUs according to Eq. (8) → BAna ; 12: recycle the remaining bandwidth Bk ← Bk ; 13: allocate bandwidth to T-CONT-4, and T-CONT-5 of all H-ONUs according to Eq. (9) → BAbe ; 14: recycle the remaining bandwidth Bk ← Bk ; 15: if Bk > 0 then 16: go to line 11 to allocate bandwidth for L-ONUs whose bandwidth cannot be 17: 18: 19: 20: 21:
satisfied→ BAna and BAbe ; else calculate Uti4 , Tt _ave ; end if end if Output Uti4 , Tt _ave ;
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Fig. 3. Upstream network throughput for different numbers of wavelengths. Fig. 6. Utilization of different types of bandwidth.
Fig. 4. Bandwidth utilization for different algorithms.
Fig. 7. Throughput of different types of bandwidth. Table 2 Parameters of each traffic source. Traffic Type
Packets size (Byte )
Average packet interval (ms )
Average speed (Mbps )
T-CONT-1 T-CONT-2
Fixed value = 500 Uniform Distribution (128-3000) Uniform Distribution (64-1500) Three-state model Three-state model
0.125 0.25
32 50.2
0.115
108.35
0.16 0.16
45.4 45.4
T-CONT-3
T-CONT-4 T-CONT-5
the proposed algorithm takes into account simultaneous transmissions at several wavelengths and the remaining bandwidth can be fully utilized for distribution, resulting in a relatively ideal effect. End-to-end delay is an important performance indicator for TWDMPON system as well. Fig. 5 compares the end-to-end delay versus ONU load for HF-DWBA, UBA-DRAS, and LP-DWBA algorithms. It can be seen that end-to-end delay increases with the increasing load. Before the normalized load reaches 0.6, the delay of the network is still in a relatively stable state. However, as ONU load sequentially increases, the
Fig. 5. Average packet delay for different algorithms.
Fig. 4 shows the utilization of bandwidth for HF-DWBA, UBA-DRAS, and LP-DWBA algorithms under four different wavelengths. It can be seen that utilization of upstream bandwidth of the three algorithms enhances with the increase of the load. Fig. 5 illustrates that the proposed HF-DWBA algorithm slightly operates better than UBA-DRAS and LP-DWBA methods in terms of bandwidth utilization. The reason is that 170
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Fig. 8. Average delay of T-CONTs.
corresponding delay is longer as well.
delay dramatically becomes worse. Because bandwidth requests from ONUs basically exceed the minimum guaranteed bandwidth, the network packets have to wait to be processed by OLT, causing a queuing delay. Besides, the queuing delay is larger than that of the propagation delay and processing delay of the packets, thus, the average packet delay drastically increases. Comparing with UBA-DRAS and LP-DWBA methods, the delay of HF-DWBA algorithm has been slightly improved. The proposed HF-DWBA algorithm can effectively decrease the network delay and satisfy the requirement of QoS, while maintaining a high resource utilization. Aiming at the different types of traffic corresponding to the four kinds of bandwidth, Fig. 6 displays various kinds of bandwidth utilization ratio for diverse loads. As depicted in Fig. 6, the guaranteed bandwidth utilization ratio is higher than the other three types of bandwidth utilization ratio. Additionally, when the load is higher than 0.5 Erlang, guaranteed bandwidth utilization ratio varies within a certain range. It is because guaranteed bandwidth ensures the basic bandwidth required by ONUs, leading to a fair distribution of ONUs, and maintains QoS. When ONU’s load exceeds 0.6 Erlang, both utilization ratios of non-guaranteed bandwidth and best-effort bandwidth decrease. This can be justified as most of ONUs cannot achieve enough bandwidth when the network load is large. Fixed bandwidth and guaranteed bandwidth have priority in bandwidth allocation within ONUs and thus the traffic of non-guarantee and best-effort bandwidths are attenuated. This algorithm reflects fairness and flexibility of bandwidth allocation. Fig. 7 shows various types of bandwidth throughput under a variety of loads. In order to perfectly meet the bandwidth requirements for each ONU, we can observe that the throughput of guaranteed bandwidth is relatively high, while the throughput of besteffort bandwidth is relatively small. In TWDM-PON, the total rate of transmission for each wavelength is 2.25 Gbps. The delay of each T-CONT is assessed within the ONUs. Each ONU contains T-CONT-1, 2, 3, 4, 5, and the average total rate of TCONT’s traffic source is 281.25 Mbps. The parameters of traffic source are shown in Table 2. Fig. 8 illustrates the average delay for various T-CONTs versus ONU load. The results of simulation show that the average delay for T-CONT1 is about 0.225 ms , which is less than a standard value (1.5 ms) recommended by the G.982 agreement of ITU-T. The average delay of TCONT-3 is less than that of T-CONT-1 because of its high average transmission rate. T-CONT-4 mainly allocates the best-effort bandwidth. Once the load increases, the best-effort bandwidth cannot be properly satisfied and gradually decreases, and the delay accordingly reduces as well. For T-CONT-2, with the increasing load, the delay increases. The reason is that the larger the traffic, the longer the queue delay. For T-CONT-5, since it contributes in every step of bandwidth allocation, the bandwidth is synthetically obtained by all steps, the
6. Conclusions In this paper, HF-DWBA algorithm was proposed based on in-depth analysis of system architecture, as well as dynamic bandwidth allocation mechanism in TWDM-PON system. According to different grades of ONUs, the proposed algorithm is optimized in wavelength selection and bandwidth allocation based on XG-PON system. The algorithm can achieve upstream bandwidth allocation including five types of T-CONTs and four bandwidth allocation modes. Combined with different SLAs, the priorities of ONUs are fully taken into account to meet the requirements of different bandwidths. Therefore, the proposed algorithm can support diverse types of traffic, as well as achieving multi-traffic broadband access. The simulation results show that HF-DWBA algorithm possesses an appropriate performance on bandwidth utilization ratio and traffic delay. Furthermore, the algorithm also ensures the fairness of resource allocation. In future researches, we will study a coupled relationship between wavelength assignment and bandwidth allocation by exploration of some favorable characteristics in wavelength assignment and bandwidth allocation processes, which can be used to promote the 2D scheduling of TWDM-PON system. Acknowledgements This work is supported by the National Natural Science Foundation of China (61501308), Science and technology research project of Liaoning Provincial Department of Education (LG2016/6), Postdoctoral Research Station project of Shenyang Ligong University (2016), Special Foundation of Doctoral Program of Shenyang Ligong University (2015), Key Laboratory Open Foundation of Shenyang Ligong University (2014, 2017), Liaoning Fourth Batch of Distinguished Professor Project (2014), Liaoning BaiQianWan Talents Program (2016), Liaoning Natural Science Foundation (20170540793), Distinguished Professor Project in Liaoning Province (2017), Program for Liaoning Innovative Research Team in University (2017). References [1] X. Gong, L. Guo, Y. Liu, Y. Zhou, H. Li, Optimization mechanisms in multi-dimensional and flexible PONs: challenging issues and possible solutions, Opt. Switching Networking 18 (Part1) (2015) 120–134. [2] X. Gong, W. Hou, L. Guo, L. Zhang, Dynamic energy-saving algorithm in green hybrid wireless-optical broadband access network, Optik 124 (14) (2013) 1874–1881. [3] I.S. Hwang, A. Rianto, A.F. Pakpahan, Software-defined Peer-to-Peer file sharing architecture for TWDM PON[C], Proc. of Wireless and Optical Communication Conference, 2018, pp. 1–4.
171
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L. Zhang et al.
[17] Y. Xiong, J.B. Tang, H. Zhang, et al., User-behavior aware dynamic resource allocation strategy in TWDM-PON, Acta Electron. Sin. (2016). [18] A. Dixit, B. Lannoo, D. Colle, et al., Dynamic bandwidth allocation with optimal wavelength switching in TWDM-PONs, Proc. of International Conference on Transparent Optical Networks, 2013, pp. 1–4. [19] G. Das, B. Lannoo, H.D. Jung, et al., A new architecture and MAC protocol for fully flexible hybrid WDM/TDM PON, Proc of European Conference on Optical Communication, 2009, pp. 1–2. [20] M. Radivojević, P. Matavulj, Novel wavelength and bandwidth allocation algorithms for WDM EPON with QoS support, Photon Netw. Commun. 20 (2) (2010) 173–182. [21] M. Radivojević, P. Matavulj, Advanced scheduling algorithm for quality of service support in WDM EPON, Opt. Express 19 (26) (2011) 587–593. [22] Mirjana R. Radivojević, P.S. Matavulj, Highly flexible and efficient model for QoS provisioning in WDM EPON, IEEE/OSA J. Opt. Commun. Network. 5 (8) (2013) 921–931. [23] M.S. Han, Performance evaluation of dynamic bandwidth allocation algorithm for TWDM PON, J. Convergence Inform. Technol. (2013). [24] Z. Zhang, H.U. Xintian, X. Chen, dynamic resource scheduling in ring-tree TWDMPON, ZTE Technol. J. 20 (5) (2014) 29–33. [25] N. Cheng, J. Gao, C. Xu, et al., Flexible TWDM PON system with pluggable optical transceiver modules, Opt. Express 22 (2) (2014) 2078. [26] M. Bi, S. Xiao, L. Yi, et al., Power budget improvement of symmetric 40-Gb/s DMLbased TWDM-PON system, Opt. Express 22 (6) (2014) 6925–6933. [27] X.S. Wang, Y.U. Shao-Hua, J.Y. Dai, Novel algorithm for dynamic bandwidth scheduling in WDM EPON, J. Commun. 33 (2) (2012) 69–75. [28] R. Gu, Y. Ji, P. Wei, et al., Software defined flexible and efficient passive optical networks for intra-datacenter communications, Opt. Switch. Network. 14 (3) (2014) 289–302. [29] R. Gu, S. Zhang, Y. Ji, et al., Efficient software-defined passive optical network with network coding, Photon Netw. Commun. 31 (2) (2016) 239–250. [30] K. Kondepu, A. Sgambelluri, L. Valcarenghi, et al., An SDN-based integration of green TWDM-PONs and metro networks preserving end-to-end delay, Proc. of Optical Fiber Communications Conference & Exhibition, IEEE, 2015. [31] J. Zhang, N. Ansari, Scheduling hybrid WDM/TDM passive optical networks with nonzero laser tuning time, IEEE/ACM Trans. Network. 19 (4) (2011) 1014–1027. [32] F. Rawshan, Y. Park, Fault-tolerable and SLA-supportive architecture for TWDMPON systems, Photon Network Commun. 30 (2) (2015) 143–149.
[4] T. Kawanaka, T. Ashida, S. Yoshima, et al., Experimenta investigation into burstmode wavelength drift of a mass-produced 10 Gbit/s EML for TWDM-PON[C], Proc. of European Conference on Optical Communication, (2018). [5] L. Xue, L. Yi, H. Ji, et al., Symmetric 100-Gb/s TWDM-PON based on 10G-class optical devices enabled by dispersion-supported equalization, J. Lightwave Technol. (2018) 99 1-1. [6] X. Wang, L. Wang, C. Cavdar, et al., Handover reduction in virtualized cloud radio access networks using TWDM-PON fronthaul, IEEE/OSA J. Opt. Commun. Network. 8 (12) (2017) B124–B134. [7] P. Iannone, A. Gnauck, M. Straub, et al., An 8 x 10-Gb/s, 42-km, high-split TWDM PON featuring distributed Raman amplification and a remotely powered intelligent splitter, J. Lightwave Technol. 99 (2017) 1-1. [8] A. Dixit, B. Lannoo, D. Colle, et al., Wavelength switched hybrid TDMA/WDM (TWDM) PON: a flexible next-generation optical access solution, Proc. of ICTON, 2012, pp. 1–5. [9] Y. Luo, M. Sui, F. Effenberger, Wavelength management in time and wavelength division multiplexed passive optical networks (TWDM-PONs), Proc. of Global Communications Conference, 2012, pp. 2971–2976. [10] A.L. Teixeira, J.D. Reis, A. Shahpari, et al., Spectral Management in Flexible Multiwavelength PONs, 2013, pp. 1–3. [11] Y. Luo, X. Yan, F. Effenberger, Next generation passive optical network offering 40Gb/s or more bandwidth, Proc. of Communications and Photonics Conference, 2012, pp. 1–3. [12] F. Gao, X.Q. Chen, S.W. Zhao, Dynamic bandwidth allocation algorithm with high bandwidth utilization for 1OG EPON system, Opt. Commun. Technol. 40 (6) (2016) 25–27. [13] Constantine A. Kyriakopoulos, Georgios I. Papadimitriou, Predicting and allocating bandwidth in the optical access architecture XG-PON, Opt. Switch. Network. (2017) 91–99. [14] M.S. Han, Performance evaluation of dynamic bandwidth allocation algorithm for XG-PON using traffic monitoring and intra-scheduling, Int. J. Software Eng. Appl. 9 (8) (2015) 207–216. [15] J.Y. Lee, I. Hwang, A.A. Nikoukar, et al., Comprehensive performance assessment of bipartition upstream bandwidth assignment schemes in GPON, IEEE/OSA J. Opt. Commun. Network. 5 (11) (2013) 1285–1295. [16] H. Wang, Y. Liang, R. Gu, et al., LP-DWBA: a DWBA algorithm based on linear prediction in TWDM-PON[C], Proc. of International Conference on Optical Communications and Networks, 2015, pp. 1–3.
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Optical Fiber Technology journal homepage: www.elsevier.com/locate/yofte
High-priority first dynamic wavelength and bandwidth allocation algorithm in TWDM-PON
T
⁎
Lincong Zhanga, Jifeng Qia, Kefeng Weib,c, Wenbo Zhanga, , Yongxin Fenga, Weigang Houa a
School of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, China School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China c Shen Kan Engineering and Technology Corporation, MCC., Shenyang 110169, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: TWDM-PON Wavelength selection Dynamic bandwidth allocation T-CONT
Time and wavelength division multiplexing passive optical network (TWDM-PON) is the mainstream scheme of the next generation access network, and it possesses a number of unique characteristics such as high-bandwidth, long-distance data transmission, and connecting lots of users. As the difference among user traffic demands increases, in order to effectively decrease the network delay and improve resource utilization, a high-priority first dynamic wavelength and bandwidth allocation (HF-DWBA) algorithm in TWDM-PON system is proposed in this study. According to the service-level agreement (SLA), in order to determine the priority of an optical network unit (ONU), the proposed algorithm ensures the high-level ONU traffic distribution in terms of wavelength assignment and bandwidth allocation, and it can execute five types of transmission containers (T-CONTs) as well as four kinds of bandwidth allocation strategies. The results of simulation show that in comparison with traditional algorithms, the proposed HF-DWBA algorithm can effectively reduce end-to-end time delay and improve bandwidth utilization ratio, while making fairness among different types of bandwidth allocation strategies.
1. Introduction In order to meet a growing demand for high-bandwidth and traffic perceived by users, a number of new high-bandwidth services have been developed (e.g., network disk and cloud computing), possessing some challenges to network access control. Traditional optical access networks [1,2], such as Ethernet passive optical network (EPON) and gigabit passive optical network (GPON), have not still fully satisfied the users’ demands. Thus, full service access network (FSAN) commenced to operate on the basis of next generation-passive optical network (NGPON), in which some requirements in 2011, indicating the time of beyond 10 Gbps is coming [3,4]. In 2012, some studies reported that time and wavelength division multiplexed passive optical network (TWDM-PON) is a primary solution to NG-PON [5–7]. In TWDM-PON, resource scheduling strategy indicates the system performances (e.g., bandwidth utilization, throughput, delay, etc.). Since four wavelengths are used in TWDM-PON and if there is no reasonable scheduling strategy for the network, on the one hand, some wavelengths may be over-use and therefore lead to large delay; on the other hand, other wavelengths may be bare and lead to unbalance on bandwidth usage. Therefore, designing a robust approach to effectively
⁎
and reasonably realize the resource scheduling on wavelength and bandwidth is significant. Some previous studies have developed a twodimensional (2D) resource scheduling method by using the dual flexibility (i.e., wavelength and bandwidth flexibilities) of TWDM-PON [8–11]. In resource scheduling issue, in order to support differentiated QoS, TWDM-PON divides bandwidth into four types, namely, fixed bandwidth, guaranteed bandwidth, non-guaranteed bandwidth, and the best effort bandwidth [12]. In TWDM-PON, the monitoring and control of the upstream traffic convergence process of all ONUs are centralized by OLT. In other words, each ONU continuously reports the respective load status of their transmission containers (T-CONTs) to OLT. As a central core of transmission convergence (TC) layer, OLT subsequently monitors the status of all T-CONTs and adjusts their location in time. Simultaneously, OLT processes two important functions, involving media access control for upstream direction and dynamic bandwidth adjustment. In the mentioned process, both of basic monitoring and basic traffic scheduling units are T-CONTs [13–15]. T-CONT is generally divided into five types, each ONU has five queues corresponding to TCONT-1, 2, 3, 4, 5. T-CONT-1 corresponds to a fixed bandwidth allocation, and its delay requirement is strictly controlled. T-CONT-2
Corresponding author. E-mail address: [email protected] (W. Zhang).
https://doi.org/10.1016/j.yofte.2018.12.029 Received 11 September 2018; Received in revised form 9 December 2018; Accepted 26 December 2018 1068-5200/ © 2019 Elsevier Inc. All rights reserved.
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TWDM-PON resource allocation, mainly take into account the ONU as a tunable transceiver, bandwidth allocation for a fixed network data traffic, and 2D resource scheduling problem based on EPON. Wang et al. [16] proposed a dynamic wavelength and bandwidth allocation (DWBA) algorithm based on a linear prediction method to schedule resources. The algorithm not only dynamically allocates the bandwidth resources in one wavelength channel, but also statistically provides multiplexing among various wavelength channels, allowing bandwidth to be effectively allocated. However, this algorithm has not considered different types of traffic and ONU priorities. Xiong et al. [17] proposed a user-behavior aware dynamic resource allocation strategy in TWDM-PON. According to the dynamic traffic status presented by user-behaviors, the ONU polling mechanism is adjusted in real-time to effectively reduce the network delay and promote the fairness of resource allocation, while this algorithm is not applicable for XG-PON. Dixit et al. [18] presented a dynamic bandwidth allocation algorithm with optimal wavelength switching in TWDM-PONs, improving network delay and channel utilization. Das et al. [19] proposed a novel architecture and medium access control (MAC) protocol for fully flexible hybrid WDM/TDM PON. This algorithm possesses a low queuing delay; however, it cannot fully exploit the advantages of multiwavelength channels. Some previous studies [20–22] proposed a resource allocation strategy based on the service level. This algorithm reduces the traffic queuing delay; however, it may cause a greater waste of bandwidth because few wavelengths sharing among ONUs. Han [23] assessed the performance of a dynamic bandwidth allocation algorithm for TWDM-PON system. Zhang et al. [24] developed a dynamic resource scheduling algorithm in ring-tree TWDM-PON system and proposed a maximum bandwidth utilization ratio algorithm as well as minimum tuning time algorithm. Cheng et al. [25] and Bi et al. [26] attempted to propose a flexible TWDM-PON system with pluggable optical transceiver modules by using two or more transceivers in one system, as well as combination of bandwidth schedule among ONUs to realize simultaneously the dynamic scheduling for both wavelengths and time slots. However, this approach requires high-cost of ONUs and does not take bandwidth allocation within ONUs into account. Wang et al. [27] developed a new method for dynamic bandwidth scheduling in WDM EPON system, without consideration of traffic diversity. There are also some researches on software defined TWDM-PON [28–30], Gu et al. [28] used software defined technology to provide the flexibility on wavelength assignment according to traffic statistics dynamically. Gu et al. [29] also proposed a software-defined passive optical network architecture with network coding (NC) to reduce downstream bandwidth consumption and thus increase the throughput and network efficiency. Kondepu et al. [30] proposed an SDN node controller architecture and a proper scheduling priority to preserve the overall service level. However, the mentioned studies often encountered two key problems. First, the developed TWDM-PON scheduling algorithms have mainly focused on EPON system and neglected performing studies on XG-PON system. Actually, EPON and XG-PON use different protocols in media access control. Besides, on the basis of XG-PON system, few twodimensional dynamic allocation algorithms for the wavelength and bandwidth flexibility were yet developed. Second, most of the previous researches have not taken into account the users’ priority and diversity of different types of traffic, meaning inadequate attention to the resource scheduling fairness in addition to different requirements of QoS. Thus, this study attempts to overcome these two main problems.
Table 1 Different types of bandwidth corresponding to different types of T-CONTs. Bandwidth Type
T-CONT Type 1
Reserved Bandwidth Extra Bandwidth
Fixed Bandwidth Guaranteed Bandwidth Non-guaranteed Bandwidth Best Effort Bandwidth
2
3
√
√ √
4
5
√
√ √ √ √
√
represents a guaranteed bandwidth allocation (i.e., bandwidth required within a specific range to meet a certain delay). T-CONT-2 is typically used for voice over Internet protocol (VoIP). T-CONT-3 provides guaranteed and non-guaranteed bandwidths, which is applicable to both services of assurance requirements and network traffic “bursting”. The main characteristic of T-CONT-4 is that there is no bandwidth guarantee, and the system congestion directly affects the bandwidth allocation, which is appropriate for network traffic with low requirements of packet loss, delay, and jitter. Moreover, T-CONT-5 is a combination of these four kinds of T-CONT, and it presents all types of bandwidth and supports all kinds of traffic as well. Table 1 lists the types of bandwidth allocation supported by different types of T-CONTs, and time delay sensitivity for different traffic flows. To assure the fairness of wavelength assignment scheme among ONUs and bandwidth allocation for different types of T-CONTs innerONUs, a high-priority first dynamic wavelength and bandwidth allocation (HF-DWBA) algorithm is proposed. This algorithm indicates the priority of ONUs based on service level agreement (SLA) [27], performing through a resource scheduling strategy both at OLT and ONU sides. This algorithm implements five types of T-CONTs as well as four kinds of bandwidth allocation and can effectively reduce the network delay and improve resource utilization. The performance of the proposed algorithm can be summarized as follows. 1) In order to take into account actual demands of different users and ensure the fairness of resource scheduling, the priority of the ONUs is defined based on SLA. Allocate bandwidth for high-level ONUs at first, and then for low-level ONUs. 2) To make the selection of wavelength be more efficient, a singlequeue multi-service stations queuing model is developed based on the characteristic of simultaneous transmission at multiple wavelengths in TWDM-PON. This model can reduce the queuing delay of each ONU and average delay of each packet. 3) In order to avoid network congestion caused by network traffic bursting, which will result in a remarkable time delay, a threshold is set for each wavelength. When the network traffic on a certain wavelength reaches 90% of the maximum capacity, this wavelength stops allocating bandwidth to the next ONUs. This can guarantee QoS for diverse services. 4) During bandwidth allocation, different bandwidth demands of five types of T-CONT are taken into account, and bandwidth allocation is on the basis of XG-PON structure to satisfy requirements for different traffic flows, delay, jitter, rate of packet loss, and various QoS. The rest of this paper is organized as follows. Section 2 elaborates previous studies on resource allocation in PON. Section 3 contains the problems’ definition in terms of wavelength assignment and bandwidth allocation. Section 4 presents the proposed HF-DWBA algorithm in detail. The results of numerical simulation are shown in Section 5. Section 6 summarizes the findings achieved in this study.
3. Problem formulation In this section, first of all, the notations used in the paper are presented, and then it will be attempted to describe how we aim to overcome the wavelength assignment problem and bandwidth allocation problem.
2. Related works Currently the on-going researches, with the aim of studying the 166
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3.1. Notations Notations in Wavelength Assignment Problem:
• M: Number of wavelengths in the whole network. • N: Number of ONUs in TWDM-PON. • λ : Maximum capacity of a single wavelength. • Req : The bandwidth request of ONUs. x : In period t , the status of ONU in the active wavelength m is • inquired. Herein, x =1 denotes that ONU is in the active wavelim
t im
i
Fig. 1. Schematic illustration of a multi-service single queue model.
i
t im
i
length m .
In TWDM-PON system, there are no restrictions for the request of the upstream direction, and each request is independent as well. In a certain period, the number of ONUs obeys the Poisson distribution of a stationary arrival rate. The internal queuing of ONUs is a single queue; the time of responding the signal receiver at OLT side to each ONU is independent; the request arrival time interval and processing time per request are independent; the duration of signal processing for each signal receiver is the same as well. The queuing model used in this study is shown in Fig. 1. According to the established model, the wavelength assignment problem can be formulated as follows:
• y : In period t , the activation of wavelength m is inquire d. Besides, y =1 represents that the wavelength m is active. ρ : The status of bandwidth allocation on current period is in• quired. When the i ONU is assigned to the m wavelength, ρ = 1 t m t m
i, m
th
th
i, m
otherwise, ρi,m = 0 . Notations in Bandwidth Allocate Problem:
• ONU : Set of ONUs in the network. • B: Total distributable bandwidth per polling cycle. • B (i, j): Fixed bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 1, 5. • B (i, j): Guaranteed bandwidth obtained by T-CONT of type j in the i H-ONU, i = 1, 2, …, N, j = 2, 3, 5. • B (i, j): Guaranteed bandwidth obtained by T-CONT of type j in the i L-ONU, i = 1, 2, …, N, j = 2, 3, 5. • B (i, j): Guaranteed bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 2, 3, 5. • B (i, j): Non-guaranteed bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 3, 5. • B (i, j): Best-effort bandwidth obtained by T-CONT of type j in the i ONU, i = 1, 2, …, N, j = 4, 5. • B : Total bandwidth required for each T-CONT in the ONU. • B : Minimum guaranteed bandwidth obtained by per ONU. • B : Default fixed bandwidth allocated to each ONU. • B : Fixed bandwidth required for ONUs. • B : Guaranteed bandwidth required for ONUs. • B : Total bandwidth allocated to ONUs. • B : Guaranteed bandwidth allocated to ONUs. • B : Non-guaranteed bandwidth allocated to ONUs. • B : Best-effort bandwidth allocated to ONUs. • B : Remaining bandwidth. • B : Guaranteed bandwidth required for each ONU. • B : Non-guaranteed bandwidth required for each ONU. • B : Best-effort bandwidth required for each ONU. • n: The number of L-ONUs at the time of allocating guaranteed bandwidth. • n : The number of H-ONUs that have not been yet met the bandth
f
M
Maximize
Ha
N
∑ ∑ ρi,m Reqi m=1 i=1
(1)
th
Subjected to
La
th
N
∑ ρi,m Reqi ≤ λlim, ∀ m ∈ {1, 2, ⋯, m}
a
th
i=1
(2)
na
∑ ximt = 1, ximt , ymt ∈ {0, 1}, ∀ i, t
th
m
ba
th
Eq. (1) calculates optimization target for the wavelength selection model to find out the optimal assignment method, satisfying the maximum bandwidth request. The available constraint in Eq. (2) represents that the single wavelength capacity does not exceed the maximum threshold to efficiently guarantee QoS. The constraint in Eq. (3) demonstrates that an ONU at a certain time only belongs to an active wavelength. The wavelength selection for TWDM-PON system can be formulated by the above-mentioned model. Although AMPL/CPLEX optimization modeling language can be used to achieve an optimal allocation scheme, an optimal solution cannot be applied to the actual network. As wavelength selection belongs to a NP-hard problem [31], an optimal solution cannot guarantee the fairness among different ONUs. Thus, a heuristic algorithm is developed to obtain an approximate optimal solution for wavelength assignment.
R
ensure fix A fix R assure R
A assure A na A be A
k a R na R be R
1
•
(3)
3.3. The bandwidth allocation problem
width requirements at the time of allocating non-guaranteed bandwidth. n2 : The number of H-ONUs that do not satisfy the current bandwidth requirements at the time of allocating the best-effort bandwidth.
When an ONU is assigned to an available wavelength, the bandwidth allocation mechanism to this wavelength channel and the number of time slots to be used to send a message are great challenges. In order to gain the best experience by users, as well as realize the maximization and efficient and fairness resource allocation, an optimal dynamic bandwidth allocation algorithm not only should effectively allocate the channel resources, but also must ensure the fairness among ONUs. In this paper, a reasonable and efficient dynamic bandwidth allocation algorithm is proposed for different types of T-CONT traffic in the ONUs. For this purpose, the bandwidth allocation problem is formulated as follows:
3.2. The wavelength assignment problem In wavelength assignment process, all ONUs are arrayed in one queue, waiting for OLT to assign the signal receiver. In other words, the number of receivers is M (that is the number of wavelengths in TWDMPON system), while there is only one ONU queue. In TWDM-PON system, ONUs are assumed as the customer sources in queuing theory. A signal receiver at OLT side is assumed as a service station in queuing theory. We suppose that the number of wavelengths supported by the TWDM-PON system is equal to “c”, which is assumed as the number of service stations in the queuing theory as well. Thus, the M/M/c queuing model is utilized to select the wavelength.
N
5
Maximize ∑ ∑ (Bf (i, j ) + Bna (i, j ) + Bbe (i, j )) i=1 j=1
Subjected to 167
(4)
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B−
∑
stops allocating the bandwidth to the next arriving ONUs. After that, bandwidth is sequentially allocated to the next arriving ONUs on the remaining wavelengths. (d) After completing the wavelength selection for H-ONUs, the available wavelength is assigned to L-ONUs according to the above-mentioned procedure. (e) If all the wavelengths are saturated, the remaining ONUs are assigned to each wavelength based on their traffic capacity ranging from small to large order until all ONUs are allocated. (2) When BRtotal > BAtotal :
Bf (i, j ) ≥ 0, j = 1, 5 (5)
1≤i≤N
Bensure ≥ Ba (i, j ), ∀ i ∈ ONU , j = 2, 3, 5
(6)
Bf (i, j ) = BAfix , ∀ i ∈ ONU , j = 1, 5
(7)
BRa, BR ≤ Beasure BHa (i, j ) = ⎧ , ∀ i ∈ ONU , j = 2, 3, 5 ⎨ Beasure − BAfix , BR > Beasure ⎩
(8)
BLa (i, j ) =
min{BRa,
Bna (i, j ) =
min{BRna,
Bk / n}, ∀ i ∈ ONU , j = 2, 3, 5
(9)
Bk / n1}, ∀ i ∈ ONU , j = 3, 5
(10)
Bba (i, j ) = min{BRbe , Bk / n2}, ∀ i ∈ ONU , j = 4, 5
(11)
Each wavelength sequentially assigns the minimum guaranteed bandwidth Beasure to all ONUs. To ensure that each ONU can be allocated to a certain bandwidth, H-ONU is firstly assigned, and then LONU is assigned. Afterwards, the required bandwidth is allocated to each ONU according to the proposed bandwidth allocation algorithm at ONU side. Due to the burstiness of a traffic stream, in a polling cycle, some ONUs may have a small demand of traffic, leading to a surplus of minimum guaranteed bandwidth. In order to avoid unbalance and bandwidth wastes during bandwidth allocation, we recycle excess bandwidth into the next bandwidth allocation loop. For making simplicity in presentation, the notations of wavelength assignment parameters are presented as follows. Ocur is the traffic of ONUs, BH − ONUi denotes the bandwidth required for high-level ONUs, BL − ONUi represents the bandwidth required for low-level ONUs, Buti is the utilization of upstream bandwidth, Bthr denotes the upstream network throughput, and Tave is the average packet delay. The pseudo-code of wavelength assignment is described in Algorithm 1.
Eq. (4) calculates an optimization target for the bandwidth allocation model, aiming to find out the optimal bandwidth allocation method, satisfying the requirements of each type of bandwidth within each ONU. The constraint available in Eq. (5) demonstrates that the total allocable bandwidth is larger than that of the fixed allocated bandwidth. In addition, the constraint existed in Eq. (6) illustrates that there is enough bandwidth to be allocated for guaranteed bandwidth. The constraints in Eqs. (7)–(11) show the allocation equations for fixed bandwidth, guaranteed bandwidth, non-guaranteed bandwidth, and best-effort bandwidth. To develop an optimal bandwidth allocation algorithm, we can map the traffic of various priorities and kinds to different T-CONTs by this algorithm. On the other hand, we can also differentiate traffic and ensure different types of traffic with diverse requirements of QoS based on the proposed bandwidth allocation algorithm, regarding T-CONT as a control unit.
Algorithm 1: Wavelength assignment approach in TWDM-PON 4. HF-DWBA algorithm
Input: M, N, λlim , Ocur , BH − ONUi , BL − ONUi ; topology of the TWDM-PON; caching queue of ONU set Oi ={1, 2, 3, …, N}, H-ONU set OH = {0, 2, 3, …, N}, LONU set OL ={0, 2, 3, …, N}; Output: Buti , Bthr , Tave . 1: the number of upstream packets sent by each ONU follows Poisson distribution: Ocur ∈ Oi ; 2: OLT collects all ONUs’ information, put H-ONUs in OH , put L-ONUs in OL ; 3: while BH − ONUi < λlim do 4: assign H − ONUi to the wavelength λ1, λ2 , λ3 , λ 4 sequentially; 5: ifBH − ONUi > λlim then 6: this wavelength stops allocating bandwidth, then allocate bandwidth to the next arriving ONUs by the next wavelength; 7: end if 8: end while 9: while BL − ONUi < λlim do 10: assign L − ONUi to the wavelength λ1, λ2 , λ3 , λ 4 sequentially; 11: if BL − ONUi > λlim then 12: this wavelength stops allocating bandwidth, then allocate bandwidth to the next arriving ONUs by the next wavelength; 13: end if 14: end while 15: calculate Buti , Bthr , Tave ; 16: Output Buti , Bthr , Tave .
In this paper, the proposed HF-DWBA algorithm dynamically allocates the resources at the OLT and ONU sides. After wavelength selection at the OLT side, the bandwidth is allocated at the ONU side. In a network packet, due to different requirements of QoS of various traffic, some kinds of traffic are sensitive to the delay (e.g., voice and video), while others are only sensitive to the cell loss rate (e.g., file transfer protocol (FTP) and E-mail). Therefore, it is necessary to distinguish different types of traffic before performs the bandwidth allocation. 4.1. Wavelength assignment algorithm The proposed algorithm assigns different weight coefficients for ONUs based on user’s SLA [29], and then divides ONUs into high- and low-priority levels. According to the characteristics of multi-wavelength simultaneous transmission of TWDM-PON, a queuing model is developed representing a multi-service single queue system. When we assign wavelengths to ONUs, we should first meet the requirements of high-level ONUs, and then satisfy the requirements of low-level ONUs to ensure a fair scheduling process among ONUs. In order to avoid congestion and increase of delay caused by gusty traffic flow when the network is busy, as well as ensuring the QoS, the proposed algorithm assigns the maximum capacity threshold for each wavelength. For making simplicity in presentation, BAtotal denotes the total available bandwidth, and BRtotal is total request bandwidth for all ONUs. The whole process of the proposed wavelength assignment algorithm is described as follows:
4.2. Bandwidth allocation algorithm In the internal of ONUs, ONU allocates bandwidth to different types of T-CONTs. The TWDM-PON system can support five types of TCONTs, as well as four different types of bandwidth. Before algorithm description, the required parameters are defined as follows: The whole process for the proposed bandwidth allocation algorithm is described as follows:
(1) When BRtotal ≤ BAtotal (a) OLT collects all ONUs’ information and classifies them into high-level ONUs (H-ONUs) and low-level ONUs (L-ONUs); (b) According to the developed multi-service single queue model, the wavelength assignment for H-ONUs on all wavelengths is transformed into packing problem. (c) When the traffic of a wavelength reaches 90%, this wavelength
(1) When BR ≤ BA , allocate bandwidth to each ONU according to the requirement of T-CONT. (2) When BR > BA , allocate bandwidth according to the following methods: 168
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Step 1: Allocate fixed bandwidth BAfix to T-CONT-1 and T-CONT-5 of each ONU. Step 2: Allocate guaranteed bandwidth BAassure to T-CONT-2, TCONT-3, and T-CONT-5 of each ONU. At the first stage, allocate bandwidth to H-ONUs. When BR > Bensure , BR ≤ Bensure , BAassure BAassure (H − ONUi ) = Bensure − BAfix ; when (H − ONUi) = BRassure ; and recycle the remaining bandwidth Bk . Secondly, allocate bandwidth to L-ONUs. Then, count the remaining BAassure (L − ONUi ) = Bk > 0 , bandwidth If Bk . assure min{BR (L − ONUi ), Bk / n} (n is the number of L-ONUs at this time); and then, recycle the remaining bandwidth Bk . Step 3: Allocate non-guaranteed bandwidth BAna to T-CONT-3 and TCONT-5 of each ONU. Count the remaining bandwidth Bk . If Bk > 0 , BAna (H − ONUi ) = min{BRna (H − ONUi ), Bk / n1} (n1 is the number of H-ONUs that have not been yet satisfied the bandwidth requirements); and then, recycle the remaining bandwidth Bk . Step 4: Allocate best-effort bandwidth BAbe to T-CONT-4 and T-CONT5 of each ONU. Count the remaining bandwidth Bk . If Bk > 0 , BAbe (H − ONUi ) = min{BRbe (H − ONUi ), Bk /n2} (n2 is the number of HONUs that do not meet the current bandwidth requirements); then, recycle the remaining bandwidth Bk . Step 5: If Bk > 0 , according to the above-mentioned methods, allocate non-guaranteed bandwidth as well as best-effort bandwidth to L-ONUs whose bandwidth requirements are not satisfied, until all the bandwidth is allocated.
Fig. 2. Bandwidth utilization of different numbers of wavelengths.
5. Performance evaluation 5.1. Parameter setting of simulation environment In this section, we compare the performance of the proposed HFDWBA algorithm with LP-DWBA [3] and UBA-DRAS [4]. LP-DWBA is a linear prediction scheme and showed advances in average packet delay. To solve the problem that the differences between users’ behavior increase, UBA-DRAS divides one cycle into several sub-cycles to alternatively send different level business. Some parameters in simulations are assumed. We assumed that the grade of ONUs is divided into two categories: H-ONU and L-ONU. The distance between OLT and ONUs is 20 km. The number of ONUs, N, is 32, the number of wavelengths, M, is 2, 4, 6, 8, respectively; the bit-rate of each wavelength is 2.5 Gbps [7], the maximum cycle time is 2 ms, and the guard time is 1 μs [32]. ONU data source follows the Poisson distribution. Packet sizes are uniformly distributed between 64 and 1518 bytes.
According to the specific steps required for execution of the bandwidth allocation algorithm, a detailed description of the pseudo-code is illustrated in Algorithm 2. Herein, T denotes the number of T-CONTs in each ONU, D represents the number of bandwidth types, Uti4 is the utilization of different types of bandwidth in the ONU, and Tt _ave represents the average delay of T-CONT. Algorithm 2: Bandwidth allocation approach in ONU Input: M, N, T, D, B; H-ONU set OH ={0, 1, 2, 3, …, N}, L-ONU set OL ={0, 1, 2, 3, …, N}; Output: Uti4 , Tt _ave ; 1:if BR ≤ BA then 2: while T-CONT whose bandwidth cannot be satisfied do 3: allocate bandwidth to each ONU according to the requirement of T-CONT; 4: end while 5: else 6: judge the number of H-ONUs and L-ONUs, put H-ONUs in OH , put L-ONUs in OL ; 7: allocate bandwidth to T-CONT-1, and T-CONT-5 of all ONUs according to Eq.
5.2. The analysis of simulation results Fig. 2 shows the effect of different loads on the utilization of upstream bandwidth when HF-DWBA allocates the resources at different wavelengths. It can be seen that as the load increases, the utilization of upstream bandwidth increases, especially linearly rises when M is equal to 6 and 8. This is due to the increase of the traffic at each wavelength as well as gradually reducing the idle time. When M is 2, the utilization of bandwidth gradually trends stably after the load 0.6, indicating that the wavelength capacity tends to saturation. Fig. 2 demonstrates that the more the number of wavelengths, the lower the utilization of upstream bandwidth under the same load. The reason is that the total bandwidth is larger when the number of wavelengths is remarkable, thus the idle time becomes longer at each wavelength. It can be seen that the greater the number of wavelengths, the larger the capacity of the system to carry the traffic. In order to obtain a higher utilization of upstream bandwidth and avoid wasting the resource overhead, the number of wavelengths should be chosen based on traffic situations. Fig. 3 displays the effect of different loads on the upstream network throughput when HAF-DWBA allocates resources at different wavelengths. Obviously, upstream network throughput increases with the increasing load. When the load is small, the upstream network throughput for different numbers of wavelengths doesn’t remarkably vary. However, with the increasing load, the network capacity for different numbers of wavelengths shows a great difference. It is mainly attributed to smaller numbers of wavelengths, which are easy to reach the maximum traffic capacity.
(5)→ BAfix ; 8: recycle the remaining bandwidth Bk ← Bk ; 9: allocate bandwidth to T-CONT-2, T-CONT-3, and T-CONT-5 of all ONUs according to Eqs. (6) and (7) →BAassure ; 10: recycle the remaining bandwidth Bk ← Bk ; 11: allocate bandwidth to T-CONT-3, and T-CONT-5 of all H-ONUs according to Eq. (8) → BAna ; 12: recycle the remaining bandwidth Bk ← Bk ; 13: allocate bandwidth to T-CONT-4, and T-CONT-5 of all H-ONUs according to Eq. (9) → BAbe ; 14: recycle the remaining bandwidth Bk ← Bk ; 15: if Bk > 0 then 16: go to line 11 to allocate bandwidth for L-ONUs whose bandwidth cannot be 17: 18: 19: 20: 21:
satisfied→ BAna and BAbe ; else calculate Uti4 , Tt _ave ; end if end if Output Uti4 , Tt _ave ;
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Fig. 3. Upstream network throughput for different numbers of wavelengths. Fig. 6. Utilization of different types of bandwidth.
Fig. 4. Bandwidth utilization for different algorithms.
Fig. 7. Throughput of different types of bandwidth. Table 2 Parameters of each traffic source. Traffic Type
Packets size (Byte )
Average packet interval (ms )
Average speed (Mbps )
T-CONT-1 T-CONT-2
Fixed value = 500 Uniform Distribution (128-3000) Uniform Distribution (64-1500) Three-state model Three-state model
0.125 0.25
32 50.2
0.115
108.35
0.16 0.16
45.4 45.4
T-CONT-3
T-CONT-4 T-CONT-5
the proposed algorithm takes into account simultaneous transmissions at several wavelengths and the remaining bandwidth can be fully utilized for distribution, resulting in a relatively ideal effect. End-to-end delay is an important performance indicator for TWDMPON system as well. Fig. 5 compares the end-to-end delay versus ONU load for HF-DWBA, UBA-DRAS, and LP-DWBA algorithms. It can be seen that end-to-end delay increases with the increasing load. Before the normalized load reaches 0.6, the delay of the network is still in a relatively stable state. However, as ONU load sequentially increases, the
Fig. 5. Average packet delay for different algorithms.
Fig. 4 shows the utilization of bandwidth for HF-DWBA, UBA-DRAS, and LP-DWBA algorithms under four different wavelengths. It can be seen that utilization of upstream bandwidth of the three algorithms enhances with the increase of the load. Fig. 5 illustrates that the proposed HF-DWBA algorithm slightly operates better than UBA-DRAS and LP-DWBA methods in terms of bandwidth utilization. The reason is that 170
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Fig. 8. Average delay of T-CONTs.
corresponding delay is longer as well.
delay dramatically becomes worse. Because bandwidth requests from ONUs basically exceed the minimum guaranteed bandwidth, the network packets have to wait to be processed by OLT, causing a queuing delay. Besides, the queuing delay is larger than that of the propagation delay and processing delay of the packets, thus, the average packet delay drastically increases. Comparing with UBA-DRAS and LP-DWBA methods, the delay of HF-DWBA algorithm has been slightly improved. The proposed HF-DWBA algorithm can effectively decrease the network delay and satisfy the requirement of QoS, while maintaining a high resource utilization. Aiming at the different types of traffic corresponding to the four kinds of bandwidth, Fig. 6 displays various kinds of bandwidth utilization ratio for diverse loads. As depicted in Fig. 6, the guaranteed bandwidth utilization ratio is higher than the other three types of bandwidth utilization ratio. Additionally, when the load is higher than 0.5 Erlang, guaranteed bandwidth utilization ratio varies within a certain range. It is because guaranteed bandwidth ensures the basic bandwidth required by ONUs, leading to a fair distribution of ONUs, and maintains QoS. When ONU’s load exceeds 0.6 Erlang, both utilization ratios of non-guaranteed bandwidth and best-effort bandwidth decrease. This can be justified as most of ONUs cannot achieve enough bandwidth when the network load is large. Fixed bandwidth and guaranteed bandwidth have priority in bandwidth allocation within ONUs and thus the traffic of non-guarantee and best-effort bandwidths are attenuated. This algorithm reflects fairness and flexibility of bandwidth allocation. Fig. 7 shows various types of bandwidth throughput under a variety of loads. In order to perfectly meet the bandwidth requirements for each ONU, we can observe that the throughput of guaranteed bandwidth is relatively high, while the throughput of besteffort bandwidth is relatively small. In TWDM-PON, the total rate of transmission for each wavelength is 2.25 Gbps. The delay of each T-CONT is assessed within the ONUs. Each ONU contains T-CONT-1, 2, 3, 4, 5, and the average total rate of TCONT’s traffic source is 281.25 Mbps. The parameters of traffic source are shown in Table 2. Fig. 8 illustrates the average delay for various T-CONTs versus ONU load. The results of simulation show that the average delay for T-CONT1 is about 0.225 ms , which is less than a standard value (1.5 ms) recommended by the G.982 agreement of ITU-T. The average delay of TCONT-3 is less than that of T-CONT-1 because of its high average transmission rate. T-CONT-4 mainly allocates the best-effort bandwidth. Once the load increases, the best-effort bandwidth cannot be properly satisfied and gradually decreases, and the delay accordingly reduces as well. For T-CONT-2, with the increasing load, the delay increases. The reason is that the larger the traffic, the longer the queue delay. For T-CONT-5, since it contributes in every step of bandwidth allocation, the bandwidth is synthetically obtained by all steps, the
6. Conclusions In this paper, HF-DWBA algorithm was proposed based on in-depth analysis of system architecture, as well as dynamic bandwidth allocation mechanism in TWDM-PON system. According to different grades of ONUs, the proposed algorithm is optimized in wavelength selection and bandwidth allocation based on XG-PON system. The algorithm can achieve upstream bandwidth allocation including five types of T-CONTs and four bandwidth allocation modes. Combined with different SLAs, the priorities of ONUs are fully taken into account to meet the requirements of different bandwidths. Therefore, the proposed algorithm can support diverse types of traffic, as well as achieving multi-traffic broadband access. The simulation results show that HF-DWBA algorithm possesses an appropriate performance on bandwidth utilization ratio and traffic delay. Furthermore, the algorithm also ensures the fairness of resource allocation. In future researches, we will study a coupled relationship between wavelength assignment and bandwidth allocation by exploration of some favorable characteristics in wavelength assignment and bandwidth allocation processes, which can be used to promote the 2D scheduling of TWDM-PON system. Acknowledgements This work is supported by the National Natural Science Foundation of China (61501308), Science and technology research project of Liaoning Provincial Department of Education (LG2016/6), Postdoctoral Research Station project of Shenyang Ligong University (2016), Special Foundation of Doctoral Program of Shenyang Ligong University (2015), Key Laboratory Open Foundation of Shenyang Ligong University (2014, 2017), Liaoning Fourth Batch of Distinguished Professor Project (2014), Liaoning BaiQianWan Talents Program (2016), Liaoning Natural Science Foundation (20170540793), Distinguished Professor Project in Liaoning Province (2017), Program for Liaoning Innovative Research Team in University (2017). References [1] X. Gong, L. Guo, Y. Liu, Y. Zhou, H. Li, Optimization mechanisms in multi-dimensional and flexible PONs: challenging issues and possible solutions, Opt. Switching Networking 18 (Part1) (2015) 120–134. [2] X. Gong, W. Hou, L. Guo, L. Zhang, Dynamic energy-saving algorithm in green hybrid wireless-optical broadband access network, Optik 124 (14) (2013) 1874–1881. [3] I.S. Hwang, A. Rianto, A.F. Pakpahan, Software-defined Peer-to-Peer file sharing architecture for TWDM PON[C], Proc. of Wireless and Optical Communication Conference, 2018, pp. 1–4.
171
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L. Zhang et al.
[17] Y. Xiong, J.B. Tang, H. Zhang, et al., User-behavior aware dynamic resource allocation strategy in TWDM-PON, Acta Electron. Sin. (2016). [18] A. Dixit, B. Lannoo, D. Colle, et al., Dynamic bandwidth allocation with optimal wavelength switching in TWDM-PONs, Proc. of International Conference on Transparent Optical Networks, 2013, pp. 1–4. [19] G. Das, B. Lannoo, H.D. Jung, et al., A new architecture and MAC protocol for fully flexible hybrid WDM/TDM PON, Proc of European Conference on Optical Communication, 2009, pp. 1–2. [20] M. Radivojević, P. Matavulj, Novel wavelength and bandwidth allocation algorithms for WDM EPON with QoS support, Photon Netw. Commun. 20 (2) (2010) 173–182. [21] M. Radivojević, P. Matavulj, Advanced scheduling algorithm for quality of service support in WDM EPON, Opt. Express 19 (26) (2011) 587–593. [22] Mirjana R. Radivojević, P.S. Matavulj, Highly flexible and efficient model for QoS provisioning in WDM EPON, IEEE/OSA J. Opt. Commun. Network. 5 (8) (2013) 921–931. [23] M.S. Han, Performance evaluation of dynamic bandwidth allocation algorithm for TWDM PON, J. Convergence Inform. Technol. (2013). [24] Z. Zhang, H.U. Xintian, X. Chen, dynamic resource scheduling in ring-tree TWDMPON, ZTE Technol. J. 20 (5) (2014) 29–33. [25] N. Cheng, J. Gao, C. Xu, et al., Flexible TWDM PON system with pluggable optical transceiver modules, Opt. Express 22 (2) (2014) 2078. [26] M. Bi, S. Xiao, L. Yi, et al., Power budget improvement of symmetric 40-Gb/s DMLbased TWDM-PON system, Opt. Express 22 (6) (2014) 6925–6933. [27] X.S. Wang, Y.U. Shao-Hua, J.Y. Dai, Novel algorithm for dynamic bandwidth scheduling in WDM EPON, J. Commun. 33 (2) (2012) 69–75. [28] R. Gu, Y. Ji, P. Wei, et al., Software defined flexible and efficient passive optical networks for intra-datacenter communications, Opt. Switch. Network. 14 (3) (2014) 289–302. [29] R. Gu, S. Zhang, Y. Ji, et al., Efficient software-defined passive optical network with network coding, Photon Netw. Commun. 31 (2) (2016) 239–250. [30] K. Kondepu, A. Sgambelluri, L. Valcarenghi, et al., An SDN-based integration of green TWDM-PONs and metro networks preserving end-to-end delay, Proc. of Optical Fiber Communications Conference & Exhibition, IEEE, 2015. [31] J. Zhang, N. Ansari, Scheduling hybrid WDM/TDM passive optical networks with nonzero laser tuning time, IEEE/ACM Trans. Network. 19 (4) (2011) 1014–1027. [32] F. Rawshan, Y. Park, Fault-tolerable and SLA-supportive architecture for TWDMPON systems, Photon Network Commun. 30 (2) (2015) 143–149.
[4] T. Kawanaka, T. Ashida, S. Yoshima, et al., Experimenta investigation into burstmode wavelength drift of a mass-produced 10 Gbit/s EML for TWDM-PON[C], Proc. of European Conference on Optical Communication, (2018). [5] L. Xue, L. Yi, H. Ji, et al., Symmetric 100-Gb/s TWDM-PON based on 10G-class optical devices enabled by dispersion-supported equalization, J. Lightwave Technol. (2018) 99 1-1. [6] X. Wang, L. Wang, C. Cavdar, et al., Handover reduction in virtualized cloud radio access networks using TWDM-PON fronthaul, IEEE/OSA J. Opt. Commun. Network. 8 (12) (2017) B124–B134. [7] P. Iannone, A. Gnauck, M. Straub, et al., An 8 x 10-Gb/s, 42-km, high-split TWDM PON featuring distributed Raman amplification and a remotely powered intelligent splitter, J. Lightwave Technol. 99 (2017) 1-1. [8] A. Dixit, B. Lannoo, D. Colle, et al., Wavelength switched hybrid TDMA/WDM (TWDM) PON: a flexible next-generation optical access solution, Proc. of ICTON, 2012, pp. 1–5. [9] Y. Luo, M. Sui, F. Effenberger, Wavelength management in time and wavelength division multiplexed passive optical networks (TWDM-PONs), Proc. of Global Communications Conference, 2012, pp. 2971–2976. [10] A.L. Teixeira, J.D. Reis, A. Shahpari, et al., Spectral Management in Flexible Multiwavelength PONs, 2013, pp. 1–3. [11] Y. Luo, X. Yan, F. Effenberger, Next generation passive optical network offering 40Gb/s or more bandwidth, Proc. of Communications and Photonics Conference, 2012, pp. 1–3. [12] F. Gao, X.Q. Chen, S.W. Zhao, Dynamic bandwidth allocation algorithm with high bandwidth utilization for 1OG EPON system, Opt. Commun. Technol. 40 (6) (2016) 25–27. [13] Constantine A. Kyriakopoulos, Georgios I. Papadimitriou, Predicting and allocating bandwidth in the optical access architecture XG-PON, Opt. Switch. Network. (2017) 91–99. [14] M.S. Han, Performance evaluation of dynamic bandwidth allocation algorithm for XG-PON using traffic monitoring and intra-scheduling, Int. J. Software Eng. Appl. 9 (8) (2015) 207–216. [15] J.Y. Lee, I. Hwang, A.A. Nikoukar, et al., Comprehensive performance assessment of bipartition upstream bandwidth assignment schemes in GPON, IEEE/OSA J. Opt. Commun. Network. 5 (11) (2013) 1285–1295. [16] H. Wang, Y. Liang, R. Gu, et al., LP-DWBA: a DWBA algorithm based on linear prediction in TWDM-PON[C], Proc. of International Conference on Optical Communications and Networks, 2015, pp. 1–3.
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