QoS-aware dynamic MAP selection schemes in HMIPv6 networks

J. Parallel Distrib. Comput. 72 (2012) 838–855

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J. Parallel Distrib. Comput. journal homepage: www.elsevier.com/locate/jpdc

QoS-aware dynamic MAP selection schemes in HMIPv6 networks WonSik Chung a , Mun-Suk Kim a , JeongHoon Mo b , SuKyoung Lee a,∗ a

Department of Computer Science, Yonsei University, Seoul, Republic of Korea

b

Department of Information and Industrial Engineering, Yonsei University, Seoul, Republic of Korea

article

info

Article history: Received 6 March 2011 Received in revised form 15 February 2012 Accepted 22 March 2012 Available online 11 April 2012 Keywords: HMIPv6 Dynamic MAP selection Mobility Load distribution Signaling cost Inter-domain handover Delay-sensitive session Handover delay

abstract We consider a dynamic Mobile Anchor Point (MAP) selection problem when there are both real-time and non-real time sessions in a Hierarchical Mobile IPv6 (HMIPv6) network. We propose schemes in which Mobile Nodes (MNs) holding real-time sessions register with the root MAP in a hierarchy of MAPs to reduce the inter-domain handovers while those with non-real time sessions select one either to balance the load or to reduce handover frequencies. Both the simulation and analytical results show the effectiveness of the proposed schemes with respect to the number of inter-domain handovers, to the average signaling cost, and to the load distribution. In addition, we could also confirm that our MAP selection schemes provide better QoS to the MNs holding real-time sessions, in that they reduce the inter-domain handovers for those MNs and the average handover delay, resulting in a shorter service disruption. © 2012 Elsevier Inc. All rights reserved.

1. Introduction Integrating several access technologies, such as 3G, Wireless Local Area Network (WLAN), and Worldwide Interoperability for Microwave Access (WiMAX) networks, has recently gained considerable attention in the study of wireless mobile communication systems. ‘‘Vertical handover’’, which is a handover technique to provide seamless mobility support between different network systems, is one of the most challenging problems for the system integration of wireless technologies. Thus, various network architecture and technologies have been developed to handle the vertical handover. Among these proposed architectures, Mobile IPv6 (MIPv6) [8] has emerged as the dominant protocol for supporting vertical handover because it is a mature protocol with several implementations including those [6] that have been through interoperability testing. In MIPv6, each Mobile Node (MN) can maintain on-gong connections between itself and Correspondents Nodes (CNs) by sending Binding Updates (BUs) to its Home Agent (HA) and all CNs it communicates with, every time it moves. Hence, the MN can be reached by its Care of Address (CoA) that provides information

∗

Corresponding author. E-mail address: [email protected] (S. Lee).

0743-7315/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.jpdc.2012.03.008

about the MN’s current location. Data packets destined to the MN are routed to its CoA. In addition, the CN can directly send data packets to the MN using the MN’s CoA. Although MIPv6 enables MNs to freely roam across various subnets regardless of the access technologies, it may incur a high signaling overhead, as well as long handover latency when the handover is too frequent. There have been several protocols proposed to overcome this drawback [20,3,19,13,9]. In [20], the Hierarchical MIPv6 (HMIPv6) has recently been proposed as a micro mobility protocol which employs a Mobility Anchor Point (MAP) to handle Binding Update (BU) for MNs within the MAP domain. Hence, network-wide signaling is only required when the MN roams outside of its current MAP domain, leading to reduction in the registration signaling cost as well as long handover latency. Such hierarchical mobility management has been widely adopted in other mobility management protocols such as Cellular IP [3] and HAWAII [19]. The performance of the HMIPv6 applied network is, however, critically affected by the selection of MAPs and their load status when there are multiple MAPs in the network. That is, even though HMIPv6 is employed in the network, long handover latency still occurs especially when the MNs move across the MAPadministrated domains due to their high velocity. In addition, the frequent inter-domain handovers can cause an excessive signaling cost resulting in a lower utilization of the network. Further, the load concentration on a certain MAP can prevent the MNs from taking advantage of the benefit from HMIPv6 in

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spite of the fact that other MAPs in the network are available. Therefore, it is important to select a MAP that will reduce the interdomain handovers and distribute the load over multiple MAPs. As a solution to the above problems, our previous studies [4,5] proposed two dynamic MAP selection schemes to mitigate load concentration on the MAPs and to reduce the frequency of interdomain handovers. The schemes proposed in our previous work, however, do not consider the characteristics of ongoing sessions to select the appropriate MAP. It is noteworthy that the inter-domain handover is more detrimental to MNs which have delay-sensitive sessions than those with delay-tolerant sessions. Therefore, in this paper, we are motivated to design a MAP selection scheme that puts a higher priority on the MNs with delay-sensitive sessions. Specifically, we propose MN carrying delay-sensitive sessions to be registered with the furthest MAP which is located at the top level in a hierarchy of MAPs in order to provide a wider MAP domain, while the MAP is selected based on our previous work for MNs holding only delay-tolerant sessions. As a result, we can provide delaysensitive traffic sessions with reduced handover delay, leading to reduction in the service disruption time. We evaluate the performance of our proposed schemes by comparing them with other existing schemes including one based on the Internet Engineering Task Force (IETF) HMIPv6 as well as the static MAP selection scheme in which the velocity range is fixed at each MAP. Another contribution in this paper is that we have developed analytical models of the system blocking probability and the average inter-domain handover signaling cost for the two schemes proposed to distribute load and reduce interdomain handovers. In addition, we compare the performance of the proposed schemes for delay-sensitive sessions with our previous work in terms of handover delay. The simulation and numerical results show that the proposed dynamic MAP selection schemes can significantly reduce the inter-domain handovers, the system blocking probability, and the average signaling cost as well as distribute the load more evenly over multiple MAPs compared to other existing schemes. Moreover, through simulations, we could also verify that not only the inter-domain handovers, but the average handover delay can be significantly reduced for the delay-sensitive sessions. The paper is organized as follows: we first discuss related work on MAP selection schemes in Section 2. The details of our proposed MAP selection schemes are presented in Section 3. In Section 4, we analyze the system blocking probability and the inter-domain handover signaling cost of the proposed schemes for distributing load and reducing inter-domain handovers, followed by the numerical results. The performance of our proposed schemes is demonstrated through simulations in Section 5. Section 6 provides our conclusions.

multi-level hierarchy [11,12,15,17]. In [11,15], the authors propose a MAP selection scheme based on the estimated MN’s velocity. However, the velocity range is fixed for each MAP and hence a MAP cannot be dynamically selected according to the network status. Further, they do not address how to resolve the overload problem when many MNs have similar speeds, leading to choosing one same MAP. The authors of [17] propose the load control scheme in the HMIPv6 network, that forces an MN with high ratio of session arrival rate to handover rate, to directly register with its HA. The scheme aims to control the number of MNs serviced by the MAP to mitigate the burden of the MAP. Considering the MN’s velocity and the load status of each MAP, our previous works [4,5] proposed two dynamic MAP selection schemes, Load and Distance (LV)-MAP and Distance and Velocity (DV)-MAP. The LV-MAP distributes the load over multiple MAPs and dynamically updates the MAP’s velocity range according to the velocity of MNs currently serviced by the MAP, with the aim to reduce the number of inter-domain handovers. In the latter scheme, the furthest MAP is selected to avoid frequent inter-domain handovers, while the slowest MN is reassociated with the MAP at the next furthest level instead of being blocked, if the furthest MAP is overloaded. Thus, the number of inter-domain handovers is reduced while sustaining a lower HMIP system blocking probability compared to the former scheme. Meanwhile, these schemes lack consideration of the characteristics of ongoing sessions although service disruptions due to interdomain handovers will be more detrimental to delay-sensitive sessions than delay-tolerant sessions. Therefore, in this paper, we propose a MAP selection scheme to support MNs holding delaysensitive sessions with higher priority in registering with the furthest MAP.

2. Related work

3. Dynamic MAP selection

Several MAP selection schemes have been proposed to solve the long handover latency and concentration of load in the literature. IETF HMIPv6 [20] suggests a distance-based MAP selection algorithm as a starting point of other MAP selection schemes. In this scheme, an MN has a knowledge of hop distance between the MN and the MAP from the DISTANCE field in the Router Advertisement (RA) message. Using this information, the MN registers with the furthest MAP since the area covered by the further MAP is usually larger than that of the MAP closer to the MN. In this way, the MN will avoid frequent inter-domain handovers. However, if a large number of MNs in the network select the furthest MAP, the selected MAP will be overloaded. To mitigate the overload problem, the multi-level hierarchical structure of MAPs is investigated in [16,18] and some efforts have been made towards selecting an appropriate MAP in the

Our system is based on HMIPv6 with a multi-level hierarchy of MAPs and Fast Handovers for MIPv6 (FMIPv6) [13]. The multi-level hierarchical structure is adopted because of the scalability and to minimize handover signaling costs instead of the flat architecture. Fig. 1 shows an example of the structure with seven MAPs and four Access Routers (ARs). We assume a binary tree in this manuscript for the sake of simplicity. However, a generalization into m-ary tree can be done as needed. Let mk denote a MAP in the tree. Without loss of generality, we assume that the height of the tree is n: a root node is at level one and a leaf node is at level n. The MAP mk supports MNs with velocity ranges of [v k , v¯ k ], where v k and v¯ k are the lowest and the highest velocities of MNs associated to MAP mk , respectively. The MAPs in a higher level deal with fast moving MNs, while those at lower levels deal with slow moving MNs. We summarize the notations in Table 1 for reference.

Fig. 1. An example multi-level hierarchical structure of MAPs.

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Fig. 2. Usage example of the proposed MAP selection schemes. Table 1 Summary of notations.

3.2. Dynamic MAP selection algorithms for delay-sensitive traffic

Symbol

Meaning

k u mk

Indices for MAP Index for entering Mobile Node (MN) Mobile Anchor Point (MAP) i or k Lowest and highest velocity of MAP mk Load and maximum load of MAP mk

v k , v¯ k ρk , ρ¯ k

3.1. Dynamic MAP selection algorithms: LV-MAP and DV-MAP We explain the main ideas of LV-MAP and DV-MAP algorithms which were already presented in [5], for completeness of the paper. LV-MAP: The key idea of LV-MAP is to select a MAP with a velocity closer to the speed of the MN so that the number of inter-domain handovers can be limited. Let vu denote the velocity for MN u. When MN u enters a HMIPv6 network, a corresponding AR selects a MAP, mk∗ from a set of associated MAPs as follows: k∗ = arg min dist(u, mk ),

(1)

k

where dist(u, mk ) =

0,

if v k ≤ vu ≤ v¯ k ;

min{|v k − vu |, |¯vk − vu |},

otherwise.



(2)

When there is no MAP mk that has zero distance, the corresponding AR selects a MAP with a velocity range closer to vu . The algorithm also considers the load of the selected MAP and performs corrective action when the load of the selected MAP is too high. Refer to [5] for the details of the corrective action. DV-MAP: DV-MAP considers the geographical distance which is not considered in the LV-MAP. 1. First, the MN u registers with the furthest MAP, say m1 as long as m1 is not overloaded. Here, if vu ≤ v 1 , then v 1 is set to vu . 2. If the furthest MAP m1 is overloaded, either MN u or the slowest MN among those associated with m1 tries to register with a child MAP mc of m1 . At the moment, v 1 is updated to the new minimum velocity among the MNs currently associated with the root MAP. This re-association process is repeated downward through the MAP tree until a non-overloaded MAP is met. 3. If any available MAP is not found until the lowest level (i.e., n) is reached, the MN with v k , which has been associated with the leaf MAP (let’s say mk ), has to register with its HA directly as in normal MIPv6.

Both the LV-MAP and DV-MAP schemes described in Section 3.1, do not consider QoS requirements of the ongoing sessions. As the Internet expands its supported traffic from best effort data to a variety of multimedia services, including video conferencing, Voice over IP (VoIP), streaming audio and video, WWW, e-mail, and file transfer, etc., QoS provisioning has become an important issue. The commonly accepted QoS metrics mainly include delay, delay jitter, and packet loss rate. As shown in Table 2, four different classes of QoS have been defined by 3GPP (3rd Generation Partnership Project): conversational, streaming, interactive, and background traffic classes [10,1]. In the table, we note that conversational traffic has more stringent requirements in delay than other traffics. We also note that in the HMIPv6 system, the primary source of delay is inter-domain handover and hence, frequent inter-domain handovers degrade the delay performance of conversational traffic. Based on these notions, we propose to assign a higher priority to the conversational traffic than other traffic classes in registering with the furthest MAP, with the aim to reduce the frequency of inter-domain handovers for the conversational traffic. We still apply a LV-MAP or DV-MAP scheme to the non-conversational traffics, as shown in Fig. 2. Even if the load of conversational traffic is high in the HMIPv6 system, the nonconversational sessions’ mobility is still supported by MIPv6. We extend the LV-MAP and DV-MAP schemes to provide QoS for delay-sensitive traffic by having the sessions of conversational class registered with the furthest MAP. We call these MAP selection schemes, LV-MAP with QoS support (LVQ) and DV-MAP with QoS support (DVQ) in the rest of our study. On the other hand, the LVMAP and DV-MAP schemes are still applied for other traffic classes. When an MN u arrives at a HMIPv6 network, the following operations are performed under LVQ scheme: 1. If the MN u does not have a session of conversational class, the LV-MAP scheme is applied. 2. If the MN u has an ongoing session of conversational class, it registers with the furthest MAP (i.e., root MAP). At the moment, if the root MAP is overloaded, the MN whose velocity is lowest among the MNs having non-conversational sessions at the root MAP (let’s say x), should be re-associated with a MAP in the next level, mc . If the MN x’s velocity, vx does not belong to mc ’s velocity range, either v c or v c is updated with vx . 3. In the above step, if all the MNs registered with the root MAP hold the conversational sessions, the MN u registers with the MAP in the next level, mc . In the case that mc is also overloaded and there are MNs with non-conversational sessions at mc , the above step is repeated. That is, the same step is repeated down the MAP tree until a non-overloaded MAP is met.

Table 2 Traffic classes and their characteristics. Traffic class

Fundamental characteristics

Service examples

Conversational Streaming Interactive Background

Low delay, small delay variation Moderate delay and variation Round trip delay is a matter of importance, moderate delay variation, request–response pattern Destination does not expect a response within a certain time

Speech, VoIP, video conferencing Streaming video, streaming audio Web-browsing Email and file downloading

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Fig. 3. An example scenario of LV-MAP and LVQ schemes.

4. If any non-overloaded MAP is not found until the lowest level (i.e., n) is reached, then the MN with v k which has been associated with the leaf MAP (let’s say mk ), has to register with its HA directly as in the normal MIPv6 unless all the MNs in the MAP tree belong to the conversational class. Otherwise, if all the MNs have conversational sessions, then the MN u directly registers with its HA. Through the above procedure, LVQ is able to decrease the number of inter-domain handovers for delay-sensitive sessions. Likewise, the DVQ scheme also allows for the conversational sessions to be registered with the furthest MAP regardless of the MN’s velocity. That is, when an MN enters the HMIPv6 system, if the MN has a non-conversational session, DV-MAP is applied. Otherwise, the same procedure described above for LVQ is performed under the DV-MAP scheme. Thus, the DV-MAP and LV-MAP can be selectively used depending on the load status of the overall HMIPv6 system. The desired actions for different ranges of load and the ratio of conversational sessions to all the sessions are exemplified in Fig. 2. DVQ is desirable whenever the ratio of conversational sessions is very low at low loads. However, even at low loads, if the ratio of conversational sessions is very high, LVQ is more suitable since DVQ will let non-conversational sessions arrive at the system earlier than conversational sessions, and be attached with the furthest MAP. On the other hand, at high loads, LVQ is capable of operating in a more efficient way in that the conversational sessions can get into further MAPs more easily than DVQ. 3.3. Example usage scenarios of the proposed MAP selection algorithms In this section, we explain how our proposed schemes: LVMAP, DV-MAP, LVQ, and DVQ schemes operate by presenting some example scenarios. For the purpose of comparison, we introduce two more MAP selection schemes: one is a static MAP selection scheme and the other is based on [20], that we will call Distancebased MAP (DMAP) hereafter. In the static scheme, the MAP’s velocity range is static as in [11,15]. In the DMAP, MN always attempts to register with the MAP at the highest level to avoid frequent inter-domain handovers. In the case that the highest MAP is overloaded, the MN probes the MAP at the next highest level without checking whether or not there is any MN which can be reassociated with the next highest level among the MNs serviced by the root MAP. This probing process is repeated down the MAP tree

until a non-overloaded MAP is met, so that the re-association of DV-MAP never takes place in the DMAP. When all the MAPs in the domain are found to be overloaded, the normal MIPv6 procedure is performed. Fig. 3 shows an example to depict how a MAP is selected in the proposed LV-MAP and LVQ schemes. We consider two MNs, MN1 and MN2 , traveling at the speeds of 45 and 35 km/h, respectively. In this scenario, we assume that the maximum number of sessions from the MNs (i.e., load entry in the MAP cache) that can be served by a MAP is ten. Under LV-MAP, when MN1 first arrives at AR1 , AR1 will find a MAP whose velocity range is the most approximate to the MN’s speed (i.e., 45 km/h) since, as can be seen in Fig. 3, the MN’s speed belongs to none of the MAPs’ current velocity ranges. Accordingly, MAP2 is selected and then MN1 registers with the selected MAP since the selected MAP is not yet overloaded. The velocity range of MAP2 is then updated with the speed of MN1 , so that the velocity range of MAP2 changes from 23–38 to 23–45. When the next MN, MN2 arrives, it is not allowed to register with MAP2 although MAP2 is selected by the LV-MAP scheme since MAP2 is now overloaded as the load status of MAP2 indicated in Fig. 3. Thus, the least overloaded MAP is selected between MAP2 ’s neighboring MAPs (i.e., MAP4 ) and the MN with the lowest speed (i.e., 23 km/h) among the MNs served by MAP2 is re-associated with MAP4 . Subsequently, MN2 can register with MAP2 in place of MN3 . Supposing that the lowest speed of the MNs served by MAP2 is 28 km/h after MN3 has gone, the velocity range for MAP2 is updated with 28–45 in the MAP cache. For the LVQ scheme, we assume that MN1 , MN2 , and MN3 belong to conversational, background, and streaming traffic classes, respectively, in this scenario. When MN1 arrives at AR1 , it registers with MAP1 even though the velocity range of MAP1 does not include the velocity of MN1 . This is because MN1 belongs to conversational traffic class and the MN with conversational sessions can register with the highest MAP unless the highest MAP is already full of other conversational sessions. Note that the range of velocity for MAP1 in the MAP cache of AR1 is not updated even though MN1 registers with MAP1 since it belongs to conversational traffic class. When the next MN, MN2 , arrives at AR1 , an appropriate MAP, MAP2 in this example, is selected based on the velocity of MN2 , as in the LV-MAP scheme. However, since MAP2 is overloaded, MN3 with no conversational session should be re-associated with the least overloaded MAP, MAP4 for MN2 . Fig. 4 depicts how DMAP, DV-MAP, and DVQ schemes work in the same example scenario as shown in Fig. 3. In the DMAP scheme,

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Fig. 4. An example scenario of DMAP, DV-MAP, and DVQ schemes.

MN1 attempts to register with the highest MAP (i.e., MAP1 ). MAP1 is already overloaded, hence the MN has to register with MAP2 . Likewise, the next MN, MN2 registers with MAP2 . However, in DVMAP, both MN1 and MN2 register with MAP1 by re-associating the MNs having lower speeds of 12 and 15 km/h, with MAP2 . We now assume that the MN with a speed of 12 km/h at MAP1 , belongs to conversational traffic class. In the DVQ scheme, the same as the LVQ scheme, when MN1 with a speed of 45 km/h, arrives at AR1 , it registers with MAP1 , while the slowest MN (15 km/h in this scenario) among the MNs with non-conversational sessions, re-associates with MAP2 . On the other hand, MN2 with a speed of 35 km/h, is not allowed to make one of the MNs with nonconversational sessions at MAP1 re-associate with a MAP in the next level in order to associate itself with MAP1 since it has a session of background traffic class. Thus, MN2 probes the next available MAP, resulting in registration with MAP2 . 3.4. Inter-domain handover process By forming a HMIPv6 network, the signaling overhead for registration can be reduced while FMIPv6 is known to minimize handover latency [13]. Based on the specific advantages of each of the two protocols, a combination of the two protocols is at times encouraged. Hence, our proposed schemes perform mobility management based on the extension of the basic hybrid scheme of HMIPv6 and FMIPv6 [9]. For LV-MAP, the detailed signaling procedure for inter-domain handover is illustrated in Fig. 5. The inter-domain process works in the same way as F-HMIPv6 does [9], except that the new MAP (nMAP) should update the MAP cache maintained in its associated ARs by sending the MAP options defined in [20]. A MAP utilizes a 7-bit reserved field and a 4-bit preference field, respectively, to disseminate its updated velocity range and load status. [0, ρ¯ k ] is divided into 15 ranges due to the length of the preference field while 0 in the preference field indicates that the MAP is 14ρ¯ overloaded. For instance, the last range [ 15 k , ρ¯ k ) is mapped to 1 in the preference field. Whenever ρk exceeds the maximum value of the current range, a MAP decreases the preference value by one in its MAP option. In case that the load status is divided into more than 16 ranges for more robust granularity, the reserved field in the Router Advertisement (RA) message can be utilized to advertise the load status of the MAP to the AR. In addition, we propose to update the Router Solicitation (RS) message to enable MNs to indicate their

Fig. 5. Inter-domain handover process for LV-MAP (also applied to nonconversational sessions under LVQ).

Fig. 6. The message format of modified Router Solicitation.

velocities and whether they have a conversational session or not. In the modified RS message, ‘Q’ flag is set when the MN has ongoing conversational sessions. A 7-bit reserved field is utilized to report the MN’s velocity. The modified RS message is depicted in Fig. 6. When an MN moves out of the current domain, the old MAP (oMAP) does not need to update its load status and velocity range since the corresponding ARs update their cache entry for the MAP

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4.1. System blocking probability

Fig. 7. Signaling for re-association between MN and MAP.

when the MN selects a different MAP or the cache entry is expired as a form of soft state de-registration. When the selected MAP is found to be overloaded, an MN currently serviced by the MAP may be re-associated with one of the neighboring MAPs, as explained in Section 3.1. The signaling procedure for the re-association is described as follows (see Fig. 7): 1. A new MN sends a Pre-Binding Update message to the selected MAP (i.e., nMAP1 in Fig. 7). 2. If the MN A currently serviced by nMAP1 is selected to be reassociated with the MAP at the next highest level (i.e., nMAP2 ), nMAP1 forms a temporary tunnel to nMAP2 and starts tunneling the packets destined for the MN A, to nMAP2 and sends a PreBinding Ack (Acknowledgment) to the new MN. 3. nMAP1 performs the registration with nMAP2 on behalf of MN A by sending a BU including MN A’s local Care-of-Address (LCoA) to nMAP2 , as in HMIPv6. 4. On the receipt of the BU from nMAP1 , nMAP2 obtains a Regional CoA (RCoA) and then sends a BU to the MN A’s HA to register the new RCoA. 5. The local binding maintained at nMAP1 for MN A is expired as a form of soft state de-registration. Even though the existing MN should be re-associated with the new MAP in order to allow for the network to accommodate more users, it is not unfair since the re-association operation does not affect the seamlessness of the re-associated MN. This is due to the fact that the binding for MN A is temporarily maintained at both nMAP1 and nMAP2 until the re-association process is completed. Fig. 8 shows the signaling procedures for DMAP and DVMAP when an inter-domain handover occurs. For LVQ and DVQ schemes, the inter-domain process is the same as those for LV-MAP and DV-MAP, respectively. In the static MAP selection scheme, the inter-domain handover process is the same as F-HMIPv6. When the HMIPv6 registration request is denied due to the overload condition in the MAP selected by the static scheme, the MN performs a normal MIPv6 registration. 4. Performance evaluation and numerical results To evaluate the performance of the proposed MAP selection schemes, we analyze the probabilities that a session is blocked by a MAP and HMIPv6 system for DV-MAP and LV-MAP, compared to DMAP and static MAP selection schemes. In both LVQ and DVQ, conversational sessions are never blocked except for the case that the entire HMIPv6 system becomes fully overloaded only by conversational sessions. Considering this exceptional case, we also analyze the system blocking probability in LVQ and DVQ. Then, on the basis of the session blocking probability at the MAP, we also investigate the signaling cost of these four schemes for interdomain handover. In our analysis, for simplicity, we suppose that we have MAPs organized as a binary tree structure with height n.

An increased blocking of sessions at a MAP will lead to disruption of ongoing sessions. Hence, it is important to reduce the system blocking probability in a HMIPv6 network, which is denoted by ps . We define the session blocking probability, p(i) , as the ratio of the number of sessions blocked to the number of sessions arriving at a MAP. We note that even if a session is blocked from a MAP, the session does not directly register with its HA/CN in the proposed schemes and DMAP, because the session can still register with another MAP in the HMIPv6 network. That is, a session cannot be serviced by the HMIPv6 system only if all the MAPs selected by the MAP selection scheme, block the session. To derive the steady-state system blocking probability, we will derive (i) the session blocking probability at each level i (denoted by ps ), which follows the session blocking probability at a MAP. For the analysis, we assume that new session arrivals to a MAP follow a Poisson process with rate, λ independent of other session-arrival processes. Since a session which is blocked by the selected MAP at the ith level will attempt to register with one of its neighboring MAPs, the arrival rate at the neighboring MAPs will be affected by such blocked sessions as well. Thus, we define λ(i) as the effective session arrival rate at a MAP in the ith level, including both new sessions to the MAP and blocked sessions from the neighboring MAPs. We assume that the session holding time is a random variable with an exponential distribution having a mean of 1/µ. Thus, we can model the MAP using a M /M /c /c queueing system where each state is the number of sessions the MAP is supporting. 4.1.1. System blocking probability in LV-MAP For simplicity, we set ρ¯ i = N for ∀i. To derive p(i) , we first consider only new session arrivals by initializing λ(i) with λ for ∀i. We then have p(i) =

aN N! N

 i =0

(3) ai i! (i)

where a = λµ . Assuming that the blocked session tries to register with its parent MAP or child MAP with equal probability, we have the effective session arrival rate to a MAP as follows: When n = 2, if the sessions that arrive at a MAP in the second level (i.e. λ(2) ), are blocked by the MAP (this blocking event occurs with the probability of p(2) ), they will attempt to register with its parent MAP. Noting that a root MAP has two child MAPs in the second level, the arrival rate of blocked sessions at the root MAP is 2λ(2) . On the other hand, the sessions blocked at the root MAP attempt to register with one of the two child MAPs. Thus, we have 2λp(2) 1 (1) λp 2

 λ

(i)

=λ+

for i = 1 (4)

for i = 2.

When n = 3, the sessions of λ(2) attempt to register with its parent or child MAP with equal probability. Thus, at the root MAP and the MAP in the third level, the arrival rates of sessions blocked by the (2) MAP in the second level, are 2 · λ 2 and we have

λ(i)

 (2) λp     1 (1) (3) = λ + 2 λp + 2λp  1   λp(2) 4

1 2

(2)

· λ 2 , respectively. Then,

for i = 1 for i = 2 for i = 3.

(5)

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P

Fig. 8. Inter-domain handover process for DMAP and DV-MAP (also applied for non-conversational sessions under DVQ).

Likewise, when n > 3, λ(i) is given by

λ(i)

λp(i+1)     1 (i−1)   λp + λp(i+1)   2    1 (i−1) + λp(i+1) = λ + 4 λp    1 (i−1)   + 2λp(i+1)   4 λp      1 (i−1) λp 4

for i = 1 for i = 2 for 2 < i < n − 1

(6)

for i = n − 1 for i = n.

Considering the blocked sessions from the neighboring MAPs, we can derive the effective session arrival rate to a MAP at each level by plugging the initial value of p(i) into Eqs. (4), (5), or (6) depending on the hierarchy of MAPs in the HMIPv6 network (i.e., n). Then, the new session blocking probability p(i) for each level is derived by using Eq. (3) and the effective session arrival rate can be obtained from Eqs. (4), (5), or (6). From the new value of p(i) , we can then have the newly computed effective session arrival rate. This process is repeated iteratively until p(i) converges to a certain value. We note that in LV-MAP, a blocked session attempts to register with one of its neighboring MAPs, depending on the load status of the neighboring MAPs. Then, we have

p(si) =

 (i) (i+1) p p    

 1 (i) (i+1) p p + p(i−1)

   2(i)

p p

(i−1)

(7)

for i = n.

Finally, we have the average system blocking probability, ps as follows: ps =

n  2i−1 (i) ps . n 2 −1 i=1

p(si) =

aN N! N

 j =0

(9) aj j! (i)

where a = λµ . For DV-MAP and DMAP schemes, a session is blocked from a HMIPv6 system if it is blocked from a MAP located at the lowest level. Thus, the average system blocking probability is given by ps =

n 

p(si) .

(10)

i=1

for i = 1 for 1 < i < n

4.1.2. System blocking probability in DV-MAP and D-MAP For both DV-MAP and DMAP, the session blocking probability has the same value since all sessions arriving at a HMIPv6 system, attempt to register with the root MAP and then try to register with a MAP at the next level whenever they are blocked from the currently selected MAP. Since all arriving sessions attempt to register with the MAP located at the highest level in both schemes, the effective session arrival rate at the root MAP is given by λ(1) = (2n − 1)λ. The sessions blocked from the root MAP tries to register with a MAP at the next highest level. Because the same process is repeated until the nth level, we can obtain the effective arrival rate to a MAP at the ith (i−1) . Then, by using M /M /c /c queueing level as λ(i) = 21 λ(i−1) ps system, we have

(8)

4.1.3. System blocking probability in LVQ and DVQ Let γ be the ratio of conversational sessions to the total session arrivals at a MAP. Then, in LVQ, the LV-MAP is applied for MNs having non-conversational sessions, which arrive at a MAP with rate (1 −γ )λ. On the other hand, all the MNs having conversational sessions, that arrive in the HMIPv6 system (i.e., (2n − 1)γ λ), attempt to register with the root MAP. Here, let’s say that n = 3. The conversational sessions are blocked by the root MAP will

W. Chung et al. / J. Parallel Distrib. Comput. 72 (2012) 838–855

attempt to register with one of the two child MAPs with the probability of p(1) . Thus, the arrival rate of blocked sessions at the child MAP in the second level is 21 (2n − 1)γ λp(1) . If the conversational sessions are blocked in the second level too, they will attempt to register with one of the two child MAPs in the third level, which gives 12 · 12 (2n − 1)γ λp(1) p(2) . Thus, we can express the conversational session arrival rate to a MAP in the ith level, λiQ as

λ(Qi) = (2n − 1)γ λ

i−1

1 j =1

2

q(i)

(11) (i)

where q(i) denotes p(i) in Eq. (3), and ps in Eq. (9) for LVQ and DVQ, respectively. As in the analysis of LV-MAP, DV-MAP, and DMAP, a converged value of p(i) is obtained by using the effective session arrival rate at a MAP and Eq. (3). For this, we derive the effective session arrival rate at a MAP in the ith level in LVQ. When n = 2, the effective session arrival rate at a MAP in the ith level is given by (i)

λ

 λ{2(1 − γ )p(2) + (2n − 1)γ }  = (1 − γ )λ + 1  λ (1 − γ )p(1) + λ(Q1)

ps =

n 2i−1 (1 − γ ) (i) (2n − 2)γ + 1 (1)  p + p . s n 2 −1 (2n − 1) s i=2

(16)

In DVQ, a conversational session arrives at a HMIPv6 system and the root MAP is overloaded, one of the non-conversational sessions at the root MAP should attempt to register with a MAP in the next level, as in DV-MAP, so that the conversational session could register with the root MAP. Thus, the average system blocking probability in DVQ can be obtained from Eqs. (9) to (10). We can derive the conversational session blocking probability, (i) pQ at a MAP in the ith level in both LVQ and DVQ as (i)

pQ =

aN N! N



(17) aj j! (i)

λ

for i = 2.

2

In LVQ, the arrival rate to the root MAP is (2n − 2)γ λ + λ among the total system arrival rate, (2n − 1)λ. We then obtain the average system blocking probability, ps in LVQ, as

j =0

for i = 1

845

(i)

where a = µQ and λQ = (2n − 1)γ λ

i−1

j =1

(i)

pQ .

(12) When n = 3, (i)

λ

= (1 − γ )λ  (2) n λ{( }  1 − γ )p  + (2 − 1)γ     1 (1) (3) + λ(Q2) + λ (1 − γ ) 2 p + 2p   1  λ{(1 − γ )p(2) } + λ(Q3)

for i = 1 for i = 2 (13)

for i = 3. 4 Likewise, when n > 3, we can obtain the effective arrival rate at a MAP in the ith level as

λ(i) = (1 − γ )λ λ{(1 − γ )p(i+1) + (2n − 1)γ }    1   for i =       1 (i−1)  (i+1)  p + p λ ( 1 − γ )   2        1 n  (i−1)  + (2 − 1)γ p    2      for i =  2  + 1 (i−1) (i+1)  λ (1 − γ ) p +p + λ(Qi)   4        for 2 <i < n − 1   1 (i−1)  (i+1)  λ ( 1 − γ ) p + 2p + λ(Qi)    4      for i = n − 1     1   (1 − γ )p(i−1) + λQ(i) λ   4 for i = n.

(14)

Using Eqs. (12)–(14), the session blocking probability in the ith level in LVQ, is given by

p(si) =

 n (1 − γ )p(i) p(i+1) (2n − 1)γ    + p(j)  n n − 2)γ + 1  ( 2 − 2 )γ + 1 ( 2   j =1    for i = 1  1

p(i) (p(i+1) + p(i−1) )   2    for 1 < i < n   (i) (i−1)   p p for i = n.

(15)

4.1.4. Numerical results of system blocking probability For the static scheme where the velocity range of a MAP is fixed, we assume that the velocity of the MNs are uniformly distributed to all the levels. In the static scheme, a session blocked from a MAP does not attempt to register with its neighboring MAPs. Instead, the blocked session directly registers with its HA/CN, as an MIPv6 registration process. Hence, the system blocking probability for the static scheme is the same as the probability obtained from Eq. (3). For numerical results, we consider a hierarchy of MAPs with three levels. We set γ and µ to 0.25 and 1/120, respectively. Fig. 9(a) shows the session blocking probability at each level versus the session arrival rate for LV-MAP, DV-MAP, LVQ, DVQ, and DMAP. For DMAP, DVQ, and DV-MAP, the session blocking probability at the lower level is much less than that at a higher level, because the MAP at the highest level is first selected for the three schemes. On the other hand, LV-MAP and LVQ show lower session blocking probability at the highest level than DV-MAP, DVQ, and DMAP because the sessions arrived at the system, do not attempt to register with the root MAP. We also observe that the session blocking probability of LVQ is higher than that of LV-MAP in the highest and the second levels because conversational sessions attempt to register with the root MAP first. Fig. 9(b) plots the system blocking probability versus the session arrival rate for the six schemes where DV-MAP, DVQ, and DMAP have the same system blocking probability as ps in Eq. (10). We observe that DV-MAP, DVQ, and DMAP show the lowest system blocking probability since the three schemes search the entire hierarchy of MAPs to select a MAP from the highest level to the lowest level. On the other hand, under LV-MAP, a blocked session attempts only one of its neighboring MAPs rather than the entire hierarchy, so that LV-MAP shows a slightly higher system blocking probability as compared to DMAP and DV-MAP. LVQ shows a similar behavior as LV-MAP because in LVQ, LV-MAP is applied for non-conversational sessions. The session blocking probability of LVQ is slightly higher than that of LV-MAP when the session arrival rate is smaller than 0.6, since the conversational sessions select the root MAP first, while when the load is high, the MAPs in lower levels, are likely to be overloaded as well. As we have expected, the static scheme shows the highest system blocking probability because a blocked session is not allowed to register with other MAPs rather than the MAP supporting the blocked session’s velocity. Finally, we can see from these results that DVQ is more desirable than LVQ, especially at low loads, in

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W. Chung et al. / J. Parallel Distrib. Comput. 72 (2012) 838–855

a

b

Fig. 9. The session blocking probability and the system blocking probability for DMAP, DV-MAP, and LV-MAP.

terms of system blocking probability at the cost of the signaling cost for inter-domain handover, which will be shown in the next section. Likewise, DV-MAP and DMAP show lower system blocking probability and higher inter-domain handover signaling cost than LV-MAP.

the deployed hierarchical MAP structure has at least three levels, the inter-domain handover signaling cost for LV-MAP is as follows: CiHO = (1 − p(i) )Ci +



1 (i) 1 p (1 − p(i+1) ) Ci+1 + CR 2 2



1 1 + p(i) (1 − p(i−1) ) Ci−1 + CR 2 2

4.2. Signaling cost for inter-domain handover In this section, we investigate the signaling cost for interdomain handover by using the session blocking probability which is obtained from Section 4.1. We denote by CA−B the average cost of exchanging a message between nodes A and B. Then, let CF represent the total signaling cost for inter-domain handover in F-HMIPv6. On the basis of the signaling procedure in [9], the total cost is expressed as

1

2 1 (i) (i−1) + p p (2CMN −oAR + CMIP v6 ), 2 for 1 < i < n



C1HO = (1 − p(1) )C1 + p(1) (1 − p(2) ) C2 +

CR = 3CM + 2CMAP −HA/CN + CnMAP −nAR + CMN −nAR

(19)

where CF already includes the transmission costs of the Prebinding Update and the Pre-binding Ack messages as shown in Fig. 7. 4.2.1. Signaling cost in LV-MAP, DMAP, and DV-MAP For the LV-MAP scheme, let Ci be the signaling cost when an MN registers with a MAP on the ith level. Then, the new status information of the selected MAP should be sent through the links from the MAP to the ARs which are associated with the MAP. The number of links needed to update MAP cache is 2j − 2 where j = n + i − 2. In this context, the additional cost for updating the MAP cache is (2j − 2)CM where CM denotes the signaling cost for exchanging a MAP option between neighboring MAPs. Then, Ci is expressed as follows: Ci = CF + (2j − 2)CM

(20)

where CMAP −AR from a leaf MAP to an AR is assumed to have the same cost as CM . Let CiHO denote the signaling cost for inter-domain handover in the case that a MAP at the ith level is selected. Then, supposing that

(21) 1 2

 CR

+ p(1) p(2) (2CMN −oAR + CMIP v6 )

(18)

Let CR denote the signaling cost for re-association between an existing MN and a MAP. The re-association procedure illustrated in Fig. 7 enables us to evaluate the signaling cost for the re-association as follows:



+ p(i) p(i+1) (2CMN −oAR + CMIP v6 )

CF = 7CMN −oAR + 5CoAR−oMAP + 4CoMAP −nMAP

+ 4CnMAP −nAR + 2CMN −nAR + 2CnMAP −HA/CN .



(22)



CnHO = (1 − p(n) )Cn + p(n) (1 − p(n−1) ) Cn−1 +

1 2

 CR

+ p(n) p(n−1) (2CMN −oAR + CMIP v6 )

(23)

where CMIP v 6 denotes the signaling cost for registering with HA and it is computed as CMIP v 6 = 2CMN −nAR + 2CnAR−nMAP + 2CnMAP −HA . In our analysis, we assume that the MNs’ velocities are uniformly distributed over all levels and when the selected MAP, mk suffers from an overload, either a newly arrived MN or one of the MNs serviced by the selected MAP registers with the least overloaded MAP between the neighboring MAPs, mp and mc with equal probability. The least overloaded MAP between mp and mc is selected with equal probability as well. Then, when the LV-MAP scheme is adopted, the average signaling cost for inter-domain handover is given by CLV =

n  2i−1 HO Ci . n 2 −1 i =1

(24)

A blocked MN attempts to register with its neighboring MAPs based on the load status in the LV-MAP, while in the static scheme, an MN simply registers with HA/CN as a general MIPv6. Thus, the average signaling cost for inter-domain handover for the static scheme is obtained as Cstatic = (1 − ps )CF + ps (2CMN −oAR + CMIP v 6 ) where ps is equal to Eq. (3) as explained in Section 4.1.4.

(25)

W. Chung et al. / J. Parallel Distrib. Comput. 72 (2012) 838–855

In the DMAP scheme, the status information of the MAPs is not maintained in the network. Recall that when a MAP is overloaded, the MN probes the MAP tree at the next level rather than reassociating an existing MN. Based on the signaling for DMAP presented in Fig. 8, the average signaling cost of DMAP for interdomain handover is expressed as follows: CDMAP = (1 − p(s1) )CF + p(s1) (1 − p(s2) )(CF + CMAP ) + · · ·

+

n−1 

4.2.2. Signaling cost in LVQ and DVQ Similarly with CDV ,1 and CDV ,2 , we let CQ ,1 and CQ ,2 denote the inter-domain handover signaling costs for two cases: whether all Q the MAPs in the HMIPv6 network are overloaded or not. Let Ci,j and Q

CHA denote the same meanings as Ci,j and CHA , respectively, except that a newly arrived MN has a conversational session. Then, we have

 Q Ci,n

p(si) (1 − p(sn) )(CF + (n − 1)CMAP )

=

+

ps {(CF − CMN −oAR − CoAR−oMAP )



+ (n − 1)CMAP }

(26)

Q

CHA =

{CF + (i − 1)CMAP + (n − i)CR + CMIP v6 } ,

for 1 ≤ i ≤ n

(27)

(i)

where ps is obtained from Eq. (9). Similarly, the registration cost for the case that a newly arrived MN registers with HA is given by

CHA =



q(l)

  i−1 (l)  pQ q(l) l=1

n 

n 

(1 − p(Qi) )

Ci,n + CHA . Q

(31)

Q

(32) (33)

Q

Next, we derive Ci,j when the HMIPv6 network is not overloaded (i.e., j ̸= n) as follows: Ci,0 = (1 − q(1) )CF Q

(34)

 Ci,1 = (1 − q(j+1) ) Q

j 

 Q Ci,j

(j+1)

= (1 − q

)

 (1)

 q(l)

l =1 j 

(l)

q

l =1

pQ 1 − (1) q

(CF + iCR )

  i−1 (l)  pQ l =1

q(l)

(j)

pQ

(35)



1 − (j) q

× {CF + (j − 1)CMAP + (i − j + 1)CR }, for 2 ≤ i ≤ n.

(36)

Using Eqs. (34)–(36), we can get C Q ,2 =

n −1  i +1 

Ci,j . Q

(37)

Finally, in both LVQ and DVQ, the signaling cost of inter-domain handover for an MN with a conversational session is CQ = CQ ,1 + C Q ,2 . Noting that in LVQ and DVQ, LV-MAP and DV-MAP are performed respectively, when an MN having a non-conversational session, arrives in the HMIPv6 network, CiHO and CDV in Section 4.2.1 are used for the MN with a non-conversational session. The average signaling cost for inter-domain handover in LVQ and DVQ, are given by

(i)

{CF − CMN −oAR − CoAR−oMAP + (n − 1)CMAP } .

(28)

Finally, we have the inter-domain handover signaling cost for the case that all the MAPs are overloaded as follows: Ci,n + CHA .

Ci,j .

n  (2n − 2)γ + 1 HO (2n − 1)γ C1 + n CQ + CiHO n 2 −1 (2 − 2)γ + 1 i =2

(38)

and CDVQ = (1 − γ )CDV + γ CQ ,

(39)

respectively.

Then, from the Appendix in [4], CDV ,2 is obtained as n−1  i+1 

CLVQ =

(29)

i=1

CDV ,2 =

n

i =1

ps

n+1

CDV ,1 =

C Q ,1 =

(l)

i=1



i=0 j=1

ps

n+1

pQ

1 − (i) q

q(l)

l =1

l =1

l =1

n 

q

(i)

  i−1 (l)  pQ

× {CF − CMN −oAR − CoAR−oMAP + (n − 1)CMAP }

(i)

where ps is obtained from Eq. (9) and CMAP indicates the signaling cost for probing a MAP, which is given by CMAP = 2CMN −oAR + 2CoAR−oMAP + 2CoMAP −nMAP . In the above Eq. (26), the last term represents the signaling cost for the case that all the MAPs in the HMIPv6 domain are overloaded, which is evaluated by subtracting the transmission cost of forward notification from CF and adding the signaling cost for probing MAPs at all levels. Under DV-MAP, when a newly arrived MN is blocked by the MAP due to overload, either the new MN or one of the MNs serviced by the MAP is supposed to register with the child MAP. Hence, either the registration or the re-association takes place j times if the MAPs at 1 through (j − 1) levels are overloaded. Let CDV ,1 and CDV ,2 denote the inter-domain handover signaling costs for two cases, respectively: whether all the MAPs in the HMIPv6 network are overloaded or not. Let Ci,j denote the signaling cost in the case that a newly arrived MN registers with the MAP located at the ith (1 ≤ i ≤ j + 1) level when all the MAPs located above the (j + 1)th level are overloaded. Under the assumption that the MN registers with the one among n MAPs at each level and HA with equal probability, we have

Ci,n =

(l)

× {CF + (i − 1)CMAP + (n − i)CR + CMIP v6 }, for 1 ≤ i ≤ n

(i)

i=1

n 

n  l =1

i=1 n 

847

(30)

i=0 j=1

Then, in DV-MAP, we have the average signaling cost for interdomain handover as CDV = CDV ,1 + CDV ,2 .

4.2.3. Numerical results The parameters and their values used for numerical results are shown in Table 3, which are obtained from [14]. Fig. 10 plots the signaling cost per inter-domain handover versus the session arrival rate for DMAP, LV-MAP, DV-MAP, LVQ, and DVQ, and static schemes. From this figure, we observe that the static scheme requires the lowest signaling cost among the six schemes. However, the lowest signaling cost of the static scheme is attained at the cost of high system blocking probability, as shown in

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W. Chung et al. / J. Parallel Distrib. Comput. 72 (2012) 838–855

Table 3 Input values of CA−B parameters. Parameter

Value

Parameter

Value

CMN −oAR , CMN −nAR CnMAP −HA/CN

5 30

CoAR−oMAP , CnAR−nMAP , CM CoMAP −nMAP

10 15

Fig. 10. Comparison of inter-domain handover signaling costs for LV-MAP, DV-MAP, and DMAP.

Fig. 9(b), as well as a high number of inter-domain handovers which will be verified in Section 5. We also observe that our proposed LV-MAP scheme requires the next lowest signaling cost for inter-domain handover and the proposed LVQ shows a little higher signaling cost than the LV-MAP since the signaling due to re-association, is increased by conversational sessions in the LVQ. Interestingly, as the session arrival rate increases, the signaling cost for LV-MAP and the static schemes decreases, contrary to the other two schemes. This is due to the fact that under LV-MAP, the cost for updating the MAP cache is not induced as the overall system blocks more sessions. Similarly, under the static scheme, the signaling cost for F-HMIPv6 is not incurred as the system blocking probability increases, so that the average signaling cost is lessened. Under DMAP, DV-MAP, and DVQ, all arriving sessions attempt to register with the root MAP first even if the root MAP is overloaded. We see that the signaling costs for DV-MAP and DVQ are higher than that for DMAP because the re-association process may operate when an MN is blocked in the DV-MAP and the DVQ, while the signaling cost for DVQ is greater than that for DV-MAP because the re-association occurs more frequently in DVQ than in DV-MAP, to support conversational sessions. 5. Performance evaluation via simulation Simulations were conducted for evaluating the performance of the proposed DV-MAP, LV-MAP, LVQ, and DVQ schemes, compared with DMAP and static schemes in terms of the average handover delay, the average number of inter-domain handovers, the system blocking probability, and the load distribution. 5.1. Simulation model An event-driven simulator has been developed in C++ to simulate DV-MAP, LV-MAP, LVQ, DVQ, DMAP, and static schemes. In the simulation, all the MAPs are organized as a binary tree structure with the height n = 3. We assume that each AR provides a circular topology with a radius of 500 m and the maximum number of MNs each MAP can serve is ten. During the simulations,

the MNs are uniformly distributed to all the ARs and then they start to move. Each MN can generate at most one session, the duration of which has an exponential distribution with a mean of 180 s. A session arrival process follows a Poisson distribution with various mean values ranging from 0.2 to 1. The sessions are generated with the equivalent ratio for the four traffic classes shown in Table 2. The mobility characteristics of the MNs are categorized into three classes with the equivalent ratio: vehicle, bicycle, and pedestrian as done in [12]. Each class has a maximum speed, vmax and a set of preferred speeds, vpref which consists of 35 vmax and vmax in the simulation [2]. For mobility of the MNs, we use the Smooth Random Mobility model [2]. When an MN is generated, its initial velocity is chosen from the two preferred speed values, 53 vmax , vmax , and the range [0, vmax ] with probabilities of 0.2, 0.5, and 0.3, respectively, where a uniform distribution is assumed on the range of [0, vmax ]. Then, the MN moves with the selected speed until a new target speed is set again. The target speed is updated at a time interval which follows an exponential distribution with a mean of µv s. Whenever a new target speed is decided, the MN accelerates or decelerates until the target speed is reached or a new target speed is decided again, denoted by amin and amax . The maximum deceleration and acceleration is noted in m/s2 . The MN selects a random acceleration/deceleration value from [amin , amax ]. It also decides whether to change its movement direction or whether to keep it with probabilities of 61 and 56 , respectively, at a time interval with an exponential distribution the mean of which is µϕnew s. The parameter values for a mobility model, which are obtained from [12,2], are given in Table 4. The two input sets shown in Table 4 represent two different levels of mobility. We initialize the speed range of each MAP in the ith level with , vmax − i · vmax ] where vmax is obtained from the [vmax −(i − 1)· vmax n n vehicle type. Then, the speed range of each MAP in the ith level, is set as follows: [5.57, 8.35 m/s], [2.78, 5.56 m/s], and [0, 2.77 m/s] for Input1; [12.98, 19.47 m/s], [6.49, 12.97 m/s], and [0, 6.48 m/s] for Input2, when i = 1, 2, and 3, respectively. All the simulations are run to obtain the results in a 95% confidence interval. 5.2. Handover delay To evaluate the handover delay, we consider the time interval between the moment when the MN receives the last packet through the previous point of attachment and the moment when it is able to receive the first packet from its CN through the new point of attachment after the BU is completed (local BU and regional BU for intra and inter-domain handovers, respectively). Two handover cases have to be distinguished: an intradomain handover occurs when an MN changes its AR within the MAP-administrated domain while an inter-domain handover is performed when an MN moves out of the current administrative domain. Let dintra and dinter be the delay for intra- and inter-domain handovers, respectively. We also let Pintra and Pinter denote the average ratios of intra and inter-domain handovers, respectively. Then, the average handover delay, dav g is given by dav g = Pintra dintra + Pinter dinter

(40)

where Pintra + Pinter = 1. Fig. 11 illustrates the signaling procedure based on F-HMIPv6 when an intra-domain handover takes place. Let dA−B denote the delay to send a message between A and B nodes. We denote by dRS_RA the delay for detecting the movement by exchanging RS and RA messages between the MN and the new AR. From Fig. 11, we have dintra = dL2 + dRS_RA + 2dAR−MN + 2dAR−MAP .

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W. Chung et al. / J. Parallel Distrib. Comput. 72 (2012) 838–855

849

Table 4 Parameter values for mobility model. Parameter

Vehicle

Bicycle

Input1

vmax

Input2

8.34 m/s

19.46 m/s

−2.4 m/s2 1.5 m/s2

amin amax

µv µϕnew

−5.6 m/s2 3.5 m/s2

5.88 m/s

0.66 m/s

1.54 m/s

−0.18 m/s2 0.12 m/s2

−0.42 m/s2 0.28 m/s2

Table 5 Parameter values for average handover delay. dAR−MN

dAR−MAP

dMAP −HA/CN

Value

50 ms

7 ms

4 ms

52 ms

Input2

−1.68 m/s2 1.12 m/s2

Fig. 11. Signaling procedure for intra-domain handoff.

dL2

Input1

2.52 m/s

75 s 360 s

Parameter

Input2

−0.72 m/s2 0.48 m/s2

25 s 120 s

Based on the signaling procedures presented in [9], the interdomain handover delay is given by dinter = dL2 + dRS_RA + 2dAR−MN + 2dAR−MAP

+ 2dMAP −HA/CN .

Pedestrian

Input1

(42)

Unlike the intra-domain handover, dAR−MAP in Eq. (42) varies depending on the level in which the selected MAP is located (i.e., what MAP selection scheme is used). Table 5 shows the parameters and their values for evaluating the average handover delay, which are based on [7]. 5.3. Simulation results and discussions Fig. 12(a) and (b) show the ratio of inter-domain handovers for all handovers during the simulation time for each traffic class. We observe that LVQ and DVQ schemes show a much smaller ratio of inter-domain handovers for conversational traffic class at the price of a larger ratio for the other three non-conversational sessions, compared to the other four schemes. Fig. 13(a) and (b) plot the ratio of inter-domain handovers for the conversational traffic class versus the session arrival rate for all the six schemes. In these figures, we see that both LVQ and DVQ schemes achieve a smaller number of inter-domain handovers for the conversational class than the other four schemes. The ratio increases as the arrival rate increases since the MAPs in the HMIPv6 system are loaded with more conversational sessions and hence, the conversational sessions are more likely to directly register with the HA. In addition, we can see that the ratio for DVQ is much lower than LVQ. This is because not only the MNs with conversational sessions but also the MNs with non-conversational sessions, attempt to register with the highest MAP in DVQ while in LVQ, the MNs with non-conversational sessions are associated

125 s 600 s

with the MAPs according to the MNs’ velocity. However, LVQ shows smaller number of inter-domain handovers for the conversational class, compared to DV-MAP, LV-MAP, and static schemes. Tables 6 and 7 show the average handover delay for each traffic class. The handover delay is measured based on Eqs. (41) and (42). Then, using the measured intra- and inter-handover delay and the ratio of inter-domain handovers shown in Fig. 12 (i.e., Pintra , Pinter ), we compute the average handover delay from Eq. (40). From Tables 6 and 7, we see that the LVQ and DVQ schemes can reduce the average handover delay for conversational sessions. More specifically, the improvements of LVQ over LVMAP, DMAP and static schemes are about (3.48%, 9.77%, 7.68%) and (5.01%, 11.17%, 10.71%) for Input1 and Input2, respectively. The improvement of DVQ over DV-MAP, DMAP, static, and LVMAP schemes are (17.26%, 28.77%, 27.13%, 23.81%) and (17.94%, 29.05%, 28.68%, 24.12%) for Input1 and Input2, respectively. This improvement comes from the fact that the number of inter-domain handovers, is reduced for conversational traffic class under LVQ and DVQ as the MNs with conversational sessions can register with the highest MAP unless the highest MAP is already full of other conversational sessions. We can see that in terms of the handover delay, DVQ performs the best for conversational class, while performing worse than the other schemes for other traffic classes. It is also observed from the tables that DV-MAP shows longer handover delay for conversational class, while achieving shorter handover delay for other classes, compared to DVQ. The handover delay of DV-MAP is shorter than LVQ for the four traffic classes because DV-MAP focuses more on reducing the interdomain handovers in the overall system than on load distribution which is still the aim of LVQ. However, the reduced average handover delay for DV-MAP is attained at the cost of increased signaling cost and uneven load distribution compared to LVQ. Here, we note that streaming services can also be classified into delaysensitive traffic although its delay requirement is less stringent than conversational class, whereas Interactive and Background services are delay-tolerant [1]. Accordingly, the streaming sessions may suffer from delay performance degradation in DVQ. Thus, if the QoS policy is to provide a fair delay performance for all the four classes, DV-MAP can be applied to the network. Or if the network administrator would like to ensure that conversational sessions are guaranteed the highest level of service on the network, DVQ can be employed. Fig. 14(a) and (b) show the total number of inter-domain handovers versus the session arrival rate during the entire simulation time. We see that both LV-MAP and DV-MAP schemes effectively reduce the inter-domain handovers, compared to DMAP and static schemes. More specifically, in terms of the number of inter-domain handovers, the average improvements of LV-MAP over DMAP and the static scheme are around 17.95% and 18.61%, respectively while the improvements of DV-MAP over DMAP and the static scheme are 37.04% and 36.89%, respectively. This makes sense because both LV-MAP and DV-MAP select a MAP based on the MN’s velocity. That is, DMAP does not consider the MN’s velocity and the static scheme does not adapt the velocity range of the MAPs to the velocity of currently active MNs in the network. We also see that the inter-domain handovers are reduced more by DVMAP than by LV-MAP, because DV-MAP selects the furthest MAP

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a

b

Fig. 12. The ratio of the inter-domain handover for each traffic class.

a

b

Fig. 13. The ratio of inter-domain handover for conversational traffic class. Table 6 Average handover delay for each QoS class with Input1. Schemes

LVQ DVQ DV-MAP DMAP STATIC LV-MAP mLV-MAP

Input1 Conversational (ms)

Streaming (ms)

Interactive (ms)

Background (ms)

132.1 104.3 126.0 146.4 143.1 136.9 128.8

144.5 150.4 125.6 146.6 142.7 136.9 128.4

144.3 150.7 125.9 146.7 143.1 136.8 129

144.2 150.2 125.7 146.4 143.3 136.5 128.9

to support the MN’s velocity, while LV-MAP does not consider the distance between the MAP and the MN. In addition, we observe an increase in the total number of inter-domain handovers for DVQ and LVQ, compared to DV-MAP and LV-MAP, respectively. This is because some MNs with non-conversational sessions move fast, but should register only with a lower level MAP due to other conversational sessions. To investigate the load distribution, we use the fairness index of loads observed at all the MAPs in the network. During the simulation, the load at each level, ρi , is recordedevery five seconds and then the fairness index is computed as

(

n

i

ρi )2 . ρi2

In Fig. 15(a)

i

and (b), we plot the fairness index versus the session arrival rates. These two graphs indicate that the fairness index value for LV-

MAP is the highest among the four schemes for the entire range of session arrival rate. Thus, we know that LV-MAP performs the best in distributing the load, among the four schemes. On the other hand, it is observed that at a high session arrival rate (greater than 0.8), the six schemes achieve similar fairness index values because the load of all the MAPs approaches full capacity. For LVQ, the fairness index value is smaller than that for LV-MAP since the conversational sessions attempt to register with the highest MAP. This registration is performed regardless of whether the load is concentrated on the highest MAP, while LV-MAP distributes the load when the highest MAP is overloaded. On the other hand, the fairness index value for DVQ is almost equal to that for DV-MAP. This is because both DV-MAP and DVQ schemes fill the hierarchy of the MAPs from the highest level to the lowest level.

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Table 7 Average handover delay for each QoS class with Input2. Schemes

Input2

LVQ DVQ DV-MAP DMAP STATIC LV-MAP mLV-MAP

Conversational (ms)

Streaming (ms)

Interactive (ms)

Background (ms)

130.7 104.4 127.2 147.1 146.4 137.6 129.6

145.2 149.7 127.5 147.2 146.6 137.5 129.8

145.2 149.7 127.4 147.1 146.5 137.4 129.3

145.1 149.6 127.3 146.8 146.3 137.4 130.6

a

b

Fig. 14. Total number of inter-domain handovers.

a

b

Fig. 15. Fairness index of loads among MAPs.

Fig. 16(a) and (b) show the system blocking probability for all the six schemes. From Fig. 16 as well as Fig. 9(b) in Section 4.1, what we see is that these simulation results match the numerical results quite well. That is, the static scheme shows the highest system blocking rate because in the static scheme, the blocked sessions register with their HA/CN without trying to register with other MAPs. It can be also observed that LV-MAP has a higher system blocking probability than DMAP as well as DV-MAP for both Input1 and Input2. As mentioned in Section 4.1, this is because LVMAP attempts only the neighboring MAPs rather than the entire hierarchy when the selected MAP is overloaded. On the other hand, DV-MAP and DMAP perform the best in terms of the system

blocking probability since they fill the MAPs from the highest level to the lowest level. In Fig. 16, we can also see that the system blocking probability for DVQ is almost the same as that for DVMAP since both schemes select the MAPs from the highest level to the lowest level, resulting in similar load status of the network. For LVQ, the system blocking probability is much lower than that for LV-MAP. We ascribe the lower system blocking probability for LVQ to the fact that the MNs with conversational sessions, do not probe only the neighboring MAPs but the entire hierarchy to determine whether there is an available MAP. Similarly, under the static scheme, the signaling cost for F-HMIPv6 is not incurred as the system blocking probability

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a

b

Fig. 16. System blocking probability.

a

b

Fig. 17. Average signaling cost for an inter-domain handover.

increases, so that the average signaling cost is lessened. Under DMAP or DV-MAP, all arriving sessions attempt to register with the root MAP first even if the root MAP is overloaded. We also see that the signaling cost in DV-MAP is higher than that in DMAP because the re-association occurs when an MN is blocked. Even though DV-MAP outperforms the other two existing schemes in terms of the frequency of inter-domain handovers and the session blocking probability, it is attained at the cost of increased signaling overhead due to the re-association procedure shown in Fig. 7. The average signaling cost per MN is plotted in Fig. 17. As expected from the numerical results in Fig. 10, we see from the simulation results of the average signaling cost per MN and the blocking probability that the average signaling cost for LVMAP starts to decrease from the point where the session blocking probability reaches around 0.1 for both input values (the system blocking probability reaches around 0.1 when the session arrival rate is around 0.4 and 0.5 for Input1 and Input2, respectively). This is because under LV-MAP, the blocked sessions are more likely to fail to be re-associated with the neighboring MAP as the session arrival rate increases from the peak point, resulting in less signaling cost, compared to DV-MAP, DVQ, and DMAP. On the other hand, the signaling cost for DV-MAP and DMAP increases with the increase of the session arrival rate. Thus, we see that under LV-MAP, the signaling cost for inter-domain handover

is less than that under DV-MAP when the hierarchy of the MAPs is overloaded, as we intended for the two schemes in Section 3.1. The static scheme shows the lowest signaling cost at the price of a higher session blocking rate. In addition, the LVQ scheme shows almost the same performance as LV-MAP with regard to the average signaling cost. This is because the signaling procedure for LVQ is exactly the same as LV-MAP except for the case that a conversational session registers with a lower MAP after the probing process. However, such probing process does not take place frequently, resulting in nearly equal performance between LVQ and LV-MAP in terms of the average signaling cost for interdomain handover. In contrast to the LVQ scheme, the average signaling cost for DVQ is much higher than DV-MAP since the total number of inter-domain handovers for the DVQ scheme is much higher than that for DV-MAP. It should be noted that the high signaling cost for DVQ is also caused by frequent re-association processes incurred to associate the MNs of conversational sessions with the highest MAP. We next conduct the simulation tests for n = 5. In this simulation, the two mobility models, Input1 and Input2 are assigned to each MN with the equal probability. Table 8 shows the average handover delay for each traffic class. From the table, it can be seen that DVQ provides conversational class with the smallest average handover delay also for n = 5. Figs. 18–21 show the total number

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Table 8 Average handover delay for each QoS class when n = 5. Schemes

LVQ DVQ DV-MAP DMAP STATIC LV-MAP mLV-MAP

Input1 and Input2 Conversational (ms)

Streaming (ms)

Interactive (ms)

Background (ms)

121.3 107.8 122.4 145.1 146.3 138.3 126.5

144.2 148.3 123.4 144.2 145.3 138 128.6

145.2 148.4 122.4 145.5 146.3 138.1 128.5

145.2 148.3 123.4 145.2 146.3 139 128.7

Fig. 20. System blocking probability for n = 5. Fig. 18. Total number of inter-domain handovers for n = 5.

Fig. 19. Fairness index of loads among MAPS for n = 5.

Fig. 21. Average signaling cost for an inter-domain handover when n = 5.

of inter-domain handovers, the fairness index, the system blocking probability, and the signaling cost results, respectively, when n = 5. We see from these figures and the table that all the schemes achieve similar behavior as n = 3. Similar to Fig. 15 for n = 3, LVMAP and LVQ show smaller fairness index value than DV-MAP and DVQ because the hierarchy of the MAPs are filled from the highest level to the lowest level in DV-MAP and DVQ schemes. However, the number of inter-domain handovers and the blocking probabilities of all the schemes are higher and lower, respectively, for n = 5 than those for n = 3 because more MAPs are available for reassociation in the system with n = 5 than with n = 3. For the same reason, the signaling costs are higher for n = 5 than those for n = 3. That is, more signaling messages due to more

re-associations are generated in the system with n = 5 than with n = 3. 5.4. More discussions The simulation results in the previous section clearly reveal that LV-MAP enables improvement in terms of the signaling cost and fairness index rather than the other schemes, however, this performance is off-set by its blocking probability and handover delay. From the simulation results, what we can expect with respect to LV-MAP is that the blocking probability and handover delay of LV-MAP might be improved, maintaining the LV-MAP’s benefits by allowing a blocked MN to search the tree to the root or

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Fig. 22. Average TCP throughput per session for background traffic.

leaf MAP rather than its parent or child MAP, to find an appropriate MAP in the LV-MAP. To demonstrate the performance of the modified LV-MAP (mLV-MAP), we perform more simulations. In the simulation, a slightly more MNs blocked at the selected MAP could register with the root MAP in mLV-MAP than in LV-MAP. As a result, in terms of the number of inter-domain handovers, the improvement by mLV-MAP over LV-MAP is small as 2.2% as shown in Figs. 12–14 and mLV-MAP improves the handover delay by 5.7% as shown in Tables 6 and 7. We observe from Fig. 16 that the blocking probability improvement of mLVMAP over LV-MAP is 20.3% because more MNs could register with a MAP in the HMIPv6 system by searching the tree beyond the neighbor MAP. However, the signaling cost in mLV-MAP is higher than in LV-MAP, as shown in Fig. 17. Fig. 15 shows that mLVMAP has similar fairness index to LV-MAP. We also find that the blocking probability of DV-MAP is still much smaller than that of mLV-MAP with higher signaling cost. We also observe from Table 8 and Figs. 18–21 that when n = 5, mLV-MAP behaves similarly to when n = 3 in terms of the average handover delay, the frequency of inter-domain handovers, the fairness index, the blocking probability, and the signaling cost. Finally, if the mean handover delay and the blocking probability are more important than the signaling cost as for VoIP, then we suggest using DV-MAP. Otherwise, if the network administrator focuses on the signaling overhead in the network, we suggest using the LV-MAP. Additionally, to see the effect of the different schemes on background traffic using TCP, we simulate TCP and then measure the average throughput for the background traffic. Fig. 22 shows the average throughput per background session for the different schemes. We see from Fig. 22 that DVQ and DV-MAP schemes achieve the lowest and the highest throughput, respectively. This is because in DVQ, the conversational sessions can register first with the MAPs at higher levels, while DV-MAP aims to reduce the inter-domain handovers for the four traffic classes in the overall system. 6. Conclusions and future extensions In this paper, we focused on MAP selection schemes for improving the performance of the HMIP network. We first described two dynamic MAP selection schemes proposed in our previous work, LV-MAP and DV-MAP. The basic idea of the two proposed schemes is to select an optimal MAP based on the MN’s mobility. The LV-MAP distributes loads over multiple MAPs for an overloaded HMIPv6 network, while for a less overloaded network, DV-MAP can be used to select the furthest MAP among non-overloaded MAPs supporting the MN’s velocity. We aim to reduce the inter-domain handovers and distribute the load over the MAPs. However, the previous MAP selection schemes do not provide QoS to real-time (i.e., delay-sensitive) traffic sessions.

Thus, we proposed two new MAP selection schemes for delaysensitive traffic sessions, LVQ and DVQ in this paper by extending our previous work. In the new MAP selection schemes, we have the MNs with conversational sessions registered with the highest MAP, while the other MNs with non-conversational sessions follow the LV-MAP or DV-MAP schemes. The simulation and numerical results showed that DV-MAP is more advantageous in terms of the frequency of inter-domain handovers and the system blocking probability, compared with the two existing schemes: DMAP which is based on the IETF HMIPv6 and the static scheme in which the MAP’s velocity range is fixed. Through the results, we have also demonstrated that LV-MAP outperforms DV-MAP and DMAP schemes in terms of the average inter-domain handover signaling cost and the load distribution, and the signaling cost could be reduced more by LV-MAP when the network load is high. The static scheme shows the lowest signaling cost at the cost of a higher session blocking rate and performs worse than LV-MAP with respect to the frequency of the inter-domain handovers and load distribution. We also found that the blocking probability and handover delay of LV-MAP could be improved by allowing a blocked MN to search the tree to the root or leaf MAP rather than its parent or child MAP, to find an appropriate MAP in the LV-MAP. At last, the results revealed that our MAP selection schemes for conversational sessions, DVQ and LVQ provide better QoS to the MNs holding delay-sensitive sessions, in that they reduce the inter-domain handovers for those MNs and the average handover delay, resulting in a shorter service disruption. Further, through the simulation of mLV-MAP where a blocked MN can search the tree beyond its neighbor MAP, it is shown that DV-MAP achieves smaller blocking probability and handover delay even than mLV-MAP. Therefore, DV-MAP is suggested to be employed in the network if the blocking probability and handover delay are one of the most important performance metrics. We believe that more challenging practical issues will show up in implementation of the proposed algorithms. They include how to handle varying speeds of vehicles, admission control methods for delay guarantee, and maintaining a reasonable TCP throughput of delay-tolerant applications, which is our future research direction. Acknowledgments This research was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0004733) and in part, by the ITRC program of MKE, Korea under NIPA-2012-(H0301-12-1003). References [1] 3GPP TS 23.107, Quality of Service (QoS) Concept and Architecture (Release 10), March 2011. [2] C. Bettstetter, Smooth is better than sharp: random mobility model for simulation of wireless networks, ACM MSWiM’01, Jul. 2001. [3] A. Campbell, J. Gomez, S. Kim, A. Valko, C. Wan, Z. Turanyi, Design, implementation, and evaluation of cellular IP, IEEE Wireless Commun. Magazine 7 (4) (2000) 42–49. [4] W. Chung, S. Lee, Cost-effective MAP selection in HMIPv6 networks, IEEE ICC, Jun. 2007. [5] W. Chung, S. Lee, Improving performance of HMIPv6 networks with adaptive MAP selection scheme, IEICE Trans. Commun. E90-B (4) (2007) 769–776. [6] Helsinki University of Technology (HUT), Dynamics mobile IP, http://dynamics.sourceforge.net. [7] R. Hsieh, A. Seneviratne, A comparison of mechanisms for improving mobile IP handoff latency for end-to-end TCP, ACM MobiCom’03, 2003. [8] D. Johnson, C. Perkins, J. Arkko, Mobility support in IPv6, IETF RFC 3775, Jun. 2004. [9] H.Y. Jung, H. Soliman, S.J. Koh, N. Takamiya, Fast handover for hierarchical MIPv6 (F-HMIPv6), Internet Draft, draft-jung-mipshop-fhmipv6-00.txt, Oct. 2005.

W. Chung et al. / J. Parallel Distrib. Comput. 72 (2012) 838–855 [10] H. Kaaranen, A. Ahtiainen, L. Latinen, S. Naghian, V. Niemi, UMTS Networks— Architecture, Mobility and Services, second ed., WILEY, 2005. [11] K. Kawano, K. Kinoshita, K. Murakami, A mobility-based terminal management in IPv6 networks, IEICE Trans. Commun. E85-B (10) (2002) 2090–2099. [12] K. Kawano, K. Kinoshita, K. Murakami, Multilevel hierarchical mobility management scheme in complicated structured networks, IEEE LCN, Nov. 2004. [13] R. Koodli (Ed.) Fast handovers for mobile IPv6, IETF RFC 4068, Jul. 2005. [14] W. Ma, Y. Fang, Dynamic hierarchical mobility management strategy for mobile IP networks, IEEE JSAC, vol. 22, no. 4, May 2004. [15] E. Natalizio, A. Scicchitano, S. Marano, Mobility anchor point selection based on user mobility in HMIPv6 integrated with fast handover mechanism, IEEE WCNC, Mar. 2005. [16] S. Pack, Y. Choi, M. Nam, Design and analysis of optimal multi-level hierarchical mobile ipv6 networks, Wireless Pers. Commun. 36 (2) (2006) 95–111. [17] S. Pack, T. Kwon, Y. Choi, Mobility-based load control scheme at mobility anchor point in hierarchical mobile IPv6 networks, IEEE Globecom, Nov. 2004. [18] S. Pack, M. Nam, Y. Choi, A study on optimal hierarchy in multi-level hierarchical mobile IPv6 networks, IEEE Globecom, Nov. 2004. [19] R. Ramjee, T. Porta, S. Thuel, K. Varadhan, S. Wang, HAWAII: a domain-based approach for supporting mobility in wide-area wireless networks, IEEE/ACM Trans. Networking 6 (2) (2002) 396–410. [20] H. Soliman, C. Castelluccia, K. El Malki, L. Bellier, Hierarchical mobile IPv6 mobility management, IETF RFC 4140, Aug. 2005.

WonSik Chung received his B.S. and M.S. degrees in Computer Science from Yonsei University, Seoul, Korea, in 2006 and 2008, respectively. His research interests include wireless communication, heterogeneous networks, and quality-of-service networking.

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Mun-Suk Kim has received his B.S. and M.S. degrees in Computer Science from Yonsei University, Seoul, Korea, in 2007 and 2009, respectively. He is currently working towards Ph.D. degree in Computer Science, Yonsei University. His research interests include wireless communication, heterogeneous networks, and quality-ofservicenetworking.

Jeonghoon Mo received the B.S. degree from Seoul National University, Korea, and the M.S. and Ph.D. degrees from the University of California, Berkeley. He is a Professor in the Department of Industrial and Information Engineering, Yonsei University, Seoul, Korea. Before joining the Yonsei, he was with AT&T Laboratories, Middletown, New Jersey, and with start-ups in San Jose, California. He worked in voice-over-IP (VoIP) quality assessment and the performance analysis of network processors. His research interests include transport/media access control (MAC) design of communication networks, WiMax, Wi-Fi, queuing theory, optimization, and quality of service. He is also involved with the WiMax Forum. SuKyoung Lee received her Ph.D. in Computer Science from Yonsei University, Seoul, Korea, in 2000. From 2000 to 2003, she worked with the advanced networking technologies division at the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA. She is currently an Associate Professor in the Department of Computer Science at Yonsei University, Seoul, Korea. Her current research interests include wireless and mobile networks.