Quality of service support in IEEE 802.11 wireless ad hoc networks

Ad Hoc Networks 2 (2004) 265–281 www.elsevier.com/locate/adhoc

Quality of service support in IEEE 802.11 wireless ad hoc networks Jamal N. Al-Karaki *, J. Morris Chang Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA Available online 17 April 2004

Abstract Supporting Quality of Service (QoS) in wireless networks is a challenging problem. The IEEE 802.11 LAN standard was developed primarily for elastic data applications. In order to support the transmission of real-time data, a pollingbased scheme called the point coordination function (PCF) was introduced in IEEE 802.11. However, PCF was not able to meet the desired and practical service differentiation requirements to fulfill the need of real-time data. Therefore, Task Group E of the IEEE 802.11 working group released several IEEE 802.11e drafts, whose main task is to support QoS in IEEE 802.11 LANs. The polling scheme of PCF is extended in IEEE 802.11e into the more complex hybrid coordination function (HCF). We found that HCF has several performance issues that may affect its anticipated performance. In this paper, we address these issues and propose a QoS enhancement over PCF, called enhanced PCF (EPCF) that enables Wireless LAN to send a combination of voice, data and isochronous data packets using the current IEEE 802.11 PCF. First, we compare the performance of the proposed model (EPCF) with the HCF function of the IEEE 802.11e through simulation. Second, we extend the proposed model (EPCF) to work in a multihop wireless ad hoc mode and present the advantages and limitations in this case. Simulation results demonstrate an enhanced performance of our scheme over the legacy PCF and a comparable performance to the IEEE 802.11e HCF in terms of the average delay and system throughput. However, EPCF is much simpler than HCF, provides flow differentiation, and is easy to implement in the current IEEE 802.11 standard.
2004 Elsevier B.V. All rights reserved. Keywords: Ad hoc networks; QoS; IEEE 802.11e; Clustering; Scheduling

1. Introduction Quality of Service (QoS) in wireless networks is a challenging problem because of many reasons. First, network bandwidth is of limited availability. Second, timely delivery of multimedia data is dif*

Corresponding author. E-mail addresses: [email protected] (J.N. Al-Karaki), [email protected] (J.M. Chang).

ficult due to mobility, low power capabilities and service disruption because of link failures and/or security problems. Third, the wireless channel fading and high bit error rate directly affect the throughput performance of the network. To enable QoS, the cooperation of all network elements is required. Any QoS assurances are only as good as the weakest link in the path between the sender and the receiver (for ease of reference, Table 1 provides a list of abbreviations used in the paper).

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2004 Elsevier B.V. All rights reserved. doi:10.1016/j.adhoc.2004.03.006

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Table 1 List of abbreviations used in this paper List of abbreviations IEEE BSS DS AP PC PCF DCF HC HCF HCCA EDCA MAC CSMA/ CA CFP CP CF-Poll CF-End CW CWmax , CWmin UPs MSDU DTIM TBTT NAV SIFS PIFS AIFS DIFS PF PHY QoS QSTA RTS/ CTS ACK AC UPs TXOP CAPs WLAN WM HOL CDMA VAP CBR, VBR

Institute of Electrical and Electronics Engineers Basic service set Distribution system Access point Point coordinator Point coordination function Distributed coordination function Hybrid coordinator Hybrid coordination function HCF controlled channel access Enhanced distributed channel access Medium access control Carrier sense multiple access/ collision avoidance Contention free period Contention period Contention free-poll Contention free end Contention window Contention window maximum and minimum, respectively User priorities MAC service data unit Delivery traffic indication message Target Beacon transmission time Network allocation vector Short inter frame space PCF inter frame space Arbitration inter frame space Double inter frame space Persistence factor Mode physical layer mode, coding and modulation scheme Quality of Service QoS stations Request to send/clear to send Acknowledgement Access category User priorities Transmission opportunity Controlled access phases Wireless local area network Wireless medium Head of line Code division multiple access Virtual access point Constant and variable bit rate, respectively

(802.11e) (802.11e) (802.11e) (802.11e)

(802.11e)

(802.11e) (802.11e)

(802.11e)

(802.11e) (802.11e) (802.11e)

IEEE 802.11 wireless LAN (WLAN) standard [1] has been widely and rapidly accepted in the wireless networks community. The main criteria that characterize 802.11 1 networks are simplicity and robustness against failures. This is due to the distributed approach using collision avoidance mechanisms which reduces the probability of collisions among competing flows. The 802.11 medium access control (MAC) layer supports two access methods: DCF (distributed coordination function) and PCF (point coordination function). The DCF is designed for best-effort data transmission by using carrier sense multiple access with collision avoidance (CSMA/CA). The DCF scheme does not provide any means of service differentiation and thus assumes that all flows have equal priority. The main concern of DCF is to reduce the collision among the flows that are competing for access to the wireless medium (WM). The PCF targets the transmission of realtime traffic as well as the best-effort data traffic where it differentiates between traffic of different priorities and allow frames of high priority a faster access to the WM. The PCF access method is based on a polling scheme controlled by an access point (AP). In brief, we may view 802.11 WLAN as a wireless version of the wired Ethernet, which supports best-effort service. QoS support in wireline as well as in wireless networks is a hot area of research. In fact, QoS is a key issue in the future wireless Internet [28]. Although lots of research have been done on supporting QoS in the Internet and other networks[22– 24,27], the challenge of QoS support for wireless networks remains an open problem. In the wireline world, the concept of cognitive packet network (CPN) [22,23] is presented, where intelligent peerto-peer routing is carried out with the help of ‘‘smart packets’’ based on best-effort QoS goals. In [23], the choice of a ‘‘goal’’ and ‘‘reward’’ function has been implemented to combat for stringent QoS requirements of packetized voice over CPN and then compared to IP routing protocol. In the wireless world, QoS support has recently grown largely where different schemes employing different 1 In the rest of the paper, we drop the prefix IEEE for convenience.

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variations of PCF and DCF were proposed [3–8]. However, in all previous schemes, there have been several tradeoffs between various parameters in supporting QoS. For example, some schemes modify the contention window size to provide QoS differentiation by increasing or decreasing it accordingly. This indeed may degrade the QoS performance. If the contention window size is increased, then some other mobile nodes in the network may starve. As such, these schemes provide a limited QoS support under the 802.11 standard. While the 802.11 standard has a limited QoS support, a set of QoS enhancements to the medium access control (MAC) constitutes the main part of the new 802.11e draft [2]. The motivation behind the 802.11e draft 2 stems from the fact that the DCF and PCF schemes were not able to fulfill the QoS requirements of multimedia applications. DCF is simple and allocate WM access to all flows in the same manner. PCF, though it includes service differentiation mechanisms, it still considers all flows from a specific station to have the same priority. Therefore, the 802.11e draft has introduced the enhanced distributed channel access (EDCA), which adds transmission prioritization to CSMA/ CA [16]. EDCA is a completely distributed scheme and allows each station to sort its traffic in four different access categories (AC) [15]. By doing this, EDCA provides service differentiation, taking into consideration the various needs of flows within a specific station. As such, EDCA could be considered as the new version of the legacy DCF [14]. The 802.11e draft also introduces a new coordination function named hybrid coordination function (HCF). HCF allows a hybrid coordinator (HC), typically located at the access point (AP), to start polling-based contention-free access at any time during the contention period to conform to the QoS parameterizations. These two new mechanisms for QoS support, namely EDCA and HCF, defined in the 802.11e draft have been evaluated through simulation in a recent work [9]. It has been found that both schemes perform better than the legacy 802.11 standard when the legacy PCF or DCF modes are used. 2 Please note that 802.11e is still a draft not a standard protocol and has not been officially approved to date.

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However, there are some concerns with HCF that is related to the mechanism of updating service information for mobile hosts. First, during the controlled contention period, which is the contention-free period controlled by the HC, each host gets an opportunity to send out a resource request frame. As a result, hosts can update the channel requirement information only when they get the opportunity during the contention phase. Being not able to communicate back the change in the allocation requirements immediately, hosts are forced to wait and then compete, which will affect their throughput and the overall network performance. It would be more efficient to make this kind of communications active, i.e., letting the stations indicate the change in their requirements in a prompt manner. Second, HCF imposes a burden on the network management module due to its complexity. For example, each station shall maintain the following variables in order to manage four instances of EDCA, as suggested by HCF: AIFSN, CWMin, CWMax, TXOPLimit, TXOPBudget[AC] and Load[AC], a total of 12 variables. In addition to those variables, each station needs also to maintain five other variables that measure the amount of time a station have already used from its budget (TxCounter, TxUsed, TxLimit, TxRemainder and TxMemory). Those variables will serve the purpose of managing the admission control procedure since the AP considers those variables to decide whether or not to admit new stations requesting association. Managing this high number of variables and communicating them between the stations and the AP on a regular basis could cause a threat to the efficient usage of network bandwidth. In conclusion, HCF relies on complex modelling and the use of a large number of variables to track the various measurements and needs in the network. Hence, a valid question is whether the simple 802.11 can be modified to address QoS in WLANs. In this paper, we propose an improvement on legacy PCF that would yield results comparable to HCF, without having to employ the many variables used by HCF. The improved PCF, called enhanced PCF (EPCF), does not need to maintain the many variables used by HCF. Notice that the essence of HCF is the many controlling variables it

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uses to support QoS. We believe that even fine tuning the HCF variables or decreasing the number of these variables cannot guarantee an enhanced performance of this new HCF than the current 802.11e HCF. In fact, this issue is hard to judge due to the many parameters used by HCF and due to the fact that a fine tuning of the variables may heavily depend on the traffic patterns in the network. On the other hand, our EPCF scheme has the advantage of being lightweight and efficient yet it yields results that are comparable to that of complex HCF. We shall prove our point through profound analysis and extensive simulation of the proposed scheme, EPCF. We also observed that most of the proposed protocols focused on a single-hop QoS guarantees (within one basic service set (BSS)), where it is assumed that an access point (AP) is serving a group of mobile hosts 3). However, 802.11 supports another mode of operation which is the multihop ad hoc mode where an infrastructureless environment is assumed. These multihop wireless ad hoc networks employ 802.11 as its underlying MAC. As of currently, multihop wireless networks are gaining much attention because of this infrastructureless feature, which is needed in several circumstances [10]. In Infrastructureless networks, each node is allowed to move freely and there is no fixed node called the AP as the case in the infrastructured single hop networks. As such, we also extend the proposed scheme, EPCF, to operate on wireless multihop ad hoc networks in order to support end-to-end QoS guarantees. Our contribution in this paper is threefold. First, we investigate QoS enhancements in the new 802.11e draft and compare it to the legacy 802.11. Second, we present an enhanced centralized scheme over the legacy 802.11 PCF, namely EPCF, and compare its performance to the 802.11e HCF. Third, we extend the proposed scheme, EPCF, to work in multihop ad hoc WLAN and present the advantages and drawbacks in this case. The rest of the paper is organized as follows. In Section 2, we identify and analyze the problems of QoS support in the legacy 802.11, and we also

3

We use mobile node, station, or host interchangeably.

explain the QoS enhancements in the new 802.11e deaft. Section 3 presents the new proposed centralized mechanism for QoS support on the current 802.11 PCF. Section 4 presents the multihop version of our scheme. We present a performance evaluation and comparison with the new 802.11e using simulation results in Section 5. The paper concludes with a summary in Section 6.

2. 802.11 QoS-support problems and QoS enhancements in 802.11e In this section, we review some of the limitations of the legacy 802.11 PCF. Then, we investigate the QoS enhancements presented in 802.11e, which was motivated by the legacy 802.11 limitations. 2.1. 802.11 problems The 802.11 legacy PCF has a limited QoS support although it was primarily designed to support multimedia delivery in WLAN. The heart of PCF is the point coordinator (PC). The PC, which is typically co-located with the AP, generates beacon frames to announce the beginning of a contention free period (CFP). The specific control frame, namely contention free-end (CF-End), is transmitted by the PC as the last frame within the CFP to signal the end of the CFP. Although PCF was meant to support real time data in the CFP, there are limitations with the legacy PCF that led to the current activities inside the 802.11 working group to enhance the protocol performance. These limitations motivated the development of the enhanced 802.11e protocol. 4 We will now discuss some of these problems. If PCF is supported in a basic service set (BSS), both PCF and DCF coexist and in this case, time is divided into superframes as shown in Fig. 1. Each superframe consists of a contention period (CP) where DCF is used, and a CFP where PCF is used. During the CFP, access point (AP) sends

4 Please note that 802.11e is still a draft not a standard protocol and has not been officially approved to date.

J.N. Al-Karaki, J.M. Chang / Ad Hoc Networks 2 (2004) 265–281 Superframe

Superframe CFP

CFP

CP

CP

Timing Diagram

Fig. 1. Superframe in IEEE 802.11.

contention free-poll (CF-poll) frames to stations when they are clear to access the medium. The AP transmits beacon frames periodically in order to deliver management information to mobile hosts. The boundaries between CFPs and CPs are marked by beacons carrying the delivery traffic indication message (DTIM), which is used to wake up stations in power-save mode to receive any buffered data frames. Mobile hosts can use the information present in the beacon frames in order to associate with the AP, which is performed during the CP. This association is mandatory if the terminal needs to transmit any data on the network and have its transmissions scheduled by the PCF, which is usually required for QoS-sensitive data (see Fig. 2). However, the current 802.11 PCF faces certain limitations which hinder its ability to support QoS [9]. We summarize some of these limitations here: • The unpredictable beacon delays and unknown transmission durations of the polled stations in PCF mode. • In the current 802.11 standard, stations can start their transmissions even if the MAC service data unit (MSDU) delivery cannot finish before the upcoming target beacon transition time (TBTT). This issue may severely affect the QoS facility as it introduces unpredictable time delays in each CFP.

SuperFrame

CFP repetition interval CFP

CFP B

PCF

DCF

B

PCF

DCF

Busy meduim

Fig. 2. The use of beacons and contention free period in IEEE 802.11.

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• Another problem with the PCF is concerned with the unknown transmission time of polled stations. A station that has been polled by the PC is allowed to send a possibly fragmented single frame and of arbitrary length. • Different modulation and coding schemes are specified in 802.11a (part of 802.11 standard); thus the duration of the MSDU Delivery that happens after polling is not under the control of the PC. As such, further QoS support to other stations that are polled during the rest of the CFP is not possible. 2.2. QoS enhancements in 802.11e In this subsection, we discuss the QoS enhancements detailed in the 802.11e draft, which is related to the EDCA and the HCF. The legacy DCF cannot support the QoS requirements of multimedia applications as it does not include prioritization mechanisms. Therefore, the 802.11 task group E proposed the EDCA mechanism which includes a prioritization enhancement based on different access categories (ACs). One or more user priorities (UPs) can be assigned to each AC. In this case, each AC has a distinct queue, an arbitration inter frame space (AIFS), and contention window parameters. Each AC contends for medium access with only one CSMA instance using the parameters that belong to its lowest UP. This corresponds to the priority of the AC as a whole. The AIFS length of a certain access category (AC) is calculated according to the following equation: AIFSðACÞ ¼ AIFSNðACÞ  aSlotTime þ aSIFSTime: The AIFSN[AC] (AIFS Number) values field specifies 4 AIFSN values, for ACs 0–3, respectively. Separate backoff timers are maintained for AC if a mobile host (MH) has several ACs. When the backoff timer of an AC counts down to zero, the MH transmits a frame from the queue with highest priority and initiates a transmission opportunity (TXOP), which is a bounded duration time interval in which the MH may transmit a sequence of SIFS-separated DATA frame exchanges. During the TXOP, the MH can send a burst of DATA frames separated by short inter

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frame space (SIFS). The transmission priority (TXOP) ends when there are no more frames to be transmitted or when the TXOP maximum duration expires. Besides EDCA, the 802.11e QoS facility includes an additional coordination function called HCF which will be discussed in the next section. We note that the 802.11e draft defines a new group of frames which are similar to those in the legacy PCF frame set but augmented with a large set of QoS attributes: QoS NULL, QoS DATA, QoS CF-ACK, QoS CF-POLL, QoS DATA+ CF-ACK, QoS CF-ACK+CF-POLL, QoS DATA+CF-POLL and QoS DATA+CF-ACK+CFPOLL. A CAP is a sequence of TXOPs initiated by the HC with the transmission of a QoS Data frame or QoS CF-POLL frame (see Fig. 3(b)). The CAP ends when the wireless medium remains idle for a double inter frame space (DIFS) interval. Furthermore, mobile stations can update the channel requirement information only when they get the opportunity during the contention phase. Hence, this is a passive process where a change in allocation requirement cannot be transmitted immediately. This contention is performed on a per-mobile host basis. However, the same mobile host might have many applications with different requirements. Hence if we chose a particular priority level for a station, then lower priority flows will get more allocation than is required and requirements of higher priority traffic will not be met. The per-host priority model also leads to another problem. For packets that require acknowledgments (ACKs) at the same priority level, if HC is not sending those ACKs back at the specific priority rate, the throughput of these flows CFP

B

CP

CAP

CAP

CAP

(a) TXOP Limit CF–poll SIFS

TXOP granted

DIFS

(b) Fig. 3. (a) The generation of CAPs in 802.11e (during CP). (b) The transmission opportunity grant in HCF.

will suffer at the mobile hosts. These potential problems of HCF might negatively affect its performance and results in an overall network performance degradation. On the contrary, the legacy PCF is much simpler and easier to implement. 2.3. HCF operation Like PCF, HCF includes a polling mechanism controlled by the AP, which is used during controlled access periods (CAPs) to implement its rules. The HCF combines functions from the DCF and PCF with some enhanced, QoS-specific mechanisms and frame subtypes to allow a uniform set of frame exchange sequences to be used for QoS transfers during both the CP and CFP. HCF is more flexible than PCF in the sense that CAPs can occur anytime during the superframe, with the ratio between contention-free and contention transmission being controlled by a token-bucket of time units. This is in contrast with legacy IEEE 802.11 in which the PCF based contention-free period (CFP) has a fixed position in the superframe, forcing QoS sensitive traffic to wait for the entire DCF contention period (CP) before being polled. However, to make the CFPs more frequent would require shortening the DTIM period, which would increase protocol overhead and wake-up stations in power save mode more frequently. During the CP, the HCF employs the DCA mechanism that provides differentiated, distributed acces to the WM for 8 UPs for QoS stations (QSTAs). The QoS facility accepts traffic from higher layers that belong to one of eight possible UPs. The frames will then be mapped from to one of four possible ACs. Collisions between ACs within a single station are dealt with internally and this case is referred to as virtual collision detection. To start a CP period, the same rules applied in EDCA are used, i.e., after AIFS plus backoff time, or when the station received a special poll frame, the QoS CF-Poll from HC. The QoS CF-Poll from HC can be sent after a PIFS idle period without any backoff. Therefore, the HC can issue polled TXOPs in the CP using its prioritized medium access. The HCF uses the EDCA that operates concurrently with a controlled channel access mechanism based on a polling mechanism that is similar

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to legacy PCF but it allows the HC to start contention-free controlled access phases (CAPs) at any time during a CP. The CAPs can be initiated after the medium remains idle for at least a PCF inter frame space (PIFS) interval (see Fig. 3(a)). To launch a CAP, the HC makes use of an access mechanism called the HCF controlled channel access (HCCA). The HCCA serves also as a way for the HC to learn which station needs to be polled, at which times, and for which durations. The HCCA makes use of the HC’s high priority of access to the wireless medium (WM) to initiate frame exchange sequences and allocate TXOPs to QoS stations (QSTAs) so as to provide limitedduration controlled access phase (CAP) to transfer QoS data. HC traffic delivery and TXOP allocation may be scheduled during both the CFP and CP to meet QoS requirements of particular traffic categories (TCs) or traffic streams (TSs). TXOP allocation and contention-free transfers of QoS traffic from the HC can be based on the HC’s QoS basic service set (QBSS) wide knowledge of the amounts of pending traffic belonging to different TSs and/or TCs. This kind of flexibility results in a better performance over legacy PCF although 802.11e-based mobile hosts are still allowed to support PCF.

3. The proposed scheme for QoS support in 802.11 WLANs In this section, we present our proposed scheme, called enhanced PCF (EPCF). We first present an overview of the proposed scheme, followed by the system model, and then the problem formulation. 3.1. Overview EPCF is an extension to the PCF of the 802.11 standard. The motivation stems from the fact that the 802.11 standard, though simple, does not guarantee timely delivery of packets. Although it is able to perform better than legacy 802.11 PCF, the new 802.11e HCF is too complex to be implemented and have some potential problems. On the

271

other hand, the 802.11 PCF is simple and has already been implemented and used. Hence, our objective is to come up with an enhanced version of 802.11 PCF that can have comparable performance to HCF while retaining the simplicity of PCF. Note that 802.11e HCF maintains a large set of variables in order to control the medium access, and hence be able to provide guaranteed service differentiation. However, reducing or varying the number of HCF variables is not guaranteed to preserve its superiority to the legacy 802.11 PCF, and hence HCF trades complexity for better performance. We prefer to enhance the simple PCF rather than suggest a new complex function that may not be easy to implement. Therefore, we propose an enhancement over PCF to support QoS. Our proposed scheme also addresses the performance issues of HCF that were mentioned earlier, especially the per-host priority model. Under EPCF, we show that each host can perform implicit service differentiation for different applications running at the same host and thus resolves this issue. Having that said, we now describe in details the design and operation of the proposed EPCF. Note that real-time traffic (multimedia) normally consists of delay-sensitive packets such as in the case of audio and video transmission. In this case, each packet needs a bound on the delay incurred while traversing the media between the source–destination pair. We refer to this time bound as the required maximum delay (Dmax ), and packets delayed beyond Dmax are discarded. For non-real time packets, the maximum delay value is set to large value. Packets with the lowest Dmax must be transmitted first. We have also studied the effect of packet-burst mode [25] on QoS support in WLANs [26]. In packet-burst mode, when a mobile station seizes control of the WM under PCF, it can transmit multiple MAC frames consecutively as long as the whole transmission time does not exceed the transmission opportunity (TXOP) limit, which is determined and announced by the AP. For this purpose, we allow each station to maintain another variable called Qsize to reflect the size of its queue. It has been shown in [26] that by maintaining Qsize at each station, number of dropped

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packets in the system is reduced, and hence the system throughput increases. 3.2. System model In our model, we consider a single infrastructure basic service set (BSS) with one AP (access point) and n mobile stations as shown in Fig. 4. The AP is connected to a DS (distribution system) through which it can communicate with other APs. Each mobile station exchanges real-time traffic (audio and video) as well as simple data (non-real-time traffic) with the access point in both directions (mobile station-AP and AP-mobile station) using the PCF. We assume that each mobile station has its own local scheduler by which it can sort its packets according to their Dmax values in such a way the HOL (head of line) packet at each station is the one with the lowest Dmax value. 3.3. Problem formulation Given the system model described above, our objective is to propose an extension to the PCF of IEEE 802.11 such that mobile stations are polled in order, based on the Dmax values of HOL packets at each station. Clearly, this is a hierarchical scheduling problem, in which, each mobile station schedules its own packets locally, and the AP

Access Point(AP)

Distribution System

MH

MH

MH

MH

Queues with elastic data and Multimedia Data

Fig. 4. System Model of IEEE 802.11 PCF mode.

schedules the stations registered in its polling list. The basic idea of our scheme is shown in Fig. 4. An AP adds all mobile stations into its polling list at the beginning of each CFP. In order to make 802.11 MAC protocol a more efficient demand assignment protocol to support wireless fair queuing policies, we suggest a new polling scheme with two phases as shown in Fig. 5(a). 1. Round-robin polling phase (Fig. 5(b)). At the beginning of a CFP the AP performs a single polling pass in a round-robin fashion. During this phase, the AP collects priority information about the HOL (head of line) packet at each station. The AP polls mobile stations one by one and in sequential order. Each station, in response, sends time-out value information about its HOL packet, if any. To prevent polling empty nodes, the AP uses a history scheme where it removes in each polling round all the stations that had null packets in the previous two pollings for this CFP period. This information is then used by the access point to determine the initial polling order in the next phase. 2. Priority-based polling phase (Fig. 5(c)). This is a dynamic polling scheme in which the polling order keeps changing based on the priority information received from the mobile stations. Initially, the AP schedule station polling order according to the priority information gathered during the round-robin phase. Each AP-mobile station transaction is performed according to the following steps: (a) The AP sends CF-Poll to the station with the highest priority. (b) The polled station transmit its pending packet, piggybacked with the next HOL packet time-out value as shown in Fig. 5(c). An acknowledgment to the previous frame can also be included to reduce the transmission overhead. (c) The AP updates its schedule according to the priority information it receives about the next HOL packet of the polled station. These steps are repeated until the end of the CFP. If a host has more packets to send, we relay

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273

Fig. 5. The proposed model (a) modification of CFP, (b) first phase timing, (c) second phase timing.

the information about the next packet as follows. We piggyback the information about the next packet, i.e., Dmax , in the frame transmitted from the MH by making use of the more data field of the frame control of 802.11e (see Fig. 6). If the polled station sends a frame with the more data field set to 0, the access point drops that station from the polling list. This is usually used by the AP to indicate to a station in power-save mode that more frames are buffered for the station at the HC. In our scheme we use the more data field to indicate that the specific flow at this mobile host has another packet with the specified Dmax value and needs to be polled during the next round. The time-out value for non-real-time traffic will be decremented over time, and at some point, it will fall within the range of Dmax values of the real-time traffic. When this happens, such non-real-time traffic will be treated as real-time traffic and its

delay requirement start to be reflected at the AP. A mobile host can have elastic data packets as well as multimedia packets in its queue and, therefore, packets will have different Dmax values. To illustrate the operation of the proposed QoS scheduling scheme, consider the following example.

Example. Consider a single BSS consisting of one AP and four multimedia mobile stations. Each mobile station maintains a list of packets sorted according to their maximum delay values as shown in Table 2. • Initially the AP polls the mobile stations with round-robin (i.e., the polling order will be 1; 2; 3; 4). Throughout this phase, the AP collects information about the HOL packet at each station.

Fig. 6. IEEE 802.11e control frame format.

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Table 2 Four mobile hosts with different Dmax values for packets Packet no

MH1

MH2

MH3

MH4

1 2 3 4

3 5 14 15

5 8 11 16

2 4 12 13

4 5 10 12

• The priority-based polling phase starts by polling station 3 (since it has the highest priority). The polling order will be 3; 1; 4; 2. • Station 3 transmits packet 1 and the time-out value of the next packet (i.e., 4). • The AP updates its polling order to become 1; 4; 3; 2. • Station 1 transmits packet 1 and the maximum delay value of the next packet (i.e., 5). • The AP updates its polling order to become 4; 3; 2; 1. • Station 4 transmits packet 1 and the maximum delay value of the next packet (i.e., 5). • The AP updates its polling order to become 3; 2; 1; 4. • Station 2 transmits packet 1 and the maximum delay value of the next packet (i.e., 8). 10. The AP updates its polling order to become 1; 4; 3; 2. This operation continues in the same fashion until all the packets are transmitted. So far, EPCF supports QoS in single BSS where the enhanced PCF is implemented in the AP. The multihop ad hoc mode of 802.11 encounters a situation where it is needed to support end-to-end QoS guarantees over multiple wireless hops. In ad hoc mode, the notion of AP does not exist and all mobile hosts are equivalent and can play the role of AP in the network. Moreover, mobile nodes are free to move resulting in a continually varying network topology. Hence, providing end-to-end performance guarantees for packets traversing multiple wireless hops requires the cooperation of all mobile hosts on the path between the source and the destination hosts [17,18]. The QoS perceived in this case is the same as the QoS obtained from the weakest link in the way from the source to the destination [12]. In the next section, we extend the proposed scheme (EPCF) to work in a

multihop ad hoc environment. For this purpose, we devise a novel scheme for converting the varying physical network topology of the multihop 802.11 WLAN into a fixed virtual topology where our scheme can provide end-to-end guarantees in a simple manner.

4. End-to-end QoS support in multihop wireless networks In the previous section, we showed how EPCF supports QoS in single hop infrastructured networks. In this section, we extend the proposed scheme in order to provide end-to-end QoS performance guarantees in multihop wireless ad hoc networks that employ 802.11. Multihop wireless ad hoc networks are distinguished from other communication networks by many features such as absence of a fixed infrastructure, dynamic topology, wireless multihop communication, and strict resource limitations (e.g., limited bandwidth and energy resources). As such, QoS guarantees, e.g., end-to-end bandwidth and maximum delay are hard to satisfy [13]. Bandwidth is limited due to the time varying characteristics of the wireless channel, which directly affects the throughput performance of such networks. The ephemeral node associations cause frequent route (service) disruptions, which may result in QoS guarantees violations for the ongoing as well as admitted sessions. Recently, power-aware routing received an extensive research and hence can be considered as one type of quality routing [20,21]. In the multihop ad hoc mode of 802.11, the notion of AP does not exist, i.e., there is no fixed communication infrastructure and all mobile hosts are equivalent and can play the role of AP in the network. Moreover, mobile nodes are free to move resulting in a variable network topology. Hence, providing end-to-end performance guarantees for packets traversing multiple wireless hops requires the cooperation of all mobile hosts on the path between the source and the destination hosts [10,18]. Thus, dynamic network topology of these networks may render any attempt to provide QoS guarantees. Consequently, providing timely delivery between a pair of mobile nodes in this multi-

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hop infrastructureless environment is more challenging than the single hop case. To be able to provide QoS in these networks, we need a way to map their dynamic topologies onto a fixed and stable architecture. Only then, the network may support QoS guarantees in an easy and efficient manner. In the next section, we present a simple scheme that maps the network topology from the dynamic domain onto the fixed domain. The proposed scheme forms a fixed wireless virtual backbone on top of the physical topology. The fixed virtual backbone consists of mobile nodes that act as temporary access points and these nodes are replaced periodically to avoid single node failure problem and provide fairness among nodes in terms of how much time each node act as an AP. The set of selected mobile nodes are called the virtual access points (VAPs). 4.1. Creating the fixed virtual backbone A wireless ad hoc network (WANs) is modelled as a communication graph G ¼ ðN ; LÞ, where N is the finite set of the mobile nodes and L is the set of undirected links connecting them. Each mobile node ni , i 2 N has a set of neighbors NBi . For the sake of simplicity and a functional MAC protocol, we assume all mobile nodes to have identical maximum transmission (radio) range r. In order to be able to use the proposed scheme EPCF in WANs, we map the network physical topology onto a fixed virtual topology. To create the fixed virtual topology, we divide the network area into disjoint, adjacent, fixed-size, and hexagon-shaped zones (fixed clusters) as shown in Fig. 7. We select the clusters to be hexagons because they provide the optimal zone coverage (has larger area) among other regular shapes. pffiffiffi Note that the area of a regular hexagon is 32 3x2 where x is the hexagon side length. The side x of each pffiffilength ffi hexagon is selected as x 6 r= 3 to allow direct communication between two VAPs in two neighboring hexagons. Each zone (i.e., hexagon) has a unique address (ZoneID) which can be the ordered pair consisting of the zone row and column numbers, respectively. Each mobile node is a member of one of those zones and its membership is

275

Virtual Access Point (VAP) Normal Mobile Host

Fig. 7. Network partitioning with virtual access points (VAPs) in neighboring zones communicate directly.

determined based on its location in the network area. The role of VAP is a temporary role, which changes dynamically as the topology or other factors affecting it change. In general, finding the minimal set of VAPs in an arbitrary connected graph is an NP-Complete problem. However, our clustering approach uses cluster shapes that approximate optimal cluster coverage, hence we expect the cardinality of VAPs to be close to optimal [11]. A VAP role is changed when one of the following cases occurs. First, the current VAP fails (e.g., battery is out of service). Second, the current VAP leaves its current hexagon area and enters another area. Third, the current election period, which is a system design parameter, comes to an end. Finally, a VAP may request to be replaced by another VAP when its load becomes heavy or it needs to move out of this area. In all these cases, the VAP will be replaced with the next eligible node in the cluster. 5 When a zone is created, a simple algorithm is performed to select the appropriate mobile node to act as VAP. The theme of the selection algorithm is to select the most eligible node that will serve as VAP in the respected zone. The eligibility of a node to become a VAP depends on different parameters such as the node remaining battery energy, node speed, and node location. An eligibility

5

We use the terms zone and cluster interchangeably.

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factor of a node i, called EFi , to serve as a VAP at time t is calculated as

Transmission without RTS/CTS

DIFS

Data SIFS

EFi ðtÞ ¼ a1 evi ðtÞ þ a2 ðeIi ðtÞ Þ þ a3 Bi ðtÞ

ACK DIFS

þ a4 ð1  Ei ðtÞÞ;

Contention Window

(a)

where vi ðtÞ is the mobile node average speed at time t, and Ii ðtÞ is the number of times the node assumed the role of a VAP till time t, Bi ðtÞ is the remaining battery energy in node i at time t, Ei ðtÞ is the Euclidian distance of node i with respect to the zone center calculated at time t, and a1 ; a2 ; a3 ; a4 are weighting factors that reflect the importance of each parameter 0 6 ai 6 1, i ¼ 1; . . . ; 4. The node that has the highest value of EF will elect itself as the VAP in that zone. After creating the wireless virtual backbone, the proposed QoS mechanism, EPCF, is implemented inside each zone at the respected VAP, which assumes the function of the normal AP in infrastructured wireless networks. Our proposed protocol is able to provide a minimum throughput and delay bounds for each flow, as will be shown in the simulation results. Besides, it seeks to achieve fair and maximum allocation of the shared wireless channel bandwidth by employing the distributed implementation of EPCF. However, these two criteria can potentially be in conflict when a single logical channel is shared among multiple contending flows and spatial reuse of the channel bandwidth may not be sometimes possible. Therefore, the EPCF centralized scheme inside each zone (a zone is equivalent to one BSS) is implemented. The detailed operation of the EPCF mechanism in the multihop environment is described next. Each VAP node maintains a local schedule. To prevent collision, we assume that data transmission will be preceded by a control handshake (i.e., four-way handshake) as shown in Fig. 8 to inform the neighborhood VAP nodes about the intention of the sender to transmit a packet. We also assume that there is a routing agent that finds a path from the source to the destination nodes and this path is used to route the packets through the set of VAPs. The local schedule is updated after each transmission heard from other neighboring stations. We also assume that VAPs maintain complete

NAV

DIFS SIFS

RTS

Data SIFS

SIFS CTS

ACK NAV(RTS)

Transmission with CTS/RTS

(b)

NAV (CTS) NAV( data)

Fig. 8. Basic access mechanism in IEEE 802.11: (a) 2-way handshake, (b) 4-way handshake.

knowledge of the virtual network topology by the use of a link state algorithm as well as maintaining the flow information at the scheduler. The operation of the extended scheme proceeds as follows. The source mobile host sends an RTS signal with information about the HOL packet requirements to the neighboring VAPs. Upon hearing the RTS, the neighboring nodes will defer their transmissions. The intended VAP receiver (neighbor VAP) responds with a CTS and allows the sender to send the packet without collisions. Notice that the elected VAP assumes the role of an access point (AP) in an infrastructured wireless networks and can be anywhere in the hexagon. Channel communication management in different zones can be controlled using code division multiple access (CDMA). The assignments of codes to zones is selected such that neighboring zones use different spreading codes in order to reduce interference and to enhance spatial reuse of channels. It should be noted that within each zone, the MAC (medium access control) layer is implemented using IEEE 802.11 MAC protocol such that EPCF can be exploited.

5. Simulation results In this section we present the results of performance evaluation of EPCF through simulations

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the ratio between the number of packets generated by the application layer sources and the number of packets received by the destinations. Packet delivery ratio is an expressive metric as it describes the loss rate that will be seen by the transport protocols, which in turn affects the maximum throughput that the network can support. The average end-to-end packet delay is a meaningful metric because of the need to support the QoS guarantees for the multimedia (audio/video) traffic. Service differentiation in a mobile host refers to the ability of the QoS scheme to differentiate between different applications requirements running at the same mobile host. This is also important as PCF and HCF scheduling scheme polls the stations in the order of association IDs (AIDs), i.e., service is performed per-station and not perapplication although the new 802.11e distinguishes between different application requirements but put the burden of this extra management on the mobile node itself. Fig. 9 shows the maximum delay for the bursty traffic. Note that HCF achieves the lowest delay and our proposed scheme was able to perform comparably well against HCF. The 802.11e EDCA also performs well and all schemes show a comparable performance for the multimedia traffic. The maximum throughput obtained is shown in Fig. 10. EPCF performs better than EDCA but marginally less than HCF even at higher offered loads. The difference between the two schemes stems from the fact that EPCF operates only in the CFP while HCF works in both CFP and CP. To further solidify this point, we measured the

14 12 Maximum Delay (msec)

and compare it with other schemes related to 802.11 and in particular the newly proposed HCF. We used the NS-2 simulator [29] to simulate the various schemes. For the centralized scheme, we set up a network consisting of one BSS with four nodes and an extra node as an access point (AP) (as in Fig. 4). We generate three types of traffic from all nodes to the AP (bursty data (e.g., HTTP), audio, and video). Link data rate is fixed at 11 Mbps. Each bursty data source generates 100 Kbps. The audio source model generates 60-byte messages periodically with an interval of 20 ms resulting in bit rate of 24 Kbps. For the video source model we have used an output bit rate of 256 Kbps (used for video conferencing traffic). We vary the offered load by varying the number of traffic streams and the inter-arrival time of those traffic streams according to a Poisson distribution. For the multihop case, the setup of the experiment was as follows. The network area is 500 · 500 m2 . The number of mobile nodes is 20. The control frame size is set to 100 ms. Each node can transmit to a range of 100 m. Nodes are allowed to move according to the waypoint mobility model, although we also experimented with other mobility models as shown later in this section, where a node selects a destination and starts moving towards that destination at a speed that is uniformly distributed between 5 and 20 m/s. When a mobile node reaches the destination, it pauses for some time before selecting a new destination. Note that pause time of zero means constant mobility. The 802.11e EDCA AIFS (data) is set to 60 ls + 10 · aSlotTime. For HCF, dot11DefaultCPTXOPLimit is set to 5040 ls, the dot11CAPMax 5040 ls, HCF CAP timer update time 5120 ls, dot11CAPRate is set to 20 ls. The wireless medium bit error rate (BER) at the 11 Mbps transmission rate is set to BER11 ¼ 1.3E)5. PCF capable stations have the maximum CFP set as 10ms in each superframe which has a length of 30 ms. The maximum duration of a CAP is configured as 5040 ls. We evaluate the performance of the proposed protocol based on the following metrics: (a) packet delivery ratio, (b) average end-to-end packet delay, (c) service differentiation among flows in the same mobile host. We define the packet delivery ratio as

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4

EPCF

2 0 0.1

0.2

0.3

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0.7

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Fig. 9. Maximum delay versus the percentage offered load.

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Throughput (Kbps)

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1400 E DCF HCF

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EP CF 800 600 400

1 0.98 0.96 0.94 0.92 0.9 0.88 0.86 0.84 0.82

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0

20

200 0 0.1

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0.3

0.4 0.5 0.6 Offered Load (%)

0.7

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6

It should be pointed out that the authors have experimented with several simulation settings and across a range of conditions. All scenarios have resulted in similar trends and conclusions, i.e., varying number of nodes in BSS, varying traffic loads resulted in the same trends as in the reported results. However, we have limited ourselves to the scenarios in this paper since they suffice to illustrate our point.

60 80 Pause time (seconds)

100

120

Fig. 11. The effect of node free mobility on the network packet delivery ratio for high and low mobility.

Average end-to-end delay (ms)

Fig. 10. Network throughput versus the percentage offered load.

cumulative throughput of each scheme for the whole simulation period. The results are shown in Fig. 14. As shown in the Figure, EPCF performs better than the legacy PCF and its performance is comparable to HCF. Moreover, both HCF and EPCF perform better than PCF under the tested conditions. It is worth mentioning that the simulation results were averaged over ten experiments. 6 For the multihop setting, we study the effect of node mobility on the network throughput and also the effect of the path length (number of hops) on the network end-to-end delay achieved by the proposed scheme. Packet Delivery ratio of the multihop EPCF is shown in Fig. 11 for low mobility (speed is 5 m/s) and high node mobility (20 m/s) both employing the waypoint mobility model used in ns-2. As shown in the Figure, the decreases when the nodes increase their movement. The effect of the path length on the network delay is shown in Fig. 12. It is obvious that an increase in path length increases the delay of the packets as they traverse multiple queues and experience various delays at different nodes, and (3) The probabilistic random walk model (PRWM) [19]. For

40

80 70 60 50 40 Multihop case

30 20 10 0 0

1

2

3 4 5 path length (# of hops)

6

7

8

9

Fig. 12. Network end-to-end delay when the route length changes.

each model, we find the network packet delivery ratio. The results in Fig. 9 show that the probabilistic random walk model produces the most realistic motion and thus produces the best results in terms of the packet delivery ratio. We also studied the effect of nodes mobility patterns on the system throughput. To be more specific, we considered more realistic mobility models and studied their effect on the system throughput. Fig. 13 shows the effect of three mobility models on the system throughput for different node speeds. The three models are completely random model (CRM) where nodes movement are completely random, waypoint mobility model (WPM) used in ns-2 and described earlier, and the more realistic probabilistic random walk probability model (PRWM) [19]. As expected, under PRWM the system was able to deliver more packets than the other two mobility models since the mobility patterns in this model are closer to a realistic scenario. Note that random node movement may cause network partitions and hence frequent route breakage. As a result, packets

J.N. Al-Karaki, J.M. Chang / Ad Hoc Networks 2 (2004) 265–281 1.2

Packet delivery ratio

1 0.8 0.6 0.4

PRWM

0.2

WPM CRM

0 0

20

40

60 80 Pause Time (sec)

100

120

Fig. 13. Effect of mobility model on the system throughput using EPCF.

Fig. 14. Maximum throughput of the three schemes.

are being dropped or missing their required QoS guarantees more often.

We now show how EPCF can provide the same, or even better, performance than HCF when the a mobile node traffic is coming from different application types with different requirements i.e., we address the per-host priority model issue in 802.11e. Recall that 802.11e deals with each host as one single entity i.e., it does not differentiate between different application requirements running at the same host. In this experiment, we generated three types of traffic (constant bit rate (CBR), real-time variable bit rate (rt-VBR) and non-real-time VBR (nrt-VBR)) that correspond to various types of applications running at the same host. The VBR traffic generator implemented for this purpose is based on the two-state Markov model shown, where the traffic generator is sending packets at the peak cell rate (PCR) in state 1, and at a reduced rate (RR) in state 0. The number of successfully transmitted packets of each traffic is counted to find the delivery ratio of each type of traffic. Fig. 15 shows the packet delivery ratio of the three traffic types for both HCF and EPCF. It is apparent that HCF was not able to distinguish between the three types of traffic and therefore the packet delivery ratios of rt-VBR and nrt-VBR were penalized. On the contrary, EPCF was able to provide higher packet delivery ratios of rt-VBR and nrt-VBR than CBR, as promised by the scheduler and by the network.

1.2

Packet Delivery Ratio

1

0.8

0.6 rt-VBR (EPCF) nrt-VBR(EPCF) CBR( EPCF) rt-VBR (HCF) nrt-VBR(HCF) CBR( HCF)

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0 1

3

5

7

9 11 13 15 17 19

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21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

number of packets served (1packet=0.001seconds)

Fig. 15. Service differentiation in HCF and EPCF for different traffic types.

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6. Conclusions This paper has presented a performance evaluation of an enhanced version of the 802.11 PCF called EPCF and compared its performance to the 802.11e QoS enhancements in HCF. The proposed scheme is implemented in the PC in the single-hop case and in the elected VAPs in the multihop case, where we discussed the advantages and disadvantages in each case. Simulation results clearly showed that 802.11e improves QoS support of 802.11 networks when both EDCA and HCF are used. Also, our proposed scheme, EPCF, shows an enhancement in the QoS performance when compared to 802.11e HCF. However, the new HCF in the 802.11e has some performance issues which can degrade the quality of service provided by networks that employ HCF. We addressed these issues and we have provided a simple solution for some of the issues of HCF, particularly pertaining to the complex function needed to support QoS at the level of per-host priority model. Although both HCF and EPCF performs comparably, our proposed scheme is much simpler and easy to implement since it is based on the simple function of PCF in 802.11. Currently, we are developing an analytical model to support the simulation results of the proposed scheme, EPCF, reported in this paper. The multihop version of our scheme is a promising approach since it converts the physical network topology into a fixed topology where complex management algorithms to maintain network states are not necessary.

Acknowledgements The Authors would like to thank the anonymous reviewers for their valuable comments which helped enhance the quality of presentation of this paper.

References [1] IEEE Std 802.11-1997, Wireless Local Area Networks Standard, November 1997.

[2] IEEE Std WG 802.11e/D4.4-2003, Wireless medium access control (MAC) and physical layer (PHY) specifications: Medium access control (MAC) enhancements for quality of service (QoS), IEEE 802.11e, June 2003. [3] I. Mahadevan, K.M. Sivalingham, Quality of service in wireless networks based on differentiated services architecture, in: Proceedings of the Eighth International Conference on Computer Communications and Networks, 1999, pp. 548–553. [4] Y. Hong, G.C. Walsh, L.G. Bushnell, Real-time mixedtraffic wireless networks, IEEE Transactions on Industrial Electronics 48 (5) (2001) 883–890. [5] A. Veres, A.T. Campbell, M. Barry, L.-H. Sun, Supporting service differentiation in wireless packet networks using distributed control, IEEE Journal on Selected Areas in Communications 19 (10) (2001) 2081–2093. [6] J. Yeh, C. Chen, Support of multimedia services with the IEEE 802-11 MAC protocol, IEEE International Conference on Communications 2002, ICC 2002, vol. 1, 2002, pp. 600–604. [7] T. Suzuki, S. Tasaka, Performance evaluation of prioritybased multimedia transmission with the PCF in an IEEE 802.11 standard wireless LAN, in: 12th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications 2001, vol. 2, September/October 2001, pp. 70– 77. [8] A. Lindgren, A. Almquist, O. Schelen, Evaluation of quality of service schemes for IEEE 802.11 wireless LANs Local Computer Networks, 2001, in: Proceedings of 26th Annual IEEE Conference on LCN 2001, 2001, pp. 348– 351. [9] S. Mangold, S. Choi, P. May, O. Klein, G. Hiertz, L. Stibor, IEEE 802.11e wireless LAN for QoS, European Wireless Conference, 2002. [10] D.D. Perkin, H.D. Hughes, A survey on quality-of-service support for mobile ad hoc network, Wireless Communications and Mobile Computing 2 (2002) 503–513. [11] J.N. Al-Karaki, Modeling of stability and reliability of wireless ad hoc networks, in: Proceedings of the International Conference on Performance Modelling and Evaluation of Heterogeneous Networks (HET-NETs ’03), Ilkley, West Yorkshire, UK, 2003. [12] Z. Cai, M. Lu, X. Wang, Channel access-based selforganized clustering in ad hoc networks, IEEE Transactions on Mobile Computing 2 (2) (2003) 102–113. [13] G. Ahn, A.T. Campbell, A. Veres, S. Li-Hsiang, Supporting service differentiation for real-time and best-effort traffic in stateless wireless ad hoc networks (SWAN), IEEE Transactions on Mobile Computing 1 (3) (2002) 192–207. [14] M. Hoeben, M. Wentink, Enhanced D-QoS through virtual DCF, IEEE 802.11-00/351, October 2000. [15] S. Choi, J. del Prado, A. Grag, M. Hoeben, S. Shankar, M. Wentink, Multiple frame exchange during EDCF TCOP, IEEE 802.11-01/566r3, January 2002. [16] M. Benveniste, G. Chesson, M. Hoeben, A. Singla, H. Teunissen, M. Wentink, EDCF proposed draft text, IEEE working document 802.11-01/131r1, March 2001.

J.N. Al-Karaki, J.M. Chang / Ad Hoc Networks 2 (2004) 265–281 [17] J.L. Sobrinho, A.S. Krishnakumar, Quality-of-service in ad hoc carrier sense multiple access networks, IEEE Journal on Selected Areas in Communications 17 (8) (1999) 1353–1368. [18] A. Lindgren, A. Almquist, O. Schelen, Quality of service schemes for IEEE 802.11––a simulation study, in: Proceedings of the Ninth International Workshop on Quality of Service (IWQoS’2001), June 2001. [19] T. Camp, J. Boleng, V. Davies, A survey of mobility models for ad hoc network research, Wireless Communications and Mobile Computing 2 (5) (2002) 483–502 (Special Issue on Mobile Ad Hoc Networking: Research, Trends and Applications). [20] E. Gelenbe, R. Lent, A power aware routing algorithm, SPECTS’03, Summer Simulation Multiconference, Society for Computer Simulation, Montreal, Canada, 20–24 July 2003. [21] J. Wu, F. Dai, M. Gao, I. Stojmenovic, On calculating power-aware connected dominating set for efficient routing in ad hoc wireless networks, Journal of Communications and Networks 5 (2) (2002) 169–178. [22] E. Gelenbe, R. Lent, A. Montuori, Z. Xu, Cognitive packet networks: QoS and performance, in: Proceedings of IEEE MASCOTS Conference, Fort Worth, TX, 2002. [23] E. Gelenbe, M. Gellman, P. Su, Using loss and delay as QoS goals in cognitive packet networks, SPECTS’03, Summer Simulation Multiconference, Society for Computer Simulation, Montreal, Canada, 20–24 July 2003. [24] E. Gelenbe, Self-aware networks and quality of service, in: Proceedings of IEEE Symposium on Computer Communications’03 (ISCC’03), June 29–July 3, 2003. [25] S. Choi, J. del Prado, A. Garg, M. Hoeben, S. Mangold, S. Shankar, M. Wentink, Multiple frame exchanges during EDCF TXOP, IEEE 802.11-01/566r3, January 2002. [26] J.N. Al-Karaki, M.J. Chang, A simple distributed access control scheme for supporting QoS in IEEE 802.11 Wireless LANs, in: Proceedings of IEEE Wireless Communications and Networking Conference (WCNC 2004), Atlanta, GA, USA, 21–25 March 2004. [27] X. Xiao, L.M. Ni, Internet QoS: A big picture, IEEE Network 13 (2) (1999) 8–18. [28] Z. Wang, Internet QoS: Architectures and Mechanisms for Quality of Service, The Morgan Kaufmann Series in Networking, Morgan Kaufmann, Los Altos, CA, 2001.

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[29] NS-2 Manual, Available from . Jamal N. Al-Karaki received the B.Sc. and M.Sc. degrees in electrical/computer engineering from Jordan University of Science and Technology, Jordan, and the Ph.D. degree in computer engineering from Iowa State University, USA in 1993, 1995 and 2004, respectively. He has worked at many institutions for the period 1995– 2001. In 2004, he received the Research Excellence Award from Iowa State. His research interests include Wireless networks, Ad hoc networks, Sensor networks, and Internet QoS. He has published more than 20 technical papers in these areas. J. Morris Chang received the B.S. degree in electrical engineering from Tatung Institute of Technology, Taiwan, the M.S. degree in electrical engineering and the Ph.D. degree in computer engineering from North Carolina State University in 1983, 1986 and 1993, respectively. In 2001, He joined the Department of Electrical and Computer Engineering at Iowa State University where he is currently an Associate Professor. His industrial experience includes positions at Texas Instruments, Microelectronics Center of North Carolina, and AT&T Bell Laboratories. He was on the faculty of the Department of Electrical Engineering at Rochester Institute of Technology, and the Department of Computer Science at Illinois Institute of Technology (IIT). In 1999, he received the IIT University Excellence in Teaching Award. His research interests include Wireless Networks, Object-oriented Systems, Computer Architecture, and VLSI design and testing. He has published more than 90 technical papers in these areas. His current research projects are supported by three NSF grants (including two ITR awards). He served as the Secretary and Treasurer in 1995 and Vendor Liaison Chair in 1996 for the International ASIC Conference. He was the Conference Chair for the 17th International Conference on Advanced Science and Technology (1CAST 2001), Chicago, Illinois, USA. He was on the program committee of ACM SIGPLAN 2004 Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES’04). He is on the editorial boards of Journal of Microprocessors and Microsystems and IEEE IT Professional. He is a senior member of IEEE.