Dynamic Admission Control in IEEE e EDCA-based Wireless Home Network

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2 This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE CCNC 2006 proceedings. Dynamic Admission Control in IEEE e EDCA-based Wireless Home Network Hayoung Yoon, JongWon Kim 0, and DongYun Shin Networked Media Lab., Dept. of Information and Communications, Gwangju Institute of Science and Technology (GIST), Gwangju, , Korea, {hyyoon, Device Solution Group, Digital Solution Center, SAMSUNG ELECTRONICS, Seoul, , Korea, Abstract In this paper, we introduce a dynamic admission control (DAC) to protect and maintain QoS-demanding traffic streams in IEEE e enhanced distributed channel access (EDCA) based wireless home network. The proposed DAC dynamically adjusts to achieve high bandwidth utilization while maintaining the desired QoS in a deteriorative channel condition. The ITU-T H scalable video codec and NS-2-based simulation results show that the proposed DAC can efficiently balance the tradeoff between resource utilization and QoS guarantee in unstable wireless home network. I. INTRODUCTION Wireless LANs (WLANs) - especially IEEE [1] based - are becoming popular. The initial shape of WLANs is wireless infrastructure for the Internet connection in the office environment and it is recently spread over more larger area (e.g., hot-spot zones in the airport, hotel, and building). Nowadays many electronic appliance makers are attracted by the ever spreading WLAN infrastructures and trying to make their products to be end-system of WLAN. Especially, this trend is remarkable in the audio and visual (AV) system parts and one of the representative application is wireless home network that combines several AV devices [2], [3]. In this home networks, WLANs are begun to deliver more bandwidthintensive and delay-stringent media contents such as streaming video and interactive voice. However, these QoS demanding service cannot be appropriately serviced due to the hostile wireless channel characteristics such as scarce bandwidth, highly fluctuating delay, random/burst losses, and contention for wireless channel resources. To support QoS required service for WLAN, IEEE e [4] has been standardizing a hybrid coordination function (HCF). The HCF provides two channel access schemes; the enhanced distributed channel access (EDCA) and a HCF controlled channel access (HCCA). The EDCA is an extension of conventional distributed coordination function (DCF). It provides prioritized QoS services which classifies all the traffics destined medium access control (MAC) layer to multiple access categories (ACs) and it differentiate the chance to get a transmission opportunity (TXOP) using unequal channel access parameters. The EDCA is a fundamental and mandatory channel access mechanism of the IEEE e while the HCCA is optional and provides parameterized QoS service. 0 Corresponding author: JongWon Kim (jongwon@netmedia.gist.ac.kr) The HCCA needs centralized and polling and scheduling algorithms to allocate the TXOP and its duration. In this paper, we only consider the EDCA as a channel access scheme, therefore all of our represented algorithms are only for the EDCA. In a fully shared medium like wireless channel in WLAN, it is necessary to achieve QoS requirements that not only performs service differentiation mechanism but also admission control. So, the IEEE e defines admission control option for the EDCA. The scope of that standard for admission control is heavily focussing on its negotiation procedure, traffic specification (TSPEC) format, and basic roles of non-ap QoS stations (QSTAs) and QoS access point (QAP) such as admission requester and granter. This limited definition is due to implementation dependent parameters such as scheduler, available channel capacity, link conditions, and retransmission limits. These parameters are highly affecting to decide admission. In this paper, we introduce the dynamic admission control (DAC) algorithm for the EDCA-based wireless home networks. The proposed DAC includes an efficient rearrangements for wireless channel quality variation in distributed way. The proposed DAC is designed as decoupled algorithm from a channel capacity acquisition scheme. Therefore, the proposed DAC can cooperate with any kinds of WLAN capacity acquisition schemes [5]. In the further of this paper, we assume that the QAP can always be aware of the channel capacity in the current WLAN configuration. The remaining parts of this paper are organized as follows. The specification of IEEE e EDCA and its admission control in draft will be summarized in the Section II. The link adaptation schemes in WLANs will be introduced in the Section III. Section IV provides the detailed explanation of the proposed DAC. It is then followed by performance evaluation based on network simulation in Section V. Finally, we conclude this paper in Section VI. II. IEEE E EDCA AND ADMISSION CONTROLS IEEE e EDCA [4] is developed to differentiate traffic streams on the station and in the WLAN. The main idea of the EDCA is to apply different waiting time to get TXOP and limit of TXOP among traffics which is composed of several different priorities. The higher the priority of a packet, the shorter the /06/$ IEEE. 55

3 backoff time and the longer the time duration for multiple packets sending. Also, it defines a policy to arrange the inner station collision (in other words, virtual collision) of packets having different priorities. When inner collision occurs, the packet from the higher-priority AC is chosen to be transmitted and other packets behave as if channel collision occurring. If the WLAN administrators need to make admission control enabled environment, they should consider which ACs require admission control. The IEEE e recommends admission control for the higher two ACs among the four (i.e., AC VO, AC VI, AC BK, and AC BE in decreasing order). It is identified whether certain ACs need admission control or not through admission control mandatory (ACM) subfields in the EDCA parameter set element that carries minimum contention window (CWmin), CWmax, arbitration inter frame space (AIFS), and TXOP limit. This information is delivered with beacon frames to non-ap QSTAs from the QAP. An add traffic stream (ADDTS) request message shall be transmitted by a non-ap QSTA to the hybrid coordinator (HC) in the QAP in order to request admission of traffic in any direction (up, down, and bidirectional links). When non-ap QSTAs need to transmit or receive such traffic and the corresponding AC s ACM equals to 1, they have to negotiate with the HC in the QAP to get admission before actual data transmission. Otherwise, they can not send or receive in that AC. If the AD- DTS response indicates that the admission request is denied, such traffic is transmitted or received in lower AC which does not require admission control. The ADDTS request message carries the mean data-rate and packet size information received from upper layer and ADDTS response gives corresponding MediumTime to non-ap QSTA if the HC grants the request. This time means maximum allowed transmission or receive time per beacon interval including overheads for such traffic demanding admission. The QAP and non-ap QSTA maintain used time for transmission and if it reaches its limit, the excessive packets for the corresponding flow are mapped to another AC which does not require admission control so that protect QoS of others. Xiao et al. [6] have suggested distributed admission control algorithm for the EDCA. Their algorithm can work in fully distributed method and effectively protect QoS required traffic and limit the best-effort traffics. The main principle of their algorithm is available budget-based resource seizing and the EDCA parameter set tuning to limit traffic which can be sent or received without admission negotiation. This paper, further, evolves the concept of distributed admission control to decide admission on station and to react against channel variation. III. WIRELESS LINK ADAPTATION In practical WLAN, physical layer (PHY) rate for packet transmission is not fixed. IEEE specifies multiple transmission rates that are achieved by different modulation techniques in the physical layer convergence procedure (PLCP) header of the PHY layer. One of the these physical bit rates is selected to achieve high throughput against channel quality variation. This technique is usually called link adaptation or rate adaptation, and it is widely used in commercial WLANs [7]. The change of PHY rate may increase the spent time for the single packet transmission and causes that the admitted MediumTime may early consumed before sending required data during that beacon interval. Therefore, it is required to control MediumTime effectively. Fig. 1. IV. DYNAMIC ADMISSION CONTROL ALGORITHM IN IEEE E EDCA-BASED WLAN WLAN Capacity QoS demanding or Best-effort traffics Capacity for each AC Channel Estimation DAC Decision and Adaptation Block diagram of DAC along with capacity estimation of WLAN. The upcoming IEEE e standard can contribute to provide QoS required service using the EDCA scheme, which can differentiate channel access chances according to the traffic class. However, such a differentiation scheme may not provide guaranteed QoS but differentiated QoS due to the contention-based nature. Besides, even though we can apply QoS provisioning strategies to the EDCA-based WLAN, unpredictable events in wireless channel can make it difficult to maintain overall QoS. Also, too much additional resource allocation or overhead to guarantee QoS may cause low utilization of network resource. In this section, we introduce a dynamic admission control (DAC) in IEEE e EDCAbased WLAN. The proposed DAC is mainly dealing with problems related to not only admission offering but also dynamic management of granted resource for QoS-demanding traffic flow in distributed ways. Fig. 1 shows the block diagram of the proposed DAC along with appropriate WLAN channel estimation strategy, which block is assumed in this paper as we mentioned. A. Link Adaptation Effects on MediumTime When user applications need to send or receive QoSdemanding traffic stream in admission control enabled IEEE e EDCA-based WLANs, they should receive MediumTime from the HC in the QAP. It is allowed time duration to transmit or receive packets over air medium during beacon interval. The QAP may use any algorithm to derive MediumTime, but IEEE e recommends procedure to calculate that may be used as: MediumTime = ρ pps MPDUExchangeTime, where pps = MeanDataRate/8 NominalMSDUSize, MPDUExchangeTime = λ + SIFS + duration(ack), (1) and λ = duration(rt S/CT S)+ NominalMSDUSize MinimumPHYRate. 56

4 Here, ρ ( 1) is called SurplusBandwidthAllowance and indicates over-the-air excess time or bandwidth for packet loss and retransmission. Eq. (1) shows how the admitted time can be derived using packet size and data-rate information of a requested traffic. The SurplusBandwidthAllowance is related to the number contending QSTAs and packet error probability (PER) in the QoS basic subset (QBSS). The SurplusBandwidthAllowance should be selected considering them and may be changed during transmitting admitted traffic stream. The MPDUExchange- Time is the required time to complete request-to-send/clearto-send (RTS/CTS) protection, single MAC service data unit (MSDU) transmission, and reception of corresponding acknowledgement over the air. MinimumPHYRate is intended to ensure that the TSPEC parameter values resulting from an admission control negotiation are sufficient to provide the required throughput for the traffic stream. To maintain the service quality in time varying channel conditions, there are two strategies. One is making overprovisioned condition using additional resource reservation: the MinimumPHYRate and SurplusBandwidthAllowance should be respectively chosen as small and as large as possible to cope peak-to-peak variation of channel status. This causes tradeoff between the resource utilization of WLAN and per-flow QoS fairness [9]. Another one is that selecting effective amount of resource at the signaling procedure and make adaptation according to channel variation. As Eq. (1) denoting, the amount of resource (i.e.,duration of MediumTime) can be adjusted depending with changes of SurplusBandwidthAllowance and MPDUExchangeTime. Let us consider the relationship between both two parameters under the given wireless channel conditions. To deliver a data frame over a wireless channel, the higher the PHY rates, the shorter the expected MPDUExchangeTime time will be lower, but the larger SurplusBandwidthAllowance and vice versa [7]. This relationship makes finding cost optimal size of resource as two dimensional optimization problem. However, if QSTAs can track the PHY rate which always inquire maximal throughput, that problem can be approximated as more simple network-adaptation problem due to we can set SurplusBandwidthAllowance to be fixed value. In the proposed DAC, the MediumTime is dynamically adjusted along with PHY rate changing in distributed way and balances the two conflicting objectives smoothly. B. Dynamic Admission Control Algorithm We assume that the QAP broadcasts beacon frames that include the EDCA parameter set and traffic load information in the QBSS, as defined in IEEE e. Another assumption is that, we focus to admission control only for QoS-demanding flows which are not highly burst in a moment but have service duration for more than several seconds. It is out of scope to regulate best-effort traffic below its limit. Several works have been proposed for best-effort rate control by other researchers [8]. One of them can be applied to the proposed admission control. In this paper, we assume that the best-effort traffics can not take up more than their thresholds in this admission control algorithm. The dynamic admission control (DAC) algorithm has two steps for admission request. The first step is a local admission control in non-ap QSTAs and the second one is an ADDTSrequest/response exchanging with the HC in the QAP. The non-ap QSTAs can calculate MediumTime by themselves and decide their admissions. For the local admission control, the QSTAs in the QBSS should share the information about currently usable resource, which can be expressed in time or. Let us define a global variable AAC, which specifies the amount of available admission capacity, which can be utilized for the next beacon interval. In our implementation, this AAC is calculated as: AAC = n ACM i=0 ( ARi n E[P ] T ACM s) i i=0 MediumTime i, (2) where n ACM, AR i, E[P], T i s, and MediumTime i indicate the number of ACs as admission control is mandatory, allocated resource for i th AC, average payload size, required time to transmit a packet successfully, and accumulated reserved time to transmit data packets belong to i th AC, respectively. Upon receiving periodic beacon frame, the non-ap QSTAs extract and update the AAC immediately. It can also be maintained by capturing ADDTS-response messages that bring TSPEC and results of admission process destined to other non- AP QSTAs. The procedure to update local AAC variable is defined in Fig. 2. UPDATE-AAC(MSG) 1 PacketType GETTYPEOFMESSAGE(MSG) 2 if PacketType = BEACON 3 then 4 ACC GETACC(MSG) 5 elseif PacketType = ADDTS-RESPONSE 6 then 7 ACC ACC GETMEDIUMTIME(MSG) 8 P GETSCHEDULEDADDTS() 9 if P NULL 10 then 11 Request GETMEDIUMTIME(P ) 12 if ACC Request 13 then return 14 else 15 ADDTS-DROP() 16 NOTIFYTOUPPERLAYER() Fig. 2. Procedure to update AAC from received beacon or captured ADDTSresponse including destined to others. In the proposed DAC algorithm, we develop an adaptation procedure to maintain the QoS of specific flow, when it experiences PHY rate changes. This procedure is shown in Fig. 3. When the PHY rate for certain QSTA is changing, it should check whether newly made one requires more transmission 57

5 MEDIUMTIME-ADAPTATION(PHY Rate, Current Time) 1 MediumTime GETMEDIUMTIME() 2 NewRequiredTime REQUIREDTIME(PHY Rate) 3 Last Time GETLASTADAPTATIONTIME() 4 Elapse T Current Time Last T 5 Excess NewRequiredTime MediumTime 6 if Excess>α 7 then 8 if Elapse T<ExcessInterval 9 then return 10 else if ACC Excess 11 then ADDTS-SCHEDULE(Excess) 12 elseif ACC < Excess 13 then REGULATE-TRAFFIC(Excess) 14 elseif Excess < α 15 then 16 if Elapse T<ReleaseInterval 17 then DELTS-SCHEDULE(Excess) Fig. 3. Procedure for responding to PHY rate adaptation. time to meet the QoS of existing flows. If the change is invalid to satisfy current QoS requirement and excessive resource can be applicable, the non-ap QSTA schedules ADDTS-request to get additional time for data transmission (from line 5 to 11 in the Fig. 3 pseudo codes). When the channel condition gets better, the non-ap QSTA should release a selected portion of resource out if its resource pool including guard resource. Since frequent network-adaptations may spoil the stability of overall QBSS, the adaptation is handled with two intervals that control minimum timing gap between two consecutive adaptations. The line 13 in the Fig. 3 indicate that the required QoS can t be fulfilled due to there is no available resource in WLAN. To maintain video streaming service with moderate quality, the less important streams can be dropped to meet current MediumTime of the corresponding flow in the traffic regulation function [10]. REQUEST-ADMISSION(T SP EC, Address, AC) 1 ReqMediumT CALCULATEMEDIUMTIME(TSPEC) 2 N ewcapacity GETCAPACITY(Address, AC) 3 UsedTime GETUSEDTIME() 4 if NewCapacity β>usedtime+ ReqMediumT 5 then 6 ADDTS-RESPONSE(ReqMediumT ) 7 else 8 ADDTS-RESPONSE(0) Fig. 4. Procedure to decide admission in HC. The local admission decision of admission can help to reduce the processing overhead at the network and the QAP for request and response procedure when the bandwidth of QBSS is almost utilized. If local test allows to request admission, the ADDTS-request is scheduled to get the TXOP. When the HC receives this request, it has to consider that newly departing traffic may cause WLAN status change. Thus, the HC should recalculate the system capacity whenever it processes admission request. The algorithm described in Fig. 4 is performed when the HC receives the ADDTS-request frame from non-ap QSTAs. It calculates requested traffic stream s MediumTime through Eq. (1) and updates total available capacity for the QBSS on the supposition that this request would be permitted to get that time. The variable β, in line 4, indicates the portion of resource for the traffic in admission control mandatory ACs among available capacity and it can be configured by the QBSS administrators. The decision of admission is simply fulfilled by comparing two values: sum of reserved and request time with its boundary value. As mentioned before, it is out of scope to design an algorithm which limits the bulk of besteffort traffic (i.e., admission free data) lower than its threshold. In this section, we have introduced the proposed DAC algorithm which includes several schemes such as local admission check and procedures for maintaining QoS and keeping high resource utilization along with PHY rate adaptation. The DAC algorithm also takes network-adaptative applications such as streaming of scalable video into consideration, which tend to continue the service although the condition is not sufficient to make it. V. SIMULATION RESULTS TABLE I THE VALUES OF PARAMETERS USED IN MODEL VALIDATION. PHY / MAC header 6 / 34 bytes RTS / CTS / ACK header 20 / 14 / 14 bytes PHY rate 1, 2, 5.5, and 11 Mbps CW low 7, 15, 31, and 63 CW high 15, 31, 63, 127, and 255 CW be 31, 63, 127, 255, 511, and 1023 Channel propagation delay 1 µs Beacon interval 0.25 sec SIFS / Slot time 20 / 10 µs AIF S high, low, and be 40, 40, and 50 µs Foreman video traffic for AC high 104 Kbps (1000 bytes payload) Foreman video traffic for AC low 208 Kbps (1000 bytes payload) Pareto traffic for AC be 100 Kbps (On/Off time=500 ms and shape=1.5) TABLE II AVERAGE PSNR OF ENCODED FOREMAN SEQUENCE. Received layer Base-layer only Both layers Both but 50% corrupted base-layers PSNR db db db We present a part of all simulation results (due to the limited space), to verify the proposed DAC algorithm for the IEEE e EDCA. We have carefully implemented NS-2 codes of EDCA from to meet the IEEE e and proposed DAC specifications. The values of the various parameters used in simulative models are summarized in Table I. We evaluate 58

6 Normalized throughput AC high : base layer video traffic AC low : enhancement layer video traffic AC be : pareto traffic Simulation time Fig. 5. Throughput of each AC as a function of simulation time with sequential resource readjustment in the EDCA+DAC case. DAC performance in terms of QoS maintenance and capacity utilization through example scenarios of scalable video transmission. All QoS-demanding traffic streams are generated through ITU-T H codec, which can provide a signal to noise ratio (SNR)-based scalable version of coded video in the form of two layers: a base-layer and the enhancementlayers. As an objective method to estimate perceptual QoS maintenance performance, we measure the average peak-topeak signal to noise ratio (PSNR) of received video stream (the larger the PSNR, the better the quality). Table II shows the effect of the two layers to the quality of reconstructed video. It is quite clear that, we should pay more attention in guaranteeing the base-layer traffic. By comparing wireless streaming with and without the DAC, we attempt to show the enhanced performance. In order to fully load the QBSS, initially the 8 Mbps pareto best-effort traffic is injected into the simulation environment. 7 sec after the start of the simulation, each video flow is requested at every three seconds interval. In our configuration, we can service a total of 19 video streams over the QBSS. Fig. 5 shows the variation in occupied bandwidth as the simulation proceeds. In this scenario, we reserve 20% of total capacity for best-effort (i.e., β=1-0.2=0.8 in Fig. 4). For the best-effort traffic control, we simply apply rate control scheme which can lock (AC be ) if they reach their limit during beacon interval. Upon receiving next beacon frame, the best-effort traffic can get the TXOP. Mode EDCA DAC +EDCA TABLE III AVERAGE PSNR OF RECEIVED FOREMAN SEQUENCE. Datarate Numbers of Low speed link High 34.62dB 34.18dB 33.81dB Low 35.36dB 34.93dB 34.55dB Average 34.99dB 34.56dB 34.18dB High 37.67dB 37.56dB 36.73dB Low 34.90dB 34.57dB 34.29dB Average 36.29dB 36.07dB 35.51dB To simulate the effect of wireless channel variation, the link quality of between the QAP and non-ap QSTAs gets worse and the data-rate of the corresponding link is become low and it would degrade the total available resource as well. In this simulation, the DAC enabled non-ap QSTAs can notice that there is no additional resource (i.e., AAC) in WLAN through the procedure in Fig. 3. So, the QSTAs with low PHY rate, drop the packets that belong to enhancement layer to achieve their current MediumTime meets the required sending rate. Table III shows the receiver-side video quality in terms of average PSNR of Foreman (quarter common intermediate format-qcif:160x120) video when the variable number of low data-rate channels is occurring. We have selected the relative small QCIF resolution for simulation so that the DAC can be efficiently working with many flows. In the EDCA case, average PSNR of high data-rate channels is almost same or even lower than that of the low data-rate channels. However, in the EDCA+DAC case, it is prevented that video flows on the high data-rate channels lose their TXOPs from intrusion of low data-rate channels. Also, the average PSNR values in the EDCA+DAC case are bigger than the one in the EDCA. VI. CONCLUSION AND FUTURE WORK In this paper, we have introduced the dynamic admission control (DAC) algorithm for supporting the QoS-demanding service in IEEE e EDCA-based wireless home networks. The proposed DAC processes the resource requests through local and central decision of admission. To maintain the QoS of admitted flows when PHY rate is dynamically changed, the proposed DAC can rearrange the granted resource in a distributed way. This process can contribute to both high network resource utilization and the QoS maintenance. The simulation results show that the DAC can provide effective QoS maintaining performance with lower overhead against the environment where physical transmission rate is dynamically changed. As future researches, we will consider the extension of DAC for multi-hop environment for guaranteed time services such as realtime multimedia applications. REFERENCES [1] IEEE WG, Part 11: Wireless LAN MAC and PHY specification, IEEE Standard, Aug [2] VIDEO54, [3] ViXs [4] IEEE WG, Draft Supplement to Part 11: Wireless MAC and PHY specifications: MAC enhancements for quality of service (QoS), IEEE Standard e/D10.0, Sep [5] Y. Xiao, Performance analysis of IEEE e EDCF under saturation condition, in Proc. ICC, vol. 1, pp , Jun [6] Y. Xiao, H. Li, and S. Choi, Protection and guarantee for voice and video traffic in IEEE e wireless LANs, in Proc. INFOCOM, Mar [7] D. Qiao, S. Choi, and K.G. Shin, Goodput analysis and link adaptation for IEEE a wireless LANs, in IEEE Trans. Mobile Computing, vol. 1, no. 4, Oct.-Dec [8] Y. Xiao, H. Li, and S. Choi, Local data control and admission control for QoS support in wireless ad hoc networks, in IEEE Trans. V ehicular T echnology, vol. 53, pp , Sep [9] D. Pong and T. Moors, Fairness and capacity trade-off in IEEE WLANs, in Proc. LCN, pp , Nov [10] H. Yoon and J. Kim, Dynamic admission control for differentiated quality of video in IEEE e wireless LANs, in Proc. SPIE IT COM 2004 : Internet Multimedia Management Systems V, Oct