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Survey of admission control in IEEE 802.11e wireless LANs

Survey of admission control in IEEE 802.11e wireless LANs. 報告人：李宗穎. Outline. Introduction Background for IEEE 802.11e Admission Control for IEEE 802.11e Conclusion. Introduction (1/2). 802.11e standard provides a very powerful platform for QoS supports in WLANs

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Survey of admission control in IEEE 802.11e wireless LANs

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  1. Survey of admission control in IEEE 802.11e wireless LANs 報告人：李宗穎

  2. Outline • Introduction • Background for IEEE 802.11e • Admission Control for IEEE 802.11e • Conclusion

  3. Introduction (1/2) • 802.11e standard provides a very powerful platform for QoS supports in WLANs • This report provide an extensive survey of advances in admission control algorithms/protocols in IEEE 802.11e WLANs

  4. Introduction (2/2) • The purpose of admission control is to limit the amount of traffic admitted into a particular service class so that the QoS of the existing flows will not be degraded, while at the same time the medium resources can be maximally utilized

  5. Background for 802.11e • EDCA (enhanced distributed channel access) • Contention based • HCCA (HCF controlled channel access) • Centralized control • NOT much research work on the admission control issue in HCCA

  6. Background for 802.11e

  7. 802.11e EDCA mode

  8. Admission Control Research • Admission Control for EDCA • Measurement-based • Model-Based • Admission Control for HCCA • Do NOT covered in this report

  9. Distributed Admission Control (1/2) • Step 1 : via beacons the QAP announces the transmission budget • Step 2 : measure the amount of time occupied by the transmission of each AC during each beacon interval • transmission budget for an AC is depleted • new flow will not be able to obtain any transmission time • existing flows will not be able to increase their transmission time [ref.] Y. Xiao and H. Li, “Evaluation of Distributed Admission Control for the IEEE 802.11e EDCA,” IEEE Commun. Mag., vol. 42, no. 9, 2004, pp. S20–S24. [ref.] Y. Xiao and H. Li, “Voice and Video Transmissions with Global Data Parameter Control for the IEEE 802.11e Enhance Distributed Channel Access,” IEEE Trans. Parallel Distrib. Sys., vol. 15, no. 11, 2004, pp. 1041–53.

  10. Distributed Admission Control (2/2) • Shortcoming • it is difficult to avoid network performance vibration because a station always adjusts its transmission parameters at every beacon interval • this scheme does not provide direct relationships between those QoS requirements from applications

  11. Two-Level Protection and Guarantee Mechanism (1/3) • First level protection • each existing voice or video flow from new and other existing QoS flows • Second level protection • the existing QoS flows from best effort traffic [ref.] Y. Xiao, H. Li, and S. Choi, “Protection and Guarantee for Voice and Video Traffic in IEEE 802.11e Wireless LANs,” Proc. IEEE INFOCOM ’04, vol. 3, Hong Kong, Mar. 2004, pp. 2152–62.

  12. Two-Level Protection and Guarantee Mechanism (2/3) • tried-and-known mechanism • a new voice/video flow is first accepted tentatively, and then tries to measure throughput and delay performance for some beacon intervals • early-protection mechanism • the budget is below a certain threshold, new flows are not allowed to enter

  13. Two-Level Protection and Guarantee Mechanism (3/3) • too many best effort data transmissions can also degrade the existing QoS flows since many collisions might occur • increase the initial contention window size (dynamic control EDCA parameter) for best-effort traffic • the problems of DAC is performance oscillation and lack of direct QoS relationships with applications

  14. Virtual MAC and Virtual Source Algorithm (1/2) • The VMAC schedules virtual packets on the radio channel in the same way as real packets • it does not transmit anything but estimates the probability of collision if the virtual packet were “really” sent [ref.] M. Barry, A. T. Campbell, and A. Veres, “Distributed Control Algorithms for Service Differentiation in Wireless Packet Networks,” Proc. IEEE INFOCOM ’01, vol. 1, Anchorage, AK, 2001, pp. 582–90. [ref.] A. Veres et al., “Supporting Service Differentiation in Wireless Packet Networks Using Distributed Control,” IEEE JSAC, vol. 19, no. 10, 2001, pp. 2081–93.

  15. Virtual MAC and Virtual Source Algorithm (2/2) • Advantage • The advantage of these virtual algorithms is that they do not cost any channel bandwidth • Disadvantage • However, they need a lot of extra processing in each mobile host

  16. Harmonica (1/2) • the AP periodically samples the link layer quality indicator (LQI) parameters, which include drop rate, link layer end-to-end delay, and throughput, for each class • select the channel access parameters that best match the QoS requirements [ref.] L. Zhang and S. Zeadally, “HARMONICA: Enhanced QoS Support with Admission Control for IEEE 802.11 Contention-based Access,” Proc. IEEE RTAS ’04, Toronto, Canada, May 2004, pp. 64–71.

  17. Harmonica (2/2) • the HARMONICA will select a traffic class i that best matches its QoS requirement and then execute an admission control processThe relative adaptation has reached a stable state • BEthroughput– Reqthroughput> BEMin • how to find the optimal increment or decrement of the channel access parameters is still a challenging problem

  18. Threshold-Based Admission Control (1/2) • Using relative occupied bandwidth • Boccu= (TBusy/T) × 100% • Boccu< Blo : Admit the inactive AC with the highest priority • Boccu >Bup: Stop the transmission of the lowest active AC during the next period of T [ref.] D. Gu and J. Zhang, “A New Measurement-based Admission Control Method for IEEE 802.11 Wireless Local Area Networks,” Mitsubishi Elec. Research Lab., Tech. rep. TR-2003-122, Oct. 2003.

  19. Threshold-Based Admission Control (2/2) • Using average collision • The average collision ratio is defined as Rc=Nc/Nt • Ncis the number of collisions that have occurred • Ntis the total number of transmissions • Similarly, there are two thresholds: the lower threshold Rloand the upper threshold Rup

  20. Threshold-Based Admission Control • If the NUC (Network Utilization Characteristic) of all the flows (NUC_total) is below the set NUC threshold (NUC_threshold), the flow can be admitted • very easy to implement and can guarantee the QoS of high priority flows when the medium is heavily loaded • the issue of fairness is not considered • difficult to set the NUC_threshold value [ref.] S. Nor, A. Mohd, and C.Cheow, AN ADMISSION CONTROL METHOD FOR IEEE 802.11e, Network Theory and Applications, 2006.

  21. Resource Sharing-Based Admission Control (1/2) • bandwidth is reserved for a particular traffic AC and also be shared among them AC_BE & AC_BK (10%) AC_VO (20%) AC_VI (40%) AC_VO & AC_VI (30%) [ref.] A. Andreadis, G. Benelli, and R. Zambon, An Admission Control Algorithm for QoS Provisioning in IEEE 802.11e EDCA, 3rd ISWPC. Santorini, Greece, 2008.

  22. Resource Sharing-Based Admission Control (2/2) • Proposed Scheme • Utilization percentages of the channel • UAC_VO≤0.5 & UAC_VI≤0.7 & UAC_VO+UAC_VI≤ 0.9 • Reject new flow conditions • UAC_VO≥ 0.5, UAC_VI≥ 0.7, UAC_VO+UAC_VI≥0.9 • Characteristic • simplicity and fair to all different traffics • the static partition of bandwidth which could lead to an inefficient utilization of resources

  23. Markov Chain Model-based Admission Control (1/3) • Predicted achievable throughput for each flow, which is calculated by • Psiis the probability of a successful transmission for flow i • Pc, Ps and Pidleare the overall collision, overall successful transmission and overall idle probability • Tcand Tsare the collision time and successful transmission time, E[P] is the data payload [ref.] D. Pong and T. Moors, “Call Admission Control for IEEE 802.11 Contention Access Mechanism,” Proc. IEEE GLOBECOM’03, vol. 1, San Francisco, CA, Dec. 2003, pp. 174–78.

  24. Markov Chain Model-based Admission Control (2/3) • based on the two-state Markov Chain model proposed in [19], the transmission probability for flow i can be derived as • piis the long-term collision probability for flow i, • W is the CWminsize for flow i, and b is the maximum backoff stage [19] G. Bianchi, “Performance Analysis of the IEEE 802.11 Distributed Coordination Function,” IEEE JSAC, vol. 18, no. 3, 2000, pp. 535–47

  25. Markov Chain Model-based Admission Control (3/3) • There are several problems in this algorithm • the analytical model is derived under saturation conditions, where each station always has packets to transmit • This research does not take account of virtual collision between different AC queues in one station

  26. Contention-Window-Based Admission Control • The key idea of this scheme is to adjust the CW values for different stations so that the goals of admission control can be fulfilled • IEEE 802.11e WLAN is operating with a CW set {CW1, … , CWn} that meets the throughput requirements {Ri, … , Rn} for all stations [ref.] A. Banchs, X. Perez-Costa, and D. Qiao, “Providing Throughput Guarantees in IEEE 802.11e Wireless LANs,” Proc. 18th Int’l. Teletraffic Cong., Berlin, Germany, Sept. 2003.

  27. G/G/1-Based Admission Control (1/2) • channel utilization (cu) which are the decision criteria and average data rate (Rmean), peak data rate (Rpeak) and average packet length (PKl) are used to characterize • a flow’s bandwidth requirement as follows: cu=(R/PKl)∗ Tsuc, where R is the traffic rate • bandwidth requirement of a flow can be translated into (cumean, cupeak). [ref.] X. Chen, H. Zhai, and X. Tian, Supporting QoS in IEEE 802.11e Wireless LANs, IEEE Transactions on Wireless LANs Communications, 2006.

  28. G/G/1-Based Admission Control (2/2) • all admitted real-time flows into two parameters (cuA,mean, cuA,peak) and also estimate the average delay Diusing the G/G/1 model • admit a new QoS flow, three requirements need to be satisfied • cuA,mean + cui,mean < CUrt • cuA,peak + cui,peak < CUmax • average delay Diless than the delay bound Di

  29. Parameters-Based Admission Control (1/2) • combination of the MAC parameters is from an heuristic real-time algorithm • first, computes the minimum aggregated bandwidth required by all flows • Second, using this value and the achievable maximum physical bandwidth, the data rate, the MAC parameters are adjusted based on a set of predefined thresholds [ref.] B. Bellalta, M. Meo, and M. Oliver, VoIP Call Admission Control in WLANs in Presence of Elastic Traffic, IEEE Journal of Communications Software and Systems, 2007.

  30. Parameters-Based Admission Control (2/2) • Characteristic • This scheme sufficiently considers all EDCA parameters and fairness between uplink and downlink • the values of threshold are difficult to set and some assumptions exist which is inaccurate to algorithm

  31. Threshold-Based Admission Control • When new flow of ACirequests admission • QAP estimates the equivalent number of competing entities of class i predicts the achievable bandwidth and one-hop delay of the new flow • the analytical model of a non-saturatedis for IEEE 802.11 DCF which is not accurate to admissioncontrol for EDCA [ref.] B. Bensaou, Z. Kong, and D. Tsang, A Measurement- Assisted, Model-Based Admission Control Algorithm for IEEE 802.11e, The International Symposium on Parallel Architectures, Algorithms, and Networks. Sydney, Australia, 2008.

  32. Conclusion • There is many challenge in wireless admission control • How to model the heterogeneous wireless networks • How to optimally map the QoS requirement between different network layer • How to dynamic change parameter according to cross-layer conditions

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