Fair and Efficient Resource Allocation with QoS Support over ...


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Fair and Efficient Resource Allocation with QoS Support over ...

  1. 1. Quality of Service Support in Wireless Networks Hongqiang Zhai http://www.ecel.ufl.edu/~zhai Wireless Networks Laboratory Department of Electrical and Computer Engineering University of Florida In Collaboration with Dr. Xiang Chen and my advisor Professor Yuguang ``Michale’’ Fang
  2. 2. Outline <ul><li>Introduction </li></ul><ul><li>Performance analysis of the IEEE 802.11 MAC protocol </li></ul><ul><li>A call admission and rate control scheme </li></ul><ul><li>Conclusion and future research issues </li></ul>
  3. 3. Wireless Landscape
  4. 4. Wireless Local Area Networks/ Wi-Fi Hot Spots <ul><ul><ul><ul><ul><li>Instant messaging </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Gaming over IP </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Voice over IP over Wi-Fi </li></ul></ul></ul></ul></ul><ul><ul><ul><li>Web traffic </li></ul></ul></ul><ul><ul><ul><li>Email </li></ul></ul></ul><ul><ul><ul><li>Streaming video </li></ul></ul></ul>Next Call May Come from a Wireless Hot Spot
  5. 5. Mobile Ad Hoc Networks and Wireless Mesh Networks
  6. 6. Quality of Service (QoS) Requirements <ul><li>Bandwidth </li></ul><ul><li>Delay and delay jitter </li></ul><ul><li>Packet loss rate </li></ul>
  7. 7. Challenges <ul><li>Unreliable physical channel </li></ul><ul><ul><li>Time-varying propagation characteristics </li></ul></ul><ul><ul><li>Interference </li></ul></ul><ul><li>Limited bandwidth </li></ul><ul><li>Limited processing power and battery life </li></ul><ul><li>Distributed control </li></ul><ul><li>Mobility </li></ul>
  8. 8. Medium Access Control <ul><li>Coordinate channel access </li></ul><ul><ul><li>Reduce collision </li></ul></ul><ul><ul><li>Efficiently utilize the limited wireless bandwidth </li></ul></ul>A B C D
  9. 9. IEEE 802.11 Distributed Coordinate Function (DCF) MAC Protocol <ul><li>Carrier sense multiple access with collision avoidance (CSMA/CA) </li></ul><ul><ul><li>Carrier sensing </li></ul></ul><ul><ul><ul><li>Physical Carrier Sensing </li></ul></ul></ul><ul><ul><ul><li>Virtual Carrier Sensing </li></ul></ul></ul><ul><ul><li>Interframe Spacing (IFS) </li></ul></ul><ul><ul><ul><li>Short IFS (SIFS) < DCF IFS (DIFS) </li></ul></ul></ul>RTS CTS DATA ACK <ul><ul><li>Binary Exponential Backoff </li></ul></ul><ul><ul><ul><li>Randomly chosen from [0, CW] </li></ul></ul></ul><ul><ul><ul><li>CW doubles in case of collision </li></ul></ul></ul>Request to send Clear to send Acknowledge DATA Contention based MAC Can it support QoS requirements of various applications? DIFS Backoff SIFS SIFS SIFS NAV(RTS) NAV(CTS) DIFS RTS … Backoff Transmitter Receiver Others B A ACK …
  10. 10. Previous Work on Performance Analysis of the IEEE 802.11 MAC Standard <ul><li>Previous studies focus on saturated case </li></ul><ul><ul><li>Each device always has packets in the system and keeps contending for the shared channel. </li></ul></ul><ul><ul><ul><li>Collision probability is very high </li></ul></ul></ul><ul><ul><ul><li>Delay performance is very bad </li></ul></ul></ul><ul><ul><ul><li>Only throughput and average delay have been derived. </li></ul></ul></ul><ul><ul><li>Related work </li></ul></ul><ul><ul><ul><li>Bianchi, JSAC March 2000 </li></ul></ul></ul><ul><ul><ul><li>Cali et al., IEEE/ACM Tran. Networking, Dec. 2000 </li></ul></ul></ul>QoS requirements of real-time services can not be guaranteed if there are many contending users?
  11. 11. Previous Work on Supporting QoS in WLANs <ul><li>Service differentiation </li></ul><ul><ul><li>Provide different channel access priorities for different services by differentiating </li></ul></ul><ul><ul><ul><li>Contention window </li></ul></ul></ul><ul><ul><ul><li>Interframe spacing (IFS) </li></ul></ul></ul><ul><ul><li>IEEE 802.11e draft (based on 802.11b) </li></ul></ul><ul><ul><li>Related work </li></ul></ul><ul><ul><ul><li>Ada and Castelluccia, Infocom’01 (CW, IFS) </li></ul></ul></ul><ul><ul><ul><li>Veres et al., JSAC Oct. 2001 (real-time measurement in virtual MAC) </li></ul></ul></ul><ul><ul><ul><li>S.T. Sheu and T.F. Sheu, JSAC Oct. 2001 (real-time traffic periods) </li></ul></ul></ul><ul><ul><ul><li>S. Mangold et al., Wireless Communications Dec. 2003 (802.11e) </li></ul></ul></ul>Service differentiation is still not enough to meet the strict QoS requirements Can the IEEE 802.11 MAC protocol do better than service differentiation? <ul><li>Research issues </li></ul><ul><ul><li>Performance in both non-saturated and saturated case </li></ul></ul><ul><ul><li>Probability distribution of medium access delay </li></ul></ul>
  12. 12. MAC Service Time <ul><li>Probability Generating Function (PGF) </li></ul><ul><ul><li>Pr{Ts=t si }=p i (0 ≤ i < ∞) </li></ul></ul>1 2 3 3 Transmit queue MAC <ul><li>MAC service time is discrete in value </li></ul><ul><ul><li>SIFS, DIFS, EIFS </li></ul></ul><ul><ul><li>Backoff time is measured in time slots </li></ul></ul><ul><ul><li>Packet to be transmitted is also discrete in length </li></ul></ul>Packet arrival 1 2 3 2 3
  13. 13. MAC Service Time <ul><li>Generalized state transition diagram (GSTD) </li></ul><ul><ul><li>Mark the PGF of the transition time on each branch along with the transition probability </li></ul></ul><ul><ul><li>PGF of the transition time between two states is the corresponding system transfer function </li></ul></ul>start end <ul><li>Widely used method </li></ul><ul><ul><li>Calculate the average # of retransmissions N R = p/(1-p) </li></ul></ul><ul><ul><li>Average transition time is N R × τ 1 + τ 2 = </li></ul></ul>
  14. 14. MAC Service Time of IEEE 802.11 State variable (j, k): j is the backoff stage, k is the backoff timer W j : the contention window at backoff stage j p: collision probability perceived by a node  : maximum # of retransmissions
  15. 15. MAC Service Time of IEEE 802.11 Observation: When p is small, both the mean and standard deviation of MAC service time are small. MAC service time (ms) PDF Collision probability p payload size = 8000 bits, with RTS/CTS MAC service time (ms)
  16. 16. Delay and Delay Variation Transmit queue MAC Packet arrival T W 1 2 3 T S T R
  17. 17. Network Throughput ( T idl p i ) ( T col p c ) ( T suc p s ) Channel utilization : Normalized throughput : Channel busyness ratio : With RTS/CTS Without RTS/CTS n: # of nodes  : the prob. that a node transmits in any slot
  18. 18. Network Throughput Collision Probability p Channel Busyness Ratio is an accurate, robust, and easily obtained sign of network status. Maximum throughput with good delay performance
  19. 19. Packet Loss Rate <ul><li>Given the collision probability p , the MAC layer may drop the packet with the probability </li></ul>Avg. queue length Pkt loss rate Channel busyness ratio
  20. 20. Model Validation Channel Busyness Ratio The optimal operating point denoted by U max <ul><li>Simulation settings </li></ul><ul><ul><ul><ul><li>50 nodes, RTS/CTS mechanism is used </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Each node has the same traffic rate. </li></ul></ul></ul></ul><ul><ul><ul><ul><li>We monitor the performance at different traffic rates . </li></ul></ul></ul></ul>
  21. 21. Call Admission and Rate Control (CARC)
  22. 22. Call Admission Control <ul><li>Channel utilization/channel busyness ratio for a flow </li></ul><ul><li>Admission control test </li></ul>R : flow data rate (bps) L : average packet length (bits) Up to U rt (= γ U max , 0< γ < 1 ) can be assigned to real-time traffic
  23. 23. Rate control <ul><li>Notation: </li></ul><ul><ul><li>r : Channel resource r allocated to each node </li></ul></ul><ul><ul><ul><li>Allowable channel time occupation ratio </li></ul></ul></ul><ul><ul><li>t p: channel time for packet p </li></ul></ul><ul><ul><ul><li>Time that a successful transmission of packet p will last over the channel. </li></ul></ul></ul><ul><ul><li>∆ : scheduled interval </li></ul></ul><ul><ul><ul><li>Time between two consecutive packets that DRA passes to the MAC layer </li></ul></ul></ul><ul><ul><li>br : channel busyness ratio </li></ul></ul><ul><ul><ul><li>br th = U max </li></ul></ul></ul>
  24. 24. Rate control <ul><li>Initialization Procedure: r=r start </li></ul><ul><li>Three-Phase Resource Allocation Mechanism: </li></ul><ul><ul><li>multiplicative-increase if underloaded, i.e., br < B M = α ×br th </li></ul></ul><ul><ul><li>Additive-increase if moderately loaded, i.e., B M ≤ br < br th </li></ul></ul><ul><ul><li>Multiplicative-decrease if heavily loaded, i.e., br ≥ br th </li></ul></ul>
  25. 25. Theoretical Results of CARC Convergence of Multiplicative-Increase Phase
  26. 26. Theoretical Results of CARC Convergence to Fairness Equilibrium
  27. 27. Simulation Studies <ul><li>Simulation settings in ns2 </li></ul><ul><ul><li>Channel rate = 11 Mbps </li></ul></ul><ul><ul><li>Voice traffic with an on-off model </li></ul></ul><ul><ul><ul><li>The on and off periods are exponentially distributed with an average value of 300 ms each. </li></ul></ul></ul><ul><ul><ul><li>During on periods, traffic rate is 32kb/s with a packet size of 160 bytes. </li></ul></ul></ul><ul><ul><li>Greedy best effort traffic </li></ul></ul><ul><ul><ul><li>Saturated CBR traffic with a packet size of 1000bytes. </li></ul></ul></ul>
  28. 28. Throughput and MAC delay CARC improves the throughput by up to 71.62% with RTS/CTS, and by up to 157.32% without RTS/CTS CARC achieves up to 95.5% of maximum throughput with and without RTS/CTS Each node is a source of greedy traffic
  29. 29. Fairness Higher aggregate throughput Short term fairness Fairness convergence speed: 0-2 s A new greedy node joins the network every other 10 seconds Throughput Time (s) Throughput Time (s)
  30. 30. Quality of Service for Voice Traffic 50 greedy nodes A new voice node joins the network every other 10 seconds. 0.0811 s 0.0406 s 99%ile 97%ile
  31. 31. Conclusion <ul><li>The IEEE 802.11 MAC protocol can support strict QoS requirements of real-time services while achieving maximum throughput. </li></ul><ul><li>Channel busyness ratio is a good network status indicator of the IEEE 802.11 systems. </li></ul><ul><li>An efficient call admission and rate control framework is proposed to provide QoS for real-time service and also to approach the maximum throughput. </li></ul>