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. Outline.
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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
Next Call May Come from a Wireless Hot Spot
Wireless Networks Laboratory (WINET)IEEE 802.11 Distributed Coordinate Function (DCF) MAC Protocol
Contention based MAC
Can it support QoS requirements of various applications?
Request to send
Clear to send
QoS requirements of real-time services can not be guaranteed if there are many contending users?
Service differentiation is still not enough to meet the strict QoS requirements
Can the IEEE 802.11 MAC protocol do better than service differentiation?
Wireless Networks Laboratory (WINET)MAC Service Time
State variable (j, k): j is the backoff stage, k is the backoff timer
Wj: the contention window at backoff stage j
p: collision probability perceived by a node
: maximum # of retransmissions
Collision probability p
payload size = 8000 bits, with RTS/CTS
MAC service time (ms)
Wireless Networks Laboratory (WINET)MAC Service Time of IEEE 802.11
When p is small, both the mean and standard deviation of MAC service timeare small.
Wireless Networks Laboratory (WINET)Delay and Delay Variation
Channel busyness ratio:
n: # of nodes
: the prob. that a node transmits in any slot
Wireless Networks Laboratory (WINET)Network Throughput
(Tidl pi )(Tcol pc)(Tsuc ps )
with good delay performance
Collision Probability p
Channel Busyness Ratio is an accurate, robust, and easily obtained sign of network status.
Avg. queue length
Pkt loss rate
Channel busyness ratio
Channel Busyness Ratio
The optimal operating point denoted by Umax
R: flow data rate (bps)
L: average packet length (bits)
Up to Urt (= γUmax, 0<γ<1) can be assigned to real-time traffic
Convergence of Multiplicative-Increase Phase
Convergence to Fairness Equilibrium
Each node is a source of greedy traffic
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
Wireless Networks Laboratory (WINET)Fairness
A new greedy node joins the network every other 10 seconds
Higher aggregate throughput
Fairness convergence speed: 0-2 s
Short term fairness
50 greedy nodes
A new voice node joins the network every other 10 seconds.