Presentation on theme: "Achieving Throughput Fairness in Wireless Mesh Network Based on IEEE 802.11 Janghwan Lee and Ikjun Yeom Division of Computer Science KAIST"— Presentation transcript:
Achieving Throughput Fairness in Wireless Mesh Network Based on IEEE Janghwan Lee and Ikjun Yeom Division of Computer Science KAIST
Wireless Mesh Network Multi-hop wireless infrastructure Multi-hop wireless infrastructure Uses IEEE Uses IEEE Residential user or small business Internet Gateway node Router node Client node
Fairness Problem Unfair bandwidth sharing among flows with different hop distance
Related Work Centralized scheme [Gamboriza] Every node in the network knows about global topology and offered load. Calculate proper ingress rate at each node. Hard to know offered load. Not scalable.
Related Work Queueing Scheme Per flow queueing [Jun] Limit queue share [Nandiraju] Cannot resolve MAC layer contention Wasting bandwidth Cannot apply to the case when queue is not occupied enough
Problem Statement Support the same bandwidth to every leaf node with distributed algorithm. uplink Assume multi-radio, multi-channel To make a model simple Separate uplink and downlink channel Eliminate propagation of interference Independent collision domain Common in [Brezezinski], [Raniwala] Find proper weight f (p,i) that satisfies c i =c j for all i,j
Node Weight Estimation Need to know the number of active nodes Just counting the number of nodes with timeout is too naive Hard to adjust timeout value because of highly dynamic network We can estimate the weight by dividing the aggregate throughput by the average throughput of leaf nodes How to know L i ?
Node Number Estimation Leaf nodes piggyback their sending rate on packets Intermediate nodes calculate average value from leaf rate Need to compensate bias
Weighted Scheduling Achieving efficient channel utilization and weighted fairness for data communications in IEEE WLAN under DCF, In Proc. of IWQOS 2002Achieving efficient channel utilization and weighted fairness for data communications in IEEE WLAN under DCF, In Proc. of IWQOS 2002 Differentiate nodes using collision model Has a problem in multi-hop network
Weighted Scheduling From the model in [Qiao] and [Bianchi], the probability that node i attempts to transmit on given slot as, The probability that node i successfully transmits on a given slot, To satisfy the weight of node i and j, f i and f j,
Weighted Scheduling With exponential backoff, Unfortunately, we cannot get the solution of equations with closed form. Numerical solution
Weighted Scheduling Contention window size according to weighted scheduling model when the base contention window is 30
Weighted Scheduling Normalized throughput with changing the weight from 2 to 5 using different models
Simulation Result Simulation Topology
Simulation Result At 20 sec stops at 60 At 40 sec At 60 sec Initial Weight estimation and weighted schduling
Simulation Result TCP Throughput of each node (sorted in ascending order) Aggregate throughput of proposed scheme achieves 97% of the IEEE throughout simulations
Simulation Result UDP throughput of each node at different load (sorted in ascending order)
Conclusion We proposed a scheme to realize throughput fairness in wireless mesh network. Our scheme performed well without significant loss of aggregate throughput
Issues Are the assumptions about topology and channel environment reasonable? Cannot apply to the single channel or unplanned network
References [Gambiroza] V. Gambiroza et al. End-to-end performance and fairness in multihop wireless backhaul networks., in proc. of Mobicom 04 [Nandiraju] N. S. Nandiraju et al., A novel queue management mechanism for improving performance of multihop flows in IEEE s based mesh networks In Proc. of IPCCC 2006, April [Jun] J. Jun and M. L. Sichitiu, Fairness and QoS in multihop wireless network. In Proc. of VTC 2003-Fall [Qiao] D. Qiao et al., Achieving efficient channel utilization and weighted fairness for data communications in IEEE WLAN under DCF, In Proc. of IWQOS 2002 [Bianchi] G. Bianchi, Performance anlysis of the IEEE distributed coordination function., JSAC March, 2000.