1. Localized Algorithm for Aggregate Fairness in Wireless Sensor Networks Authors : Shigang Chen, Zhan Zhang CISE university of Florida CISE university of Florida Published : MobiCom 2006

2. Outline Introduction Introduction Aggregate Fairness Aggregate Fairness Distributed Computation of Aggregate Flow Weights Distributed Computation of Aggregate Flow Weights AFA AFA Simulation Simulation Conclusions Conclusions

3. Introduction Congestion control is great importance in sensor networks. When a sensor network scales up with more sensors deployed in a larger area, the traffic volume increases but the channel capacity around the bottlenecks cannot be increased easily.

4. Introduction

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6. Aggregate Fairness Every source nodes generate the same packets in weightless environment. Every source nodes generate the same packets in weightless environment. Source nodes generate packets proportional to its weight. Source nodes generate packets proportional to its weight. All packets send to sink node (s) success. All packets send to sink node (s) success.

7. Distributed Computation of Aggregate Flow Weights a, b, c  U i a, b, c  U i (a, i) : upstream link of i (a, i) : upstream link of i w, x, y, z  D i w, x, y, z  D i (w, i) : downstream link of I (w, i) : downstream link of I N : set of sensors N : set of sensors E = {(k, i) | i  N, k  U i } E = {(k, i) | i  N, k  U i } i a b c x w y z Base station 1 Base station 2

8. Distributed Computation of Aggregate Flow Weights A flow s is the sequence of data packets generated from a data source s in N. The data rate of flow s is denoted as d(s) the weight is denoted as w(s) r i (s) be the rate at which the packets of flow s pass through sensor i r s (s) = d(s) r k,i (s) be the rate at which the packets of flow s pass through link (k, i)

9. Distributed Computation of Aggregate Flow Weights

10. A rate assignment {r i (s), ∀ i, s ∈ N; r k,i (s), ∀ s ∈ N, ∀ (k, i) ∈ E} is feasible if the following constraints are satisfied.

11. Distributed Computation of Aggregate Flow Weights

16. AFA make sure that a sensor k sends a packet to a sensor i only when i has the buffer space to hold the packet i sends out a packet (RTS/CTS/DATA/ACK), it piggybacks its current buffer state in the frame header When sensor i is congested, it computes a rate limit for each upstream neighbor k as follows

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31. Conclusions This paper studies the end-to-end fairness problem in data-collection sensor networks. We formally define a new aggregate fairness model, prove its properties, and propose a distributed algorithm that implements the model. The simulation results confirm the effectiveness of the algorithm in achieving (weighted) fairness among competing data flows.