Understanding and tackling the root causes of instability in wireless mesh networks

  • Authors:

  • Adel Aziz;David Starobinski;Patrick Thiran

  • Affiliations:

  • School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland;Department of Electrical and Computer Engineering, Boston University, Boston, MA;School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

  • Venue:
  • IEEE/ACM Transactions on Networking (TON)
  • Year:
  • 2011

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Abstract

We investigate, both theoretically and experimentally, the stability of CSMA-based wireless mesh networks, where a network is said to be stable if and only if the queue of each relay node remains (almost surely) finite. We identify two key factors that impact stability: the network size and the so-called "stealing effect," a consequence of the hidden-node problem and nonzero transmission delays. We consider the case of a greedy source and prove, by using Foster's theorem, that three-hop networks are stable, but only if the stealing effect is accounted for. We also prove that four-hop networks are, on the contrary, always unstable (even with the stealing effect) and show by simulations that instability extends to more complex linear and nonlinear topologies. To tackle this instability problem, we propose and evaluate a novel, distributed flow-control mechanism called EZ-flow. EZ-flow is fully compatible with the IEEE 802.11 standard (i.e., it does not modify headers in packets), can be implemented using off-the-shelf hardware, and does not entail any communication overhead. EZ-flow operates by adapting the minimum congestion window parameter at each relay node, based on an estimation of the buffer occupancy at its successor node in the mesh. We show how such an estimation can be conducted passively by taking advantage of the broadcast nature of the wireless channel. Real experiments, run on a nine-node test-bed deployed over four different buildings, show that EZ-flow effectively smooths traffic and improves delay, throughput, and fairness performance.