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Enabling distributed throughput maximization in wireless mesh networks: a partitioning approach
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Source International Conference on Mobile Computing and Networking archive
Proceedings of the 12th annual international conference on Mobile computing and networking table of contents
Los Angeles, CA, USA
SESSION: Mesh networks table of contents
Pages: 26 - 37  
Year of Publication: 2006
ISBN:1-59593-286-0
Authors
Andrew Brzezinski  Massachusetts Institute of Technology
Gil Zussman  Massachusetts Institute of Technology
Eytan Modiano  Massachusetts Institute of Technology
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 12,   Downloads (12 Months): 182,   Citation Count: 11
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ABSTRACT

This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multiradio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, in this paper we present a novel approach that takes advantage of the inherent multi-radio capability of WMNs. We show that this capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100% throughput. The partitioning is based on the recently introduced notion of Local Pooling. Using this notion, we characterize topologies in which 100% throughput can be achieved distributedly. These topologies are used in order to develop a number of channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. Finally, we evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  11

Collaborative Colleagues:
Andrew Brzezinski: colleagues
Gil Zussman: colleagues
Eytan Modiano: colleagues