Longest-queue-first scheduling under SINR interference model

We investigate the performance of longest-queue-first (LQF) scheduling (i.e., greedy maximal scheduling) for wireless networks under the SINR interference model. This interference model takes network geometry and the cumulative interference effect into account, which, therefore, capture the wireless...

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Bibliographic Details
Main Authors: Le, Long Bao (Contributor), Joo, Changhee (Author), Shroff, Ness B. (Author), Modiano, Eytan H. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery (ACM), 2013-10-21T18:16:58Z.
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Online Access:Get fulltext
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100 1 0 |a Le, Long Bao  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics  |e contributor 
100 1 0 |a Modiano, Eytan H.  |e contributor 
100 1 0 |a Le, Long Bao  |e contributor 
700 1 0 |a Joo, Changhee  |e author 
700 1 0 |a Shroff, Ness B.  |e author 
700 1 0 |a Modiano, Eytan H.  |e author 
245 0 0 |a Longest-queue-first scheduling under SINR interference model 
260 |b Association for Computing Machinery (ACM),   |c 2013-10-21T18:16:58Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/81464 
520 |a We investigate the performance of longest-queue-first (LQF) scheduling (i.e., greedy maximal scheduling) for wireless networks under the SINR interference model. This interference model takes network geometry and the cumulative interference effect into account, which, therefore, capture the wireless interference more precisely than binary interference models. By employing the ρ-local pooling technique, we show that LQF scheduling achieves zero throughput in the worst case. We then propose a novel technique to localize interference which enables us to decentralize the LQF scheduling while preventing it from having vanishing throughput in all network topologies. We characterize the maximum throughput region under interference localization and present a distributed LQF scheduling algorithm. Finally, we present numerical results to illustrate the usefulness and to validate the theory developed in the paper. 
520 |a United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-08-1-0238) 
520 |a National Science Foundation (U.S.) (Grant CNS-0915988) 
520 |a United States. Defense Threat Reduction Agency (Grant HDTRA1-07-1-0004) 
546 |a en_US 
655 7 |a Article 
773 |t Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing (MobiHoc '10)