4.7 Article

DSS: Distributed SINR-Based Scheduling Algorithm for Multihop Wireless Networks

Journal

IEEE TRANSACTIONS ON MOBILE COMPUTING
Volume 12, Issue 6, Pages 1120-1132

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TMC.2012.81

Keywords

Wireless scheduling; SINR; CSMA; discrete time Markov chain

Funding

  1. KCC (Korea Communications Commission), Korea [KCA-2013-11-911-05-002]
  2. National Research Foundation of Korea
  3. Ministry of Education, Science, and Technology [2011-0008549]
  4. US Army Research Office MURI [W911NF-08-1-0238]
  5. US National Science Foundation [CNS-0905408, CNS-CNS-1012700, CNS-1065136]
  6. Division Of Computer and Network Systems
  7. Direct For Computer & Info Scie & Enginr [1012700] Funding Source: National Science Foundation
  8. Korea Communications Agency (KCA) [11-911-05-002] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  9. National Research Foundation of Korea [2011-0008549] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The problem of developing distributed scheduling algorithms for high throughput in multihop wireless networks has been extensively studied in recent years. The design of a distributed low-complexity scheduling algorithm becomes even more challenging when taking into account a physical interference model, which requires the SINR at a receiver to be checked when making scheduling decisions. To do so, we need to check whether a transmission failure is caused by interference due to simultaneous transmissions from distant nodes. In this paper, we propose a scheduling algorithm under a physical interference model, which is amenable to distributed implementation with 802.11 CSMA technologies. The proposed scheduling algorithm is shown to achieve throughput optimality. We present two variations of the algorithm to enhance the delay performance and to reduce the control overhead, respectively, while retaining throughput optimality.

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