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Channel Aware Opportunistic Routing in Multi-Radio Multi-Channel Wireless Mesh Networks

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Abstract

Opportunistic routing (OR) involves multiple candidate forwarders to relay packets by taking advantage of the broadcast nature and multi-user diversity of the wireless medium. Compared with traditional routing (TR), OR is more suitable for the unreliable wireless link, and can evidently improve the end to end throughput. At present, there are many achievements concerning OR in the single radio wireless network. However, the study of OR in multi-radio wireless network stays the beginning stage. To demonstrate the benefit of OR in multi-radio multi-channel network, we propose a new route metric — multi-channel expected anypath transmission time (MEATT), which exploits the channel diversity and resource of multiple candidate forwarders for OR. Based on the new metric, a distributed algorithm named Channel Aware Opportunistic Routing (CAOR) is proposed. The simulation results demonstrate that MEATT improves 1.14 and 1.53 times of the average throughput than existing expected anypath transmission time (EATT)and metric of interference and channel switching cost (MIC) respectively. The average delay of MEATT is 17% and 40% lower than those of EATT, MIC, respectively.

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Authors and Affiliations

  1. College of Computer Science and Electronics Engineering, Hunan University, Changsha, 410082, China

    Shi-Ming He, Da-Fang Zhang, Kun Xie, Hong Qiao & Ji Zhang

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  1. Shi-Ming He
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  2. Da-Fang Zhang
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  3. Kun Xie
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  4. Hong Qiao
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  5. Ji Zhang
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Corresponding author

Correspondence to Da-Fang Zhang.

Additional information

This work was supported by the National Basic Research 973 Program of China under Grant No. 2012CB315805, the National Natural Science Foundation of China under Grant Nos. 61173167, 61003305, and 61173168, and the National Science and Technology Major Project of China under Grant No. 2011ZX03002-005-02.

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He, SM., Zhang, DF., Xie, K. et al. Channel Aware Opportunistic Routing in Multi-Radio Multi-Channel Wireless Mesh Networks. J. Comput. Sci. Technol. 29, 487–501 (2014). https://doi.org/10.1007/s11390-014-1444-7

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  • DOI: https://doi.org/10.1007/s11390-014-1444-7

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