Testbed results of an opportunistic routing for multi-robot wireless networks

  • Authors:
  • Dong Min Kim;Young Ju Hwang;Seong-Lyun Kim;Gwang-Ja Jin

  • Affiliations:
  • Radio Resource Management and Optimization Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 262 Seongsanno, Seodaemun-Gu, Seoul 120-749, Republic of Korea;Radio Resource Management and Optimization Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 262 Seongsanno, Seodaemun-Gu, Seoul 120-749, Republic of Korea;Radio Resource Management and Optimization Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 262 Seongsanno, Seodaemun-Gu, Seoul 120-749, Republic of Korea;Vehicle-IT Convergence Research Department, Electronics and Telecommunications Research Institute (ETRI), 138 Gajeongno, Yuseong-gu, Daejeon 305-700, Republic of Korea

  • Venue:
  • Computer Communications
  • Year:
  • 2011

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Abstract

Opportunistic routing is a candidate for multihop wireless routing where the network topology and radio channels vary rapidly. However, there are not many opportunistic routing algorithms that can be implemented in a real multihop wireless network while exploiting the node mobility. It motivates us to implement an opportunistic routing, random basketball routing (BR), in a real multi-robot network to see if it can enhance the capacity of the multihop network as mobility increases. For implementation purposes, we added some features, such as destination RSSI measuring, a loop-free procedure and distributed relay probability updating, to the original BR. We carried out the experiments on a real multi-robot network and compared BR with AODV combined with CSMA/CA (routing+MAC protocol). We considered both static and dynamic scenarios. Our experiments are encouraging in that BR outperforms AODV+CSMA/CA, particularly in dynamic cases; the throughput of BR is 6.6 times higher than that of AODV+CSMA/CA. BR with dynamic networks shows 1.4 times higher throughput performance than BR with static networks. We investigate the performance of BR in the large-scale network using NS-2 simulation. We verify the effect of node density, speed, destination beacon signal and loop-free procedure. According to the large-scale simulation, the end-to-end throughput grows with the node speed.