EasiND: Effective Neighbor Discovery Algorithms for Asynchronous and Asymmetric-Duty-Cycle Multi-channel Mobile WSNs

Abstract

Neighbor discovery is a fundamental building block for wireless sensor networks (WSNs), because it is the first step to establish communication links between sensor nodes. Traditional neighbor discovery problems mainly focus on static wireless networks, or networks where all nodes operate on the same frequency. However, the proliferation of mobile devices and multi-channel communications post new challenges to this problem. In this paper, we present an effective neighbor discovery system named EasiND for asynchronous and asymmetrical duty-cycle multi-channel mobile WSNs. Firstly, we propose an optimal synchronous multi-channel neighbor discovery algorithm based on quorum system, which can bound the discovery latency in multi-channel scenario with low power consumption. Secondly, we design an asynchronous neighbor discovery quorum system for multi-channel WSNs. Theoretical analyses demonstrate that EasiND achieves a 33.3 and 50 % reduction in power-latency product when compared to U-Connect and Acc respectively. Thirdly, in order to enable EasiND to be applied to asymmetrical duty-cycle system, we propose an on-demand time slot activation scheme that combines random and cooperative methods together, which effectively reduces discovery latency. Finally, we present a channel scanning acceleration approach based on spatio-frequency characteristics of discovered neighbors, which further decreases discovery latency. We evaluate the performance of EasiND through comprehensive test-bed experiments. Experimental results show that EasiND decreases average discovery latency by up to 84.5 % compared to U-Connect and Acc, and achieves at least 95.6 and 97 % average fraction of discoveries in a predefined time limitation under 12 and 3 % duty-cycles.