Graph-Theoretic Based Connectivity Restoration Algorithms for Mobile Sensor Networks

In mobile sensor networks (MSN), actuated sensors collaborate with each other in some predefined missions. The collaboration requires application-level coordination based on a strongly connected underlying network, which is often in an infrastructure-free ad hoc manner. The particular network topology provides flexibility as well as vulnerability to the potential applications of MSN; for example, the connectivity can be easily jeopardized if the network is partitioned into disjoint segments from the failure of some critical sensors. In this paper, a critical sensor determination and substitution (CSDS) strategy is proposed to address the important problem of network partitions in mobile sensor networks (MSN) due to the failure of particular sensors. CSDS utilizes a graph-theoretic method to locally identify critical sensors with 2-hop neighboring information. Then, an efficient backup sensor selection algorithm is proposed to monitor the critical sensors and, if necessary, substitute it in order to eliminate the partitions in MSN. The main contribution of our proposed work is that CSDS requires the relocation of only one sensor in each partition elimination process, so that the impacts on the primary missions of the MSN are minimized. Experimental simulations are conducted to evaluate the correctness and effectiveness of CSDS.