Connectivity restoration in disjoint Wireless Sensor Networks using centrality measures

In Mobile Sensor Networks (MSNs), connectivity of the sensor nodes with the sink node must be maintained at all times in order to sustain network operations. However, due to the depletion of limited on-board batteries and the exposure of the nodes to harsh environmental conditions, network can be subject to random node failures. While some of the failures can be compensated with redundancy, failure of the cut-vertex nodes renders the network partitioned. In order to restore connectivity with the sink, network structure can be updated through mobility of the nodes. However, mobility incurs excessive energy consumption and therefore, movement cost must be limited so that the network lifetime can be extended. In this paper, we present two approaches based on centrality metrics, which are commonly used in social network analysis. By applying these algorithms, we assess the relative importance of the nodes in a partition and use their centrality score while picking a node for movement. The first approach is based on closeness centrality where the less central nodes are favored for movement. The second approach is based on betweenness centrality where the nodes with the lower centrality scores are preferred for movement. The proposed approaches are implemented and tested against the currently used techniques.