Load balancing in Wireless Sensor Networks is used to distribute network traffic over multiple paths. This results in uniform nodal energy dissipation and prolonged network lifetime. Most present load balancing techniques assign weights to prospective paths based on traffic patterns and hop distances, and achieve energy efficiency. However, these techniques neglect the relative criticality of a node in a giant connected component of a WSN. The relative criticality of a node in a connected network can be measured by an appropriate centrality metric such as betweenness or closeness degree. A Centrality metric measures the relative importance of a node in terms of network efficiency and utilization of the network resources. Use of centrality measures to analyze and optimize WSNs in terms of node deployment is a relatively unexplored niche. In this work, we devise a new centrality measure called Criticality Factor (CF) which is specific to WSNs and quantitatively estimates the relative criticality of a node in a cluster in terms of its upward and downward network connectivity. The CF is based on betweenness, closeness and average degree metrics. This CF can then be used in conjunction with load balancing schemes for increased energy efficiency in a WSN cluster.
