Topology-Related Metrics and Applications for the Design and Operation of Wireless Sensor Networks

Abstract

The use of topological features, more specifically, the importance of an element related to its structural position, is a subject widely studied in the literature. For instance, the theory of complex networks provides centrality measures that have been applied to a large variety of fields (e.g., social sciences and biology). In this work, we propose a new topological measure, the Sink Betweenness (SBet), which stems from the theory of complex networks but is adapted to Wireless Sensor Networks (WSNs) to capture relevant information for this kind of network. We also provide a distributed algorithm to calculate it, and show its applicability to two different scenarios. The first one is focused on data fusion applications for event-driven WSNs, where we devise a tree-based data collection algorithm that takes advantage of node centrality to improve the data fusion efficiency. The second scenario is focused on energy balancing problems, more specifically in a problem called energy hole , where nodes closer to the sink are more likely to relay a larger number of packets than those that are further. This phenomenon is strongly related to the topology induced by the deployment of nodes along the sensor field, and it can be effectively captured by the SBet metric. Thus, we devise a data collection algorithm that is able to distribute the relay task more evenly. Simulation results show that the SBet metric can be satisfactorily used in both scenarios. We compare the proposed approach with some of the most efficient available data fusion algorithms, and show that the proposed algorithm generates consistently good-quality data collection infrastructures which require significantly smaller overhead. The use of SBet allows to alleviate the energy-hole effects by evenly balancing the relay load, and thus increasing the network lifetime. These two applications illustrate how the topology awareness can be used to improve different network functions in a WSN.