A cross-layer approach for context-aware data gathering in Wireless Sensor Networks

Successful deployment of Wireless Sensor Networks (WSNs) depends on energy efficiency in computations and networking operations. Significant research efforts have been pursued over the last decade to realize techniques aimed at data gathering while prolonging network lifetime. Within data gathering applications, there is a class of applications that do not reconstruct the entire sensing field but mainly focus on monitoring and event/anomaly detection scenarios. In such applications, only representative data values (or distinct within a given threshold) are desired from different geographical (spatial) regions. Utilizing existing data gathering techniques in this type of applications yields communication-inefficient solutions, and therefore expensive in terms of energy cost. In this paper we investigate a cross-layer approach to reduce the number of communication operations in such specialized data gathering/monitoring applications. We explore the use of overhearing at the MAC layer in modifying the behavior of the application layer to realize Dynamic Virtual Clusters (DVCs). DVCs reduce data redundancy and dynamically distribute cluster head responsibilities, thus balancing the load and prolonging the network lifetime. Despite the cost of overhearing, our results show a reduction in the number of communication operations by a factor of up to N-1, where N is the number of nodes in a neighborhood.