Balancing area coverage in partitioned wireless sensor networks

This paper deals with a resource sharing problem in wireless sensor networks (WSNs). The problem calls for identifying k data collection trees that can be managed by independent users to run applications requiring area coverage. The formalized problem, called k-balanced area coverage slices (k-BACS), calls for identifying an ensemble of k trees that share the sink node only (and no other node) in a given WSN. To avoid nodal congestion, each tree is required to satisfy constraints on the maximum degree of its nodes. The objective is to maximize the minimum total area covered by any tree in the ensemble. Existing results in the literature show that the k-BACS problem is NP-complete even if k =2. Thus, effective heuristic algorithms are needed. In this paper, we present and compare the performance of two efficient algorithms for solving the problem. Our results show that the devised algorithms produce well-balanced trees. In addition, the combined use of the computed partitions and the PEAS energy conservation protocol can produce competitive lifetime for networks where a prescribed level of area coverage is required for successful operation.