Abstract
Area coverage problem in Directional Sensor Networks (DSNs) presents great research challenges including minimization of number of active sensors and overlapping sensing coverage area among them, determination of their active sensing directions in an energy-efficient way, etc. Existing solutions permit to execute coverage enhancement algorithms at each individual sensor nodes, leading to high communication and computation overheads, loss of energy and reduced sensing coverage. In this paper, we first formulate the problem of maximizing area coverage with minimum number of active nodes as a mixed-integer linear programming (MILP) optimization problem for a clustered DSN. Due to its NP-completeness, we then develop a greedy alternate solution, namely α-overlapping area coverage (α-OAC). In α-OAC, each cluster head (CH) takes the responsibility of determining the active member nodes and their sensing directions, where, each sensing node is allowed to have at most α% coverage overlapping with its neighbors. The α-OAC CHs activate a sensor node iif the later has sufficient residual energy and send other member nodes to the sleep state. The proposed α-OAC system is distributed and scalable since it requires single-hop neighborhood information only. Results from extensive simulations, done in NS-3, reveal that the α-OAC system outperforms state-of-the-art works in terms of area coverage, network lifetime and operation overhead.