JoWUA

Abstract

Network lifetime and energy consumption of data transmission have been primary Quality of Service (QoS) obligations in Wireless Sensor Networks (WSNs). The environment of a WSN is often organized into clusters to mitigate the management complexity of such obligations. However, the distance between Sensor Nodes (SNs) and the number of clusters per round are vital factors that affect QoS performance of a WSN. The designer’s conundrum resolves around the desire to sustain a balance between the limited residual energy of SNs and the demand for prolonged network lifetime. Any imbalance in controlling conflicting objectives may result in either QoS penalties due to draining SN energies which leaves WSN’s environment unevenly covered, or an over-cost environment that is significantly difficult to distribute and operate. Low-Energy Adaptive Clustering Hierarchy (LEACH) is a well-known distributed clustering algorithm proposed to tackle such difficulties. Multiple LEACH-based algorithms have also been proposed to enhance QoS requirements. Proposed algorithms typically focus on residual energies of SNs to compute a probability function that selects cluster-heads. Some algorithms form an optimal energy-efficient path toward a destination SN. Nevertheless, these algorithms do not consider variations in network’s state at run-time. Such a state changes in an adaptive manner according to existing network structures and conditions. Thus, cluster-heads per round are not elected adaptively depending on the state and distances between SNs. To tackle such complications, this paper proposes an energy-efficient adaptive distance-based clustering called Adapt-P, in which an adaptive probability function is developed to formulate clusters. A near-optimal distance between each cluster-head and its cluster-members is formulated so that energy consumption of the network is mitigated and accordingly the network lifetime is maximized. Distances between and residual energies of SNs are employed to obtain a maximum number of cluster-heads to be elected per round. The cluster-head selection probability is adapted at the end of each round based on the maximum number of cluster-heads permitted per round found a priori and the number of existing alive SNs in the network. The Adapt-P based algorithms proposed in this paper improve the performance of LEACH algorithm in term adaptivity and network lifetime.