The Novel Energy Efficient Heuristic Based Approach with Improved Network Lifetime in wireless sensor network

Abstract

Recent advances in micro-electro-mechanical systems (MEMS) technology, wireless communications, and digital electronics have enabled the development of low-cost, low-power, multifunctional sensor nodes that are small in size and communicate at short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, leverage the idea of sensor networks based on collaborative effort of a large number of nodes. In Wireless Sensor Networks, one of the main design challenges is to severely constrained energy resources and obtain long system lifetime. Due to the power scarcity of sensors a mechanism that can efficiently utilize the energy has a great impact on extending network life time. Sensor deployment is a critical issue since it reflects the cost and detection capability of a Wireless Sensor Network. newlineThe Quality of Service (QoS) requirement is added such that targets are covered by more than one sensor at any time, and the network may remain covered even after one or more sensors covering that target fail. The connected target Coverage problem requires that all the targets are covered by a subset of sensors (Coverage requirement) and all the targets are connected to the sink node through a subset of sensors by single-hop or multi-hop paths (Connectivity requirement). If any of the above requirements cannot be satisfied, then the deployed WSN reaches its lifetime and it will not work. Power-constrained Wireless Sensor Networks are usable as long as they can sense and communicate the sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management for sensing and communication and sensor scheduling can effectively extend network lifetime. The objective is to maximize the network lifetime of such a WSN. Maximizing sensor network life time satisfying Q-Coverage requirement is a NP-Complete problem and there is no known practical algorithm for it. Here a heuristic is proposed and proved that it yield solution very near to th