Energy Efficient Resource Optimization in Intermittently Connected Sensor Networks

Wireless sensor networks (WSN) consist of several sensor nodes which are used for transmitting the data with limited capacity. In WSN, it is necessary to optimize the resource for better transmission of data from source node to destination and maximize the coverage area of the network to augment the lifetime of the network. In optimizing the resource in WSN, energy plays a major role to sustain the sensor nodes active status in the network. For maximizing the sensor nodes coverage area, several paths are followed by the previous researchers in different set of methods. Among all the previous works, Changlei Liu et. Al., presented a centralized heuristic protocol for scheduling the activities of the sensors for maximizing the spatial temporal coverage. To resolve the optimization problem, parallel optimization protocol (POP) is presented. Even though the sensor nodes are energy constrained by POP, only the limited numbers of sensor nodes are made active simultaneously for better coverage by consuming more energy. To resolve the above said issue, in this work, we plan to resolve the energy-efficient wireless sensor network coverage using node constrained linear integer programming technique. With the technique, a node constrained energy efficient connected coverage algorithm is developed for enhancing the lifetime of the network by increasing the coverage area of the sensor nodes. For the better coverage area phase, an energy drain rate of each sensor node is determined and formulates the sensing structure of the information. Experimental evaluation is done with the sensor nodes for better coverage in network environment and its performance is evaluated with varied set of sensor nodes with measuring metrics such as energy efficiency, network lifetime, and coverage area.