Energy Efficient Resource Optimization in Intermittently Connected Sensor Networks

Abstract

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.