An Investigative Approach to Enhance the Sensor Node Life by Mitigating the Recovery Effect of the Battery

Recent advances in the field of Wireless Sensor Networks (WSNs) have resulted in a wide range of applications in diversified fields and it is not an exaggeration to say that no field is untouched by the sensors. To name a few are agriculture, defense, medical, disaster and relief management, monitoring of vehicular traffic, wildlife monitoring in forests, monitoring of pollution levels in the atmosphere. The idea of micro-sensing along with wireless communication of these nodes ensures many new domains. The applications of wireless sensor networks can be broadly categorized into the environment, health, space exploration, chemical processing, and disaster relief, etc. Finally, sensor networks will provide the updated information to the end-user. It can be envisioned that in the future, wireless sensor networks will be an integral part of our lives. Nodes are usually run on non-rechargeable batteries. Therefore the energy is a chief concern. Especially when the sensor fields are enemy zones, impenetrable areas like forests and hilly terrains, and other hazardous environments, the only way to deploy them is random. In such conditions, it is difficult to replace exhausted batteries. Further many times the sensor nodes are abandoned for the very important reason that their batteries are drained out. However, the rest of the subsystems of the node are in perfect health condition. Therefore the important bottleneck is to ensure lower power consumption in challenging environments of the sensor field where sensor nodes are to be deployed. Hence past and present research work has been focused on the development of protocols for power conservation. These protocols, in general, provide trade-offs to the end-user to prolong the network lifetime.

The main objective of this paper focuses on the impact of the sampling interval, which is one of the sensor node parameters, on the battery life of the sensor node. An improper selection of sampling interval will lead to a pronounced recovery effect which leads to the premature death of the battery of the sensor node. This would in turn result in the premature death of the wireless sensor network. The suggested approach used in this paper has achieved an 18% life improvement of the battery of the sensor node and hence the lifetime of the wireless sensor network.