A battery and environmental aware approach to maximize the lifetime of wireless sensor network

Wireless sensor network (WSN) is the most sought after field because of its applications in diversified domains and it is not an exaggeration to say that there is no area which is untouched by the sensors. To name a few are agriculture, defense, medical, disaster and relief management, monitoring of vehicular traffic, wild life monitoring in forests, monitoring of pollution levels in the atmosphere. It is important to know that WSNs are energized by non-rechargeable batteries when the sensor fields are enemy zones, impenetrable terrains and hazardous environments. Under such conditions, it is the battery lifetime which mainly decides the life time of the sensor node and thus effect the life time of the WSNs. It is further necessary to note that the battery technology is not developing at the same rate as the electronics field, with the result there is more stress on the lifetime of the battery. Therefore, there is a need to enhance the lifetime of the battery so that the lifetime of the WSNs could be enhanced. Lithium batteries, with their superior performance and characteristics, are being used in a variety of applications, including wireless sensor nodes. Further, the other chief concern of wireless sensor network is improving its lifetime in detrimental environmental conditions. Most of the earlier research works have focused on designing of power-aware algorithms with less focus on discharge characteristics of the battery and its behavior in different environmental conditions while attempting to extend the lifetime of the sensor nodes. Battery discharge characteristics play a major role which decides the lifetime of WSN. This paper presents a way of extending life time of the Lithium ion battery by finding optimal sampling time of the network with respect to one of the important discharge characteristics of the battery viz.: the Recovery effect. And the behavior of the sensor node is studied experimentally, at various temperatures. The power dissipation of the sensor node along with its lifetime is analyzed with respect to its surrounding temperature. An attempt is made to decrease the power dissipation of the sensor node at lower temperatures which lead to increasing of the lifetime of WSN. The experimental results have shown a 12-18% percent enhancement in the lifetime of the battery by employing optimal sampling time and an additional lifetime improvement of 9% is achieved by compressing the data at colder environmental conditions.