A Review on Applications of Markov Decision Process Model and Energy Efficiency in Wireless Sensor Networks

Abstract

Wireless Sensor Network (WSN), in the most recent technology, is used for tracking and detecting the objects, remote monitoring and so on. The requirements of QoS, mainly for consumption of energy, at application layer is very critical issue in WSN. Wastage of energy is a considerable factor when many number of attempts for transmission is made, whenever failure occurs, due to interference and dynamics of channels. As WSN is comprised of autonomous devices and are also resource-limited, the devices need to be monitored depending on many physical phenomena in specific field of interest. Most of the time, because of uncertainty in monitored environments, WSNs function as stochastic systems which leads to some critical challenges faced by the sensor network. The major objective is to maintain low cost and efficient service time using few adaptive methods for the formation of topology, resource and power optimization, exchange of data, object detection, coverage of sensing, and security. To achieve such design goals and to reduce energy consumption, the sensor nodes have to make optimized decision from different accessible strategies. In this work, survey on applications of Markov Decision Process (MDP) is presented by designing the MDP framework which is a powerful tool for decision making and further providing solutions to obtain energy efficient sensor network. This framework includes the development of protocols and adaptive algorithms in WSN. Also various methods for solution are discussed and the methods are compared to assist as a guide for using MDPs in Wireless Sensor Network.