Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey PROJECT TITLE: Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey ABSTRACT: Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest An Adaptive Immune Based Anomaly Detection Algorithm for Smart WSN Deployments - 2015 Building a Scalable System for Stealthy P2P-Botnet Detection - 2014
