Markov decision process and network coding for reliable data transmission in wireless sensor and actor networks

Abstract

In delay sensitive applications of Wireless Sensor and Actor Networks (WSANs), achieving reliable data collection in the presence of a faulty region is a challenging issue. Sensed data may not be relayed to an actor due to fluctuations of wireless links in faulty regions. In this paper, a reliable data transmission mechanism using opportunistic encoding has been proposed for a WSAN with faulty nodes. A network coding approach has been designed by considering link loss rates and appropriate level of redundancy to achieve reliable data delivery. Further, a Markov Decision Process (MDP) has been proposed for opportunistic network coding decisions. The proposed mechanism determines the level of packet redundancy adaptively in the network coding process to improve reliable data collection and to reduce the number of data transmissions. Moreover, the state of a link changes with dynamic adverse environmental conditions, such as rainfall, fog and high temperature. The proposed mechanism analyzes the quality of link states and determines the applicability of network coding to improve the data transmission reliability and to reduce the number of data transmissions. Further, efficacy of the proposed mechanism has been shown through simulation results by considering number of data transmissions, average delivery delay, energy consumptions and network lifetime.