A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes

•An approach to evaluate COverage-REliability of Wireless Sensor Network is given.•It gives probability of successful area coverage and reliable data delivery to sink.•It considers multiple states of a sensor node: active, sleep, relay, idle, fail.•Residual energy, duty-cycle and hardware failures of nodes affects node-states.•A Monte-Carlo Markov Chain methodology is given to enumerate the random node-states. A mobile Wireless Sensor Network (mWSN) is composed of a large number of tiny, inexpensive resource-constrained sensors scattered in the field of interest, with the sink node or the data collector moving around the field. One fundamental concern of an mWSN is to provide application-specific coverage of the area under surveillance. The reliability of an mWSN depends on sensing area coverage, network connectivity, and data handling capacity of the mWSN in the presence of multi-state sensors. To mention here, each sensor node during its life cycle may exist in ACTIVE, SLEEP, RELAY, IDLE or FAIL states due to hardware failure, random duty cycle and/or energy limitations. Under such constraints, to quantify application-specific coverage oriented reliability, a new coverage-reliability index, CORE, is introduced. CORE gives a measure of the ability of a sensor network with multi-state nodes to satisfy the application-specific coverage area requirement with reliable data delivery to the mobile sink. A Monte-Carlo Markov Chain simulation approach is proposed for evaluating CORE. The conducted computational experiments are carried on mWSNs of various sizes to demonstrate the versatility of the proposed approach.