On Connected Components In Multistate Wireless Sensor Network Probabilistic Models

We consider Wireless Sensor Networks (WSNs) that undergo frequent uncontrollable topological changes over time due to changes in node states. Examples of such WSNs include networks that utilize energy replenishment methods, networks where a node's communication or sensing capabilities vary over time, and Underwater Sensor Networks (UWSNs) with free mobile floats. Quantifying the likelihood that a network of this type succeeds in performing a given task requires the adoption of a suitable mathematical model coupled with the development of a suitable performance evaluation algorithm. Our work here serves the above goal for networks where each node can be in any one of a possible set of states, each node has a weight, the topology of the network varies over time, and we want to find the likelihood that the network is in a state with a connected component whose total weight is at least a given threshold value.