A mobility prediction model for a role management dynamic algorithm for wireless sensor networks

The main goal of this paper is the analysis of the problem of joint dynamic re-assignment of node role and a Mobility Prediction Model (MPM). Based on the consideration that in almost all wireless sensor networks nodes can assume different roles it is fundamental to manage the rotation of the roles in order to realize a better energy distribution and prolong, in this way, the lifetime of the network. We focused on considering two different roles: a passive and an active role. When a sensor device assumes an active role it uses a greater amount of energy than the passive role. We considered a Role-dynamic Management Algorithm (RMA) that allows to realize a better energy distribution in the network varying in a dynamic fashion node role under different mobility conditions and permits longer lifetime to be obtained. In order to evaluate in a more opportunistic way node role changing times we developed a Mobility Prediction Model (MPM) and we jointly considered RMA and MPM on a known cross-layer approach, the EYES Source Routing (ESR) and EYES MAC (EMAC). Through extensive simulations, conducted with a well-known simulation tool, OMNeT++, we evaluated and validated the effectiveness of joint MPM and RMA.