PN-WSNA: An Approach for Reconfigurable Cognitive Sensor Network Implementations

In this paper, a decentralized Petri-net-(PN)-based wireless sensor node architecture (PN-WSNA) is proposed to model and implement a reconfigurable cognitive sensor network. The proposed PN-WSNA is defined based on an ordinary PN. Benefits of inheriting the ordinary PN are powerful modeling capabilities of discrete event dynamic systems as well as theoretical evaluations of sensor process models. A PN-WSNA engine is implemented as a kernel program in sensor nodes so that reconfigurations of sensor process can be achieved in terms of updating tiny PN-WSNA model instead of full executable firmware codes. Therefore, this approach provides an efficient and power-saving methodology to reconfigure and update the execution scenarios in remote sensor nodes. At the same time, a PN-WSNA management server is responsible for PN-WSNA model constructions, distance sensor node administrations, and routing table managements. Each PN-WSNA sensor node is realized using a BAT mote, and a simulated distributed solar tracking system is also demonstrated to verify our approaches.