Modeling mobile-agent-based collaborative processing in sensor networks using generalized stochastic Petri nets

Hongtao Du, Hairong Qi, Gregory D. Peterson

Abstract: In mobile-agent-based distributed sensor networks (MADSNs), instead of moving data from an individual sensor node to a processing center as a typical scenario in the client/server-based computing, mobile agents on that carry the executable code are dispatched from the processing center to the sensor nodes and process data locally. Because of the complicated behavior of the mobile agents, there has not been much work done in modeling and simulation. In this paper, a Generalized Stochastic Petri Net (GSPN) is used to model the mobile agents in DSNs. GSPN is a very popular modeling tool for systems that feature concurrency, synchronization and randomness. One of the most challenging problems in GSPN modeling is to design a mechanism for breaking the transition conflicts. This paper presents a random transition selector based on joint entropy and a so-called "rolling rocks random (R3) selector" to break conflicts among immediate transitions. The GSPN model based on this transition selector is synthesized on a Xilinx Virtex 1000E Field Programmable Gate Array (FPGA) using reconfigurable components. Simulation results show that the proposed transition selector performs better than the commonly used random selector.