Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks

Ali Shareef,Yifeng Zhu

doi:10.1155/2012/870281

Abstract

Energy consumption of energy-constrained nodes in wireless sensor networks (WSNs) is a fatal weakness of these networks. Since these nodes usually operate on batteries, the maximum utility of the network is dependent upon the optimal energy usage of these nodes. However, new emerging optimal energy consumption algorithms, protocols, and system designs require an evaluation platform. This necessitates modeling techniques that can quickly and accurately evaluate their behavior and identify strengths and weakness. We propose Petri nets as this ideal platform. We demonstrate Petri net models of wireless sensor nodes that incorporate the complex interactions between the processing and communication components of an WSN. These models include the use of both an open and closed workload generators. Experimental results and analysis show that the use of Petri nets is more accurate than the use of Markov models and programmed simulations. Furthermore, Petri net models are extremely easier to construct and test than either. This paper demonstrates that Petri net models provide an effective platform for studying emerging energy-saving strategies in WSNs.

Highlights

Introduction and MotivationsApplication for wireless sensor networks (WSNs) has abounded since their introduction in early 2000
We demonstrate Petri net models of wireless sensor nodes that incorporate the complex interactions between the processing and communication components of an WSN
The energy prediction of a Petri net model for a simple sensor system will be compared against real measurements collected from an IMote2 node acting as a sensor node

Summary

Introduction

Introduction and MotivationsApplication for wireless sensor networks (WSNs) has abounded since their introduction in early 2000. A sensor network typically comprises of individual nodes operating with some limited computation and communication capabilities, and powered by batteries with limited energy supply. These networks are situated at a location where they may not be accessible. Modern WSNs were proposed for solving such problems, and it was envisioned that these WSN nodes could be sprinkled over an area from the back of an airplane as it flew over such an area The nodes wherever they fell would automatically set up an ad hoc network, collect the necessary sensory information, and route the information to a base-station. The task of obtaining the equations relevant to the system can be time-consuming, if not impossible

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Conclusion