Modeling and Assessing the Dependability ofWireless Sensor Networks

This paper proposes a flexible framework for dependability modeling and assessing of Wireless Sensor Networks (WSNs). The framework takes into account network related aspects (topology, routing, network traffic) as well as hardware/software characteristics of nodes (type of sensors, running applications, power consumption). It is composed of two basic elements: i) a parametric Stochastic Activity Networks (SAN) failure model, reproducing WSN failure behavior as inferred from a detailed Failure Mode Effect Analysis (FMEA), and ii) an external library reproducing network behavior on behalf of the SAN model. This library specializes the SAN model by feeding it with quantitative parameters obtained by simulation or by experimental campaigns; it is also in charge of updating the network state in response to failure events during the simulation (e.g., routing tree updated due to node failures). The framework is thus suited to evaluate the dependability of several WSNs, with different topologies, routing algorithms, hardware/software platforms, without requiring any changes to its structure. The use of the external library makes the model simpler, decoupling the network behavior from the failure behavior. Simulation experiments are discussed that provide a quantitative evaluation of WSN dependability for a sample scenario: results show how the proposed framework supports WSN developers to find proper cost-reliability trade-offs for the system being deployed.

[1]  M. Potkonjak,et al.  On-line fault detection of sensor measurements , 2003, Proceedings of IEEE Sensors 2003 (IEEE Cat. No.03CH37498).

[2]  Bhaskar Krishnamachari,et al.  Impact of energy depletion and reliability on wireless sensor network connectivity , 2004, SPIE Defense + Commercial Sensing.

[3]  Lui Sha,et al.  Dynamic clustering for acoustic target tracking in wireless sensor networks , 2003, IEEE Transactions on Mobile Computing.

[4]  David E. Culler,et al.  Lessons from a Sensor Network Expedition , 2004, EWSN.

[5]  William H. Sanders,et al.  Dependability Evaluation Using Composed SAN-Based Reward Models , 1992, J. Parallel Distributed Comput..

[6]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[7]  Jens Palsberg,et al.  Avrora: scalable sensor network simulation with precise timing , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[8]  Antonio A. F. Loureiro,et al.  A Probabilistic Approach to Predict the Energy Consumption in Wireless Sensor Networks , 2002 .

[9]  William H. Sanders,et al.  The Möbius Framework and Its Implementation , 2002, IEEE Trans. Software Eng..

[10]  Laurent Ouvry,et al.  Probabilistic Model for Energy Estimation in Wireless Sensor Networks , 2004, ALGOSENSORS.

[11]  Sarma B. K. Vrudhula,et al.  Battery Modeling for Energy-Aware System Design , 2003, Computer.

[12]  Deborah Estrin,et al.  A wireless sensor network For structural monitoring , 2004, SenSys '04.

[13]  Michele Garetto,et al.  Modeling the performance of wireless sensor networks , 2004, IEEE INFOCOM 2004.

[14]  Arun Somani,et al.  Distributed fault detection of wireless sensor networks , 2006, DIWANS '06.

[15]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[16]  David E. Culler,et al.  Analysis of wireless sensor networks for habitat monitoring , 2004 .

[17]  S. Sitharama Iyengar,et al.  Computing reliability and message delay for Cooperative wireless distributed sensor networks subject to random failures , 2005, IEEE Transactions on Reliability.

[18]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

[19]  David E. Culler,et al.  Mica: A Wireless Platform for Deeply Embedded Networks , 2002, IEEE Micro.

[20]  Hong Liu,et al.  Infrastructure Communication Reliability of Wireless Sensor Networks , 2006, 2006 2nd IEEE International Symposium on Dependable, Autonomic and Secure Computing.

[21]  M. Economou.  The merits and limitations of reliability predictions , 2004, Annual Symposium Reliability and Maintainability, 2004 - RAMS.

[22]  Hakan Deliç,et al.  How many sensors for an acceptable breach detection probability? , 2006, Comput. Commun..

[23]  Mario Gerla,et al.  GloMoSim: a library for parallel simulation of large-scale wireless networks , 1998 .