Introduction to model-based reliability evaluation of wireless sensor networks

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 2, Issue PART 1, 2009, Pages 134-139

  Jaggle C ^a   Neidig, J ^a   Grosch, T ^a   Dressler, F ^b  

^a SIEMENS AG   (Germany)

^b UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

Author keywords

Monte Carlo Simulation; Network reliability; Sensor networks; Stochastic modeling

Indexed keywords

MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS; RELIABILITY ANALYSIS; SENSOR NETWORKS; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; TOPOLOGY;

CONVENTIONAL SYSTEMS; INDUSTRIAL ENVIRONMENTS; LIFE-TIME DISTRIBUTION; MODEL BASED APPROACH; MODEL-BASED ANALYSIS; MODEL-BASED EVALUATION; NETWORK RELIABILITY; RELIABILITY EVALUATION;

SENSOR NODES;

EID: 79960943232     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20090610-3-it-4004.00028     Document Type: Conference Paper

References (13)

1. Ball, M. (1986). Computational Complexity of Network Reliability Analysis: An Overview. IEEE Transactions on Reliability, 35(3), 230-239.
2. Chiu, C., Yeh, Y., and Chou, J. (2001). An effective Algorithm for optimal k-Terminal Reliability of distributed Systems. Malaysian Journal of Library & Information Science, 6(2), 101-118.
3. Dietrich, I. and Dressler, F. (2009). On the Lifetime of Wireless Sensor Networks. ACM Transactions on Sensor Networks (TOSN), 5(1), 1-39.
4. Durmaz, O. and Baydere, S. (2004). Impact of In-Network Buffering on the Reliability of Sensor Networks. In Proceedings of the Second International Workshop on Sensor and Actor Network Protocols and Applications (SANPA 2004). Boston, Massachusetts, USA.
5. Elmallah, E. (1992). Algorithms for k-Terminal Reliability Problems with Node Failures. Networks, 22, 369-384.
6. Hardy, G., Lucet, C., and Limnios, N. (2007). K-Terminal Network Reliability Measures with Binary Decision Diagrams. IEEE Transactions on Reliability, 56(3), 506-515. (Pubitemid 47399758)
7. International Electrotechnical Commission (1990). International Standard IEC 61025 Fault Tree Analysis.
8. Law, A. and Kelton, W. (2000). Simulation Modeling and Analysis. The McGrawHill Companies, New York.
9. Noori, M. and Ardakani, M. (2008). A Probability Model for Lifetime of Event-Driven Wireless Sensor Networks. In Proceedings of the 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2008), 269-277. San Francisco, Califonia, USA.
10. Rai, V. and Mahapatra, R. (2005). Lifetime Modeling of a Sensor Network. In Proceedings of the IEEE International Conference on Design, Automation and Test in Europe (DATE 2005), 269-277. Munich, Germany.
11. Sha, K. and Shi, W. (2005). Modeling the Lifetime of wireless Sensor Networks. Sensor Letters, 3(2), 126-135. (Pubitemid 41645739)
12. Shpungin, Y. (2008). Networks with unreliable Nodes and Edges: Monte Carlo Lifetime Estimation. International Journal of Applied Mathematics and Computer Sciences, 4(3), 160-173.
13. Whitesitt, J.E. (1995). Boolean Algebra and Its Applications. Dover Publications Inc., Mineola, New York.