A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks

2008 IEEE Congress on Evolutionary Computation, CEC 2008

Volumn , Issue , 2008, Pages 2749-2756

  Yang, Erfo ^a   Barton, Nick H ^b   Arslan, Tughrol ^a   Erdogan, Ahmel T ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b School of of Edinburgh   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; ELECTRIC LOAD FORECASTING; ENERGY EFFICIENCY; EVOLUTIONARY ALGORITHMS; HYBRID SENSORS; MODULATION; OPTIMIZATION; POPULATION STATISTICS; SENSOR NETWORKS; SENSORS; WIRELESS SENSOR NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS;

BIO-INSPIRED; ENERGY-EFFICIENT; MODULATION SCHEMES; NEW ALGORITHMS; NEW APPROACHES; NUMERICAL EXPERIMENTS; OPTIMIZATION ALGORITHMS; OPTIMIZATION PROBLEMS; OPTIMIZER; POPULATION GENETICS; SHIFTING BALANCE THEORIES; TOTAL ENERGY CONSUMPTIONS;

CONSTRAINED OPTIMIZATION;

EID: 55749109677     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2008.4631167     Document Type: Conference Paper

References (23)

1. I. Akyildiz, W. Su, Y. Sankarasubrarnaniam, and E. Cayirci, "A survey on sensor networks," IEEE Communications Magazine, vol. 40, no. 8, pp. 102-114, August 2002.
2. A. J. Goldsmith and S. B. Wicker, "Design challenges for energyconstrained ad hoc wireless networks," IEEE Wireless Communications, vol. 9, no. 4, pp. 8 27, August 2002.
3. C. Schurgers, V. Tsiatsis, S. Gancriwal, and M. B. Srivastava, "Optimizing sensor networks in the energy-latency-density design space," IEEE Transactions on Mobile Computing, vol. 1, no. 1, pp. 70 80, 2002.
4. S. Cui, A. J. Goldsmith, and A. Bahai, "Energy-constrained modulation optimization," IEEE Transactions on Wireless Communications, vol. 4, no. 5, pp. 2349 2360, September 2005.
5. R. Rujagopalan, C. Mohan, P. Varshncy, and K. Mehrotra. "Multiobjective mobile agent routing in wireless sensor networks," in Proceedings of the 2005 IEEE Congress on Evolutionary Computation (CEC'2005), Edinburgh, September 2005, pp. 1730-1737.
6. D. Jourdan and O. de Weck, "Multi-objective genetic algorithm for the automated planning of a wireless sensor network to monitor a critical facility," in Proceedings of the SPIE Defense and Security Symposium, vol. 5403, Orlando, Florida, April 12-16 2004, pp. 565-575.
7. H. Karl and A. Willig. Protocols and Architectures for Wireless Sensor Networks, 1st ed. Chichester: John Wiley & Sons, Ltd, 2005.
8. R. Jurdak, C. V. Lopes, and P. Baldi, Battery lifetime estimation and optimization for underwater sensor networks. Sensor Network Operations, Wiley and IEEE Press, 2006, pp. 397-420.
9. E. Yang, N. Haridas, A. El-Rayis, A. T. Erdogan, T. Arslan, and K. H. Barton, "Multiobjective optimal design of MEMS-hased reconligurable and evolvable sensor networks for space applications," in Proceedings of the. 2nd NASA/ESA Conference on Adaptive Hardware and Svstems, Edinburgh, August 5-8 2007, pp. 27 34.
10. Y. Ma and J. H. Ay lor, "System lifetime optimization for heterogeneous sensor networks with a Hub-Spoke topology," IEEE Transactions on Mobile Computing, vol. 3, no. 3, pp. 286 294, 2004.
11. A. Y. Wang, S. Cho, C. G. Sodini, and A. P. Chandrakasan, "Energyefficient modulation and MAC for asymmetric RP microsensor system," in Proceedings oj the 2001 International Symposium on Low-Power Electronics and Design, Huntington Beach, CA, August 6-7 2001, pp. 106 111.
12. C. Schurgers, O. Aberthorne, and M. B. Srivastava. "Modulation scaling for energy aware communication systems," in Proceedings oj the 2001 International Symposium on Low Power Electronics and Design, Huntington Beach, CA, August 6-7 2001, pp. 96-99.
13. A. L. Buczak, H. Wang, H. Darabi, and M. A. Jafari, "Genetic algorithm convergence study for sensor network optimization," Information Sciences, vol. 133, no. 3, pp. 267-282, April 2001.
14. K. H. Jones and K. N. Lodding, "Biology inspired approach for communal behavior in sensor networks," in Proceedings of the 39th Hawaii International Conference on System Sciences, Kauai, HL, USA, January 4-7 2006. pp. 1-9.
15. J. Kennedy and R. C. Eberhart. "Particle swarm optimization," in Proceedings of the 1995 IEEE International Conference on Neural Networks, Perth, Australia, Nov. 27 - Dec. 1 1995, pp. 1942 1948.
16. I. Beichl and F. Sullivan, "The metropolis algorithm," Computing in Science and Engineering, vol. 2, no. 1, pp. 65-69, January 2000.
17. F. Y. S. Tin and P. Chiu, "A simulated annealing algorithm for energy-efficient sensor network design," in Proceedings of the Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Trentino, April 3-7 2005, pp. 183 189.
18. T. Arslan, N. Haridas, E. Yang, A. Erdogan, N. Barton, A. Walton, J. Thompson, A. Stoica, T. Vladimirova, K. McDonald - Maier, and W. Howells, "ESPACENET: a framework of evolvable and reconfigurable sensor networks for aerospace-based monitoring and diagnostics,"" in Proceedings of the 1st NASA/ESA Conference on Adaptive Hardware and Systems, Istanbul, June 15-18 2006, pp. 323 329.
19. N. Metropolis, A. Rosenbluth, M. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller, "Equation of state calculations by fast computing machines," Journal of Chemical Physics, vol. 21, no. 6, pp. 1087-1092, June 1953.
20. S. M. Guru, S. K. Halgamuge, and S. Fernando, "Particle swarm optimizers tor cluster formation in wireless sensor networks," in Proceedings of the 2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing Conference, Melbourne, Australia, December 5-8 2005, pp. 319 324.
21. S. Wright, "Evolution in rnendelian populations," Genetics, vol. 16. no. 2, pp. 97-159, 1931.
22. K. H. Barton, "On the spread of new gene combinations in the third phase of Wright's shifting balance," Evolution, vol. 46, pp. 551-557, 1992.
23. K. H. Barton and S. Rouhani, "Adaptation and the 'shifting balance'," Genetical Research, vol. 61, pp. 57-74, 1993.