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Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints

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Abstract

Wireless sensor networks have emerged as a promising way to develop high security systems. This paper presents the optimizations of a space-based reconfigurable sensor network under hard constraints by employing an efficient multi-objective evolutionary algorithm (MOEA). First, a system model is proposed for cluster-based space wireless sensor networks. Second, the statement of multi-objective optimization problems is mathematically formulated under hard constraints. Third, the MOEA is used to find multi-criteria solutions in the sense of Pareto optimality. Finally, simulation results are provided to illustrate the effectiveness of applying the MOEA to the multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints.

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Notes

  1. Evolvable Networks of Intelligent and Secure Integrated and Distributed Reconfigurable System-On-Chip Sensor Nodes for Aerospace Based Monitoring and Diagnostics.

References

  • Akyildiz I, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114

    Article  Google Scholar 

  • Arslan T, Haridas N, Yang E et al (2006) 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, Turkey, pp 323–329

  • Barr R, Bicket J, Dantas D et al (2002) On the need for system-level support for Ad hoc and sensor networks. ACM SIGOPS Oper Syst Rev 36(2):1–5

    Article  Google Scholar 

  • Clare L, Gao J, Jennings E, Okino C (2005) Space-based multi-hop networking. Comp Netw ISDN Syst 47(5):701–724

    Google Scholar 

  • Deb K (2002) Multi-objective optimization using evolutionary algorithms. Wiley, Chichester

    Google Scholar 

  • Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  • Globus A, Crawford J, Lohn J, Morris R (2002) Scheduling earth observing fleets using evolutionary algorithms: problem description and approach. In: Proceedings of the third international NASA workshop on planning and scheduling for space, Houston, Texas

  • Jourdan D, de Weck O (2004a) Layout optimization for a wireless sensor network using a multi-objective genetic algorithm. In: Proceedings of the IEEE semiannual vehicular technology conference, Milan, Italy

  • Jourdan D, de Weck O (2004b) 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, Orlando, Florida, pp 565–575

  • Jurdak R, Lopes CV, Baldi P (2006) Battery lifetime estimation and optimization for underwater sensor networks. Sensor Network Operations, Wiley and IEEE Press, pp 397–420

  • Karl H, Willig A (2005) Protocols and architectures for wireless sensor networks. Wiley, Chichester

    Book  Google Scholar 

  • Krishnamurthy A, Preis R (2005) Satellite formation, a mobile sensor network in space. In: Proceedings of the 19th IEEE international parallel and distributed processing symposium (IPDPS’05), Denver, Colorado, pp 243–249

  • Kumar R, Parida P, Gupta M (2002) Topological design of communication networks using multiobjective genetic optimization. In: Proceedings of the congress on evolutionary computation (CEC-2002), Honolulu, pp 425–430

  • Meguerdichian S, Koushanfar F, Potkonjak M, Srivastava MB (2001) Coverage problems in wireless ad-hoc sensor networks. In: Proceedings of the IEEE INFOCOM, Anchorage, Alaska, pp 1380–1387

  • Rajagopalan R, Mohan C, Varshney P, Mehrotra K (2005) Multi-objective mobile agent routing in wireless sensor networks. In: Proceedings of the 2005 IEEE congress on evolutionary computation (CEC-2005), Edinburgh, pp 1730–1737

  • Schurgers C, Tsiatsis V, Ganeriwal S, Srivastava M (2002) Optimizing sensor networks in the energy-latency-density design space. IEEE Trans Mobile Comput 1(1):70–80

    Article  Google Scholar 

  • Shu T, Krunz M (2005) Joint power/rate optimization for CDMA-based wireless sensor networks. In: Proceedings of the SenMetrics 2005—third international workshop on measurement, modelling, and performance analysis of wireless sensor networks, San Diego, pp 106–115

  • Shu T, Krunz M, Vrudhula S (2005) Power balanced coverage time optimization for clustered wireless sensor networks. In: Proceedings of the the sixth ACM international symposium on mobile ad hoc networking and computing (ACM MobiHoc 2005), Urbana-Champaign, pp 111–120

  • Srinivas N, Deb K (1994) Multiobjective optimization using nondominated sorting in genetic algorithms. Evol Comput 2(3):221–248

    Article  Google Scholar 

  • Vladimiroval T, Wu X, Bridges C et al (2006) Intelligent and distributed reconfigurable system-on-chip sensor networks for space applications—an introduction to ESPACENET. In: Proceedings of the 9th annual international MAPLD conference, Washington, DC

  • Watson J, Greenberg H, Hart W (2004) A multiple-objective analysis of sensor placement optimization in water networks. In: Proceedings of the world water and environment resources conference, Salt Lake City

  • Yang E, Haridas N, El-Rayis A et al (2007) Multiobjective optimal design of MEMS-based reconfigurable and evolvable sensor networks for space applications. In: Proceedings of the 2nd NASA/ESA conference on adaptive hardware and systems, Edinburgh, pp 27–34

  • Younis M, Akkaya K, Kunjithapatham A (2003) Optimization of task allocation in a cluster-based sensor network. In: Proceedings of the eighth IEEE international symposium on computers and communication, 2003. (ISCC 2003), Kiris-Kemer, Turkey, pp 329–334

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Acknowledgments

This research is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/C546318/1. The authors thank all of the team members of the ESPACENET project, which involves the Universities of Edinburgh, Surrey, Essex, and Kent, Surrey Satellite Technology (SSTL), NASA Jet Propulsion Laboratory (JPL), EPSON, and Spiral Gateway.

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Authors and Affiliations

  1. School of Engineering and Electronics, The University of Edinburgh, King’s Buildings, Edinburgh, EH9 3JL, UK

    Erfu Yang, Ahmet T. Erdogan & Tughrul Arslan

  2. School of Biological Sciences, The University of Edinburgh, King’s Buildings, Edinburgh, EH9 3JL, UK

    Nick H. Barton

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  1. Erfu Yang
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  2. Ahmet T. Erdogan
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  3. Tughrul Arslan
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  4. Nick H. Barton
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Correspondence to Erfu Yang.

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Yang, E., Erdogan, A.T., Arslan, T. et al. Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints. Soft Comput 15, 25–36 (2011). https://doi.org/10.1007/s00500-009-0406-4

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