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Evolutionary Local Search for the Minimum Energy Broadcast Problem

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Evolutionary Computation in Combinatorial Optimization (EvoCOP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4972))

Abstract

The problem of finding the broadcast scheme with minimum power consumption in a wireless ad-hoc network is NP-hard. This work presents a new hybrid algorithm to solve this problem by combining evolutionary approaches with local search. The algorithm is benchmarked by solving instances with 20 and 50 nodes where results are compared to either optimum or best results found by an IP solver. For these instances, the proposed algorithm was able to find optimal and near-optimal solutions and outperform previous heuristics.

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References

  1. Haas, Z.J., Tabrizi, S.: On some challenges and design choices in ad-hoc communications. In: Proceedings of the Military Communications Conference IEEE MILCOM 1998, Bedford, USA, pp. 187–192 (1998)

    Google Scholar 

  2. Rappaport, T.S.: Wireless Communications: Principles and Practices. Prentice-Hall, Englewood Cliffs (1996)

    Google Scholar 

  3. Wieselthier, J.E., Nguyen, G.D., Ephremides, A.: On the construction of energy-efficient broadcast and multicast trees in wireless networks. In: Proceedings of the 19th IEEE INFOCOM 2000, pp. 585–594 (2000)

    Google Scholar 

  4. Clementi, A.E.F., Crescenzi, P., Penna, P., Rossi, G., Vocca, P.: On the complexity of computing minimum energy consumption broadcast subgraphs. In: Ferreira, A., Reichel, H. (eds.) STACS 2001. LNCS, vol. 2010, pp. 121–131. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  5. Čagalj, M., Hubaux, J.P., Enz, C.: Minimum-Energy Broadcast in All-Wireless Networks: NP-Completeness and Distribution Issues. In: MobiCom 2002: Proceedings of the 8th Annual International Conference on Mobile Computing and Networking, pp. 172–182. ACM Press, New York (2002)

    Chapter  Google Scholar 

  6. Ambühl, C.: An optimal bound for the MST algorithm to compute energy efficient broadcast trees in wireless networks. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds.) ICALP 2005. LNCS, vol. 3580, pp. 1139–1150. Springer, Heidelberg (2005)

    Google Scholar 

  7. Wan, P.J., Călinescu, G., Li, X.Y., Frieder, O.: Minimum-energy broadcasting in static ad hoc wireless networks. Wireless Networks 8(6), 607–617 (2002)

    Article  MATH  Google Scholar 

  8. Das, A.K., Marks, R.J., El-Sharkawi, M., Arabshahi, P., Gray, A.: r-shrink: A heuristic for improving minimum power broadcast trees in wireless networks. In: Global Telecommunications Conference, GLOBECOM 2003, pp. 523–527. IEEE, Los Alamitos (2003)

    Google Scholar 

  9. Das, A.K., Marks, R.J., El-Sharkawi, M., Arabshahi, P., Gray, A.: Minimum power broadcast trees for wireless networks: Integer programming formulations. In: Proceedings of the 22nd IEEE INFOCOM 2003, pp. 1001–1010 (2003)

    Google Scholar 

  10. Montemanni, R., Gambardella, L.M., Das, A.: The minimum power broadcast problem in wireless networks: a simulated annealing approach. Wireless Communications and Networking Conference (WCNC) 4, 2057–2062 (2005)

    Article  Google Scholar 

  11. Kang, I., Poovendran, R.: Iterated local optimization for minimum energy broadcast. In: 3rd International Symposium on Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks (WiOpt), pp. 332–341. IEEE Computer Society, Los Alamitos (2005)

    Chapter  Google Scholar 

  12. Kang, I., Poovendran, R.: Broadcast with heterogeneous node capability. In: Global Telecommunications Conference, GLOBECOM 2004, pp. 4114–4119. IEEE, Los Alamitos (2004)

    Chapter  Google Scholar 

  13. Guo, S., Yang, O.W.: Energy-aware multicasting in wireless ad hoc networks: A survey and discussion. Computer Communications 30(9), 2129–2148 (2007)

    Article  Google Scholar 

  14. Al-Shihabi, S., Merz, P., Wolf, S.: Nested partitioning for the minimum energy broadcast problem. In: LION II: Learning and Intelligent Optimization Conference, Trento, Italy. LNCS, Springer, Heidelberg (to be published, 2008)

    Google Scholar 

  15. Hoos, H.H., Stützle, T.: Stochastic Local Search: Foundations and Applications. The Morgan Kaufmann Series in Artificial Intelligence. Morgan Kaufmann, San Francisco (2004)

    Google Scholar 

  16. Lourenço, H.R., Martin, O., Stützle, T.: Iterated Local Search. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics, pp. 321–353 (2002)

    Google Scholar 

  17. Ilog S.A.: ILOG CPLEX User’s Manual, Gentilly, France, and Mountain View, USA (2006), http://www.cplex.com/

  18. Merz, P., Freisleben, B.: Fitness Landscapes and Memetic Algorithm Design. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 245–260. McGraw–Hill, London (1999)

    Google Scholar 

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Jano van Hemert Carlos Cotta

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Wolf, S., Merz, P. (2008). Evolutionary Local Search for the Minimum Energy Broadcast Problem. In: van Hemert, J., Cotta, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2008. Lecture Notes in Computer Science, vol 4972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78604-7_6

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  • DOI: https://doi.org/10.1007/978-3-540-78604-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78603-0

  • Online ISBN: 978-3-540-78604-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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