Delay-Constrained Least-Energy-Consumption Multicast Routing Based on Heuristic Genetic Algorithm in Unreliable Wireless Networks

  • Ting LuEmail author
  • Shan ChangEmail author
  • Guohua Liu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 699)


Delay-constrained least-energy-consumption multicast tree construction is an important problem in wireless ad hoc networks and sensor networks to support multimedia applications such as audio and video. In the past few years, delay-constrained least-cost multicast tree construction had received much attention. However, these algorithms in wired networks cannot be directly used in wireless networks, because energy consumption are not considered in protocol design. In this paper, we focus on the problem of delay-constrained least-energy-consumption multicast routing in unreliable wireless multi-hop networks. Link error rate is considered in the process of multicast tree construction. We proposed a heuristic genetic algorithm to solve the problem. Simulations are performed to demonstrate the effectiveness and efficiency of the proposed algorithm.


Link error rate Energy Delay Wireless multi-hop networks Genetic algorithm 



This work is supported by National Natural Science Foundation of China (Grant No. 61402101, 61300199), Shanghai Municipal Natural Science Foundation (Grant No. 14ZR1400900), Fundamental Research Funds for the Central Universities (Grant No. 2232014D3-42, 2232014D3-21).


  1. 1.
    Forsati, R., Haghighat, A.T., Mahdavi, M.: Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing. Comput. Commun. 31(10), 2505–2519 (2008)CrossRefGoogle Scholar
  2. 2.
    Xue, G.L., Zhang, W.Y., Tang, J., Thulasiraman, K.: Polynomial time approximation algorithms for multi-constrained QoS routing. IEEE/ACM Trans. Netw. 16(3), 656–669 (2008)CrossRefGoogle Scholar
  3. 3.
    Zhang, L., Cai, L.B., Li, M., Wang, F.H.: A method for least-cost QoS multicast routing based on genetic simulated annealing algorithm. Comput. Commun. 32(1), 105–110 (2009)CrossRefGoogle Scholar
  4. 4.
    Lu, T., Zhu, J.: Genetic algorithm for energy-efficient QoS multicast routing. IEEE Commun. Lett. 17(1), 31–34 (2012)CrossRefGoogle Scholar
  5. 5.
    Banerjee, S., Misra, A., Yeo, J., Agrawala, A.: Energy-efficient broadcast and multicast trees for reliable wireless communications. In: Proceedings of the IEEE WCNC (2003)Google Scholar
  6. 6.
    Wang, Z., Shi, B., Zhao, E.: Bandwidth-delay-constrained least-cost multicast routing based on heuristic genetic algorithm. Comput. Commun. 24(7–8), 685–692 (2001)Google Scholar
  7. 7.
    Wikipedia, Depth-first search.
  8. 8.
    Lipowski, A., Lipowska, D.: Roulette-wheel selection via stochastic acceptance. Physica A 391(6), 2193–2196 (2012)CrossRefGoogle Scholar
  9. 9.
    Guoliang, C., Xufa, W., Zhenquan, Z., Dongsheng, W.: Genetic Algorithm and Its Application. People’s Posts and Telecommunications Press, Beijing (1996)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyDonghua UniversityShanghaiChina

Personalised recommendations