Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

A EA- and ACA-based QoS multicast routing algorithm with multiple constraints for ad hoc networks

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

With the rapid development of communication networks, the quality of service (QoS) on such networks has become an important research topic. With regard to ad hoc networks, this paper presents an evolutionary algorithm (EA) and an ant colony algorithm (ACA) to serve as the basis for a QoS multicast routing algorithm (EA-ACA-QMRA). This algorithm combines the rapid global search capability and robustness of EAs with the pheromone feedback factors of ACAs while accounting for multiple constraints, including constraints related to delay, delay jitter, packet delivery ratio, bandwidth and cost. For the case of self-adapting ad hoc networks in particular, our new algorithm is far superior to traditional ACAs. Our experimental results show that the EA-ACA-QMRA can address multiple constraints in the QoS multicast routing problem and can achieve higher accuracy and faster convergence than can traditional ACAs in terms of the end-to-end delay and packet delivery ratio. The proposed algorithm provides an effective means of solving the QoS multicast routing problem for ad hoc networks, and it is better than the traditional methods at avoiding network congestion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Al-Sultan S, Al-Doori MM, Al-Bayatti AH, Zedan H (2014) A comprehensive survey on vehicular ad hoc network. J Netw Comput Appl 37:380–392

    Article  Google Scholar 

  • Bür K, Ersoy C (2009) Performance evaluation of a mesh-evolving quality-of-service-aware multicast routing protocol for mobile ad hoc networks. Perform Eval 66(12):701–721

    Article  Google Scholar 

  • Chen S, Nahrstedt K (1999) Distributed quality-of-service routing in ad hoc networks. IEEE J Sel Areas Commun 17(8):1488–1505

    Article  Google Scholar 

  • Chen T, Tsai J, Gerla M (1997) Qos routing performance in multihop, multimedia. Wirel Netw Proc IEEE ICUPC 2(2):557–561

    Google Scholar 

  • Choi JH, Shim KS, Lee S, Wu KL (2012) Handling selfishness in replica allocation over a mobile ad hoc network. IEEE Trans Mob Comput 11(2):278–291

    Article  Google Scholar 

  • Dorigo M, Gambardella LM (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53–66

    Article  Google Scholar 

  • Ho S, Shiyou Y, Yanan B, Huang J (2013) An ant colony algorithm for both robust and global optimizations of inverse problems. IEEE Trans Magn 49(5):2077–2080

    Article  Google Scholar 

  • Karthikeyan P, Baskar S (2015) Genetic algorithm with ensemble of immigrant strategies for multicast routing in ad hoc networks. Soft Comput 19(2):489–498

    Article  Google Scholar 

  • Kaur S, Bansal K, Bansal S (2013) Performance analysis of aodv, dsr and olsr routing techniques for ad hoc mobile networks. Int J Comput Sci Eng Inform Technol Res (IJCSEITR) 3(5):195–200

    Google Scholar 

  • Korošec P, Šilc J, Robic B (2003) A multilevel ant-colony optimization algorithm for mesh partitioning. Int J Pure Appl Math 5(2):143–159

    MathSciNet  MATH  Google Scholar 

  • Krishna PV, Saritha V, Vedha G, Bhiwal A, Chawla AS (2012) Quality-of-service-enabled ant colony-based multipath routing for mobile ad hoc networks. IET Commun 6(1):76–83

    Article  MathSciNet  MATH  Google Scholar 

  • Kumar P, Gyawali D (2014) Comparative analysis of unipath and multipath reactive routing protocols in mobile ad hoc network. Int J Res 1(6):287–293

    Google Scholar 

  • Lawton G (1998) Multicasting: will it transform the internet? Computer 31(7):13–15

    Article  Google Scholar 

  • Li J, Kim K, Zhang F, Chen X (2007) Aggregate proxy signature and verifiably encrypted proxy signature. In: Provable security. Springer, New York, pp 208–217

  • Li J, Li J, Chen X, Jia C, Lou W (2015) Identity-based encryption with outsourced revocation in cloud computing. IEEE Trans Comput 64(2):425–437

    Article  MathSciNet  MATH  Google Scholar 

  • Munaretto A, Fonseca M (2007) Routing and quality of service support for mobile ad hoc networks. Comput Netw 51(11):3142–3156

    Article  MATH  Google Scholar 

  • Pascual GG, Lopez-Herrejon RE, Pinto M, Fuentes L, Egyed A (2015) Applying multiobjective evolutionary algorithms to dynamic software product lines for reconfiguring mobile applications. J Syst Softw 103:392–411

    Article  Google Scholar 

  • Ray T, Tai K, Seow C (2001) An evolutionary algorithm for multiobjective optimization. Eng Optim 33(3):399–424

    Article  Google Scholar 

  • Sun B, Li L, Li X (2005) Progress of multicast routing protocols for mobile ad hoc networks. Comput Eng Appl 40(32):139–143

    Google Scholar 

  • Wang H, Xu H, Yi S, Shi Z (2011) A tree-growth based ant colony algorithm for qos multicast routing problem. Expert Syst Appl 38(9):11787–11795

    Article  Google Scholar 

  • Wang L, Shen J, Luo J (2015a) Facilitating an ant colony algorithm for multi-objective data-intensive service provision. J Comput Syst Sci 81(4):734–746

    Article  MathSciNet  MATH  Google Scholar 

  • Wang Z, Li M, Li J (2015b) A multi-objective evolutionary algorithm for feature selection based on mutual information with a new redundancy measure. Inform Sci 307:73–88

    Article  MathSciNet  Google Scholar 

  • Wineberg M (2014) Statistical analysis for evolutionary computation: an introduction. In: Proceedings of the companion publication of the 2014 annual conference on genetic and evolutionary computation, ACM, GECCO Comp ’14, pp 345–380

  • Woldesenbet YG, Yen GG (2009) Dynamic evolutionary algorithm with variable relocation. IEEE Trans Evol Comput 13(3):500–513

    Article  Google Scholar 

  • Xu M (2006) The next generation of wireless internet technology: wireless mesh network. Posts and Telecom Press, Beijing

    Google Scholar 

  • Yen YS, Chao HC, Chang RS, Vasilakos A (2011) Flooding-limited and multi-constrained qos multicast routing based on the genetic algorithm for manets. Math Comput Model 53(11):2238–2250

    Article  Google Scholar 

  • Yin PY, Chang RI, Chao CC, Chu YT (2014) Niched ant colony optimization with colony guides for qos multicast routing. J Netw Comput Appl 40:61–72

    Article  Google Scholar 

  • Zhang Dg, Zheng K, Zhang T, Wang X (2014) A novel multicast routing method with minimum transmission for wsn of cloud computing service. Soft Comput 19(7):1817–1827

  • Zhang XM, Zhang Y, Yan F, Vasilakos AV (2015) Interference-based topology control algorithm for delay-constrained mobile ad hoc networks. IEEE Trans Mob Comput 14(4):742–754

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Key Project of Natural Statistical Science and Research with the Grant No. 2015LZ30, the Natural Science Foundation of Jiangxi Province with the Grant No. 20142BAB217028, the National Natural Science Foundation of China with the Grant No. 61573157 and the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kangshun Li.

Ethics declarations

Conflict of interest

The authors declare there is no conflict of interests regarding the publication of this paper.

Additional information

Communicated by V. Loia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, W., Li, K., Huang, Y. et al. A EA- and ACA-based QoS multicast routing algorithm with multiple constraints for ad hoc networks. Soft Comput 21, 5717–5727 (2017). https://doi.org/10.1007/s00500-016-2149-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-016-2149-3

Keywords