A path-oriented encoding evolutionary algorithm for network coding resource minimization
Xing, Huanlai; Qu, Rong; Kendall, Graham; Bai, Ruibin
RONG QU email@example.com
GRAHAM KENDALL GRAHAM.KENDALL@NOTTINGHAM.AC.UK
Professor of Computer Science
Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computational overhead, due to the packet recombination performed (ie coding operations). Hence, it is of practical importance to reduce coding operations while retaining the benefits that network coding brings to us. In this paper, we propose a novel evolutionary algorithm (EA) to minimize the amount of coding operations involved. Different from the state-of-the-art EAs which all use binary encodings for the problem, our EA is based on path-oriented encoding. In this new encoding scheme, each chromosome is represented by a union of paths originating from the source and terminating at one of the receivers. Employing path-oriented encoding leads to a search space where all solutions are feasible, which fundamentally facilitates more efficient search of EAs. Based on the new encoding, we develop three basic operators, that is, initialization, crossover and mutation. In addition, we design a local search operator to improve the solution quality and hence the performance of our EA. The simulation results demonstrate that our EA significantly outperforms the state-of-the-art algorithms in terms of global exploration and computational time.
Xing, H., Qu, R., Kendall, G., & Bai, R. (2014). A path-oriented encoding evolutionary algorithm for network coding resource minimization. Journal of the Operational Research Society, 65(8), https://doi.org/10.1057/jors.2013.79
|Journal Article Type||Article|
|Online Publication Date||Jul 17, 2013|
|Publication Date||Aug 31, 2014|
|Deposit Date||Mar 17, 2015|
|Publicly Available Date||Mar 17, 2015|
|Journal||Journal of the Operational Research Society|
|Publisher||Taylor & Francis Open|
|Peer Reviewed||Peer Reviewed|
|Copyright Statement||Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf|
|Additional Information||This is a post-peer-review, pre-copyedit version of an article published in Journal of the Operational Research Society. The definitive publisher-authenticated version Journal of the Operational Research Society, vol. 65 (8), 2014, doi: 10.1057/jors.2013.79 is available online at: http://www.palgrave-jou.../full/jors201379a.html.|
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
You might also like
Do film festivals attract tourists?
Is Evolutionary Computation evolving fast enough?