A PBIL for load balancing in network coding based multicasting

One of the most important issues in multicast is how to achieve a balanced traffic load within a communications network. This paper formulates a load balancing optimization problem in the context of multicast with network coding and proposes a modified population based incremental learning (PBIL) al...

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Main Authors: Xing, Huanlai, Xu, Ying, Qu, Rong, Xu, Lexi
Format: Article
Published: Springer Verlag 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/39208/
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author Xing, Huanlai
Xu, Ying
Qu, Rong
Xu, Lexi
author_facet Xing, Huanlai
Xu, Ying
Qu, Rong
Xu, Lexi
author_sort Xing, Huanlai
building Nottingham Research Data Repository
collection Online Access
description One of the most important issues in multicast is how to achieve a balanced traffic load within a communications network. This paper formulates a load balancing optimization problem in the context of multicast with network coding and proposes a modified population based incremental learning (PBIL) algorithm for tackling it. A novel probability vector update scheme is developed to enhance the global exploration of the stochastic search by introducing extra flexibility when guiding the search towards promising areas in the search space. Experimental results demonstrate that the proposed PBIL outperforms a number of the state-of-the-art evolutionary algorithms in terms of the quality of the best solution obtained.
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institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T19:37:39Z
publishDate 2016
publisher Springer Verlag
recordtype eprints
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spelling nottingham-392082020-05-04T18:01:59Z https://eprints.nottingham.ac.uk/39208/ A PBIL for load balancing in network coding based multicasting Xing, Huanlai Xu, Ying Qu, Rong Xu, Lexi One of the most important issues in multicast is how to achieve a balanced traffic load within a communications network. This paper formulates a load balancing optimization problem in the context of multicast with network coding and proposes a modified population based incremental learning (PBIL) algorithm for tackling it. A novel probability vector update scheme is developed to enhance the global exploration of the stochastic search by introducing extra flexibility when guiding the search towards promising areas in the search space. Experimental results demonstrate that the proposed PBIL outperforms a number of the state-of-the-art evolutionary algorithms in terms of the quality of the best solution obtained. Springer Verlag 2016-07-12 Article PeerReviewed Xing, Huanlai, Xu, Ying, Qu, Rong and Xu, Lexi (2016) A PBIL for load balancing in network coding based multicasting. Lecture Notes in Computer Science, 9787 . pp. 34-44. ISSN 0302-9743 Load balancing Multicast Network coding Population based incremental learning http://link.springer.com/chapter/10.1007%2F978-3-319-42108-7_3 doi:10.1007/978-3-319-42108-7_3 doi:10.1007/978-3-319-42108-7_3
spellingShingle Load balancing
Multicast
Network coding
Population based incremental learning
Xing, Huanlai
Xu, Ying
Qu, Rong
Xu, Lexi
A PBIL for load balancing in network coding based multicasting
title A PBIL for load balancing in network coding based multicasting
title_full A PBIL for load balancing in network coding based multicasting
title_fullStr A PBIL for load balancing in network coding based multicasting
title_full_unstemmed A PBIL for load balancing in network coding based multicasting
title_short A PBIL for load balancing in network coding based multicasting
title_sort pbil for load balancing in network coding based multicasting
topic Load balancing
Multicast
Network coding
Population based incremental learning
url https://eprints.nottingham.ac.uk/39208/
https://eprints.nottingham.ac.uk/39208/
https://eprints.nottingham.ac.uk/39208/