A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization

Impact Factor:10.629

DOI number:10.1109/TEVC.2015.2457437

Affiliation of Author(s):Southwest Jiaotong Univ, Sch Informat Sci & Technol

Journal:IEEE Transactions on Evolutionary Computation

Key Words:Ant colony optimization (ACO),combinatorial optimization,network coding

Abstract:This paper presents a modified ant colony optimization (ACO) approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the concerned problem: 1) a multidimensional pheromone maintenance mechanism is put forward to address the issue of pheromone overlapping; 2) problem-specific heuristic information is employed to enhance the capability of heuristic search (neighboring area search); 3) a tabu-table-based path construction method is devised to facilitate the construction of feasible (link-disjoint) paths from the source to each receiver; 4) a local pheromone updating rule is developed to guide ants to construct appropriate promising paths; and 5) a solution reconstruction method is presented, with the aim of avoiding prematurity and improving the global search efficiency of proposed algorithm. Due to the way it works, the ACO can well exploit the global and local information of routing-related problems during the solution construction phase. The simulation results on benchmark instances demonstrate that with the integrated five extended mechanisms, our algorithm outperforms a number of existing algorithms with respect to the best solutions obtained and the computational time.

Co-author:Zhaoyuan Wang,Huanlai Xing*,Tianrui Li,Yan Yang,Rong Qu,Yi Pan

Document Code:10.1109/TEVC.2015.2457437

Volume:20

Issue:3

Page Number:325-342

ISSN No.:1089-778X

Translation or Not:no

Date of Publication:2016-06-01

Included Journals:SCI