Paper Info
Title
An Ant Colony Optimisation Algorithm For Aggregated Multicast Based On Minimum Grouping Model
Abstract
The tree-based delivery structure of the traditional Internet protocol multicast requires each on-tree router to maintain a forwarding state for a group. This leads to a state scalability problem when large numbers of concurrent groups exist in a network. To address this state scalability problem, a novel scheme called aggregated multicast has recently been proposed, in which multiple groups are forced to share one delivery tree. In this paper, we define the aggregated multicast problem based on the minimum grouping model, and propose an ant colony optimisation algorithm. The relative fullness of the tree is defined according to the characteristics of the minimum grouping problem and is introduced as an important component in identifying the aggregation fitness function between two multicast groups. New pheromone update rules are designed based on the aggregation fitness function. To improve the convergence time of the algorithm, we use the changes (brought by each group) in the relative fullness of the current tree as the selection heuristic information. The impact of the relative fullness of the tree is analysed using the hypothesis test, and simulation results indicate that introducing relative fullness to the fitness function can significantly improve the optimisation performance of the algorithm. Compared with other heuristic algorithms, our algorithm has better optimisation performance and is more suitable for scenarios with larger bandwidth waste rates. Copyright (c) 2011 John Wiley & Sons, Ltd.
Year
DOI
Venue
2013
10.1002/dac.1342
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
Keywords
Field
DocType
aggregated multicast, minimum grouping problem, ant colony optimisation, hypothesis test, greedy algorithm
Internet Protocol,Mathematical optimization,Heuristic,Computer science,Algorithm,Fitness function,Greedy algorithm,Router,Multicast,Ant colony,Scalability
Journal
Volume
Issue
ISSN
26
3
1074-5351
Citations 
PageRank 
References 
5
0.43
14
Authors
2
Name
Order
Citations
PageRank
Fangjin Zhu1204.07
Hua Wang2172.99