ICDCSW '06 Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems
Landscape analysis for multicast routing
Computer Communications
Genetic local search for multicast routing with pre-processing by logarithmic simulated annealing
Computers and Operations Research
A Novel Genetic Algorithm and Its Application in TSP
NPC '08 Proceedings of the 2008 IFIP International Conference on Network and Parallel Computing
Routing attribute data mining based on rough set theory
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
A SURVEY OF QOS ROUTING SOLUTIONS FOR MOBILE AD HOC NETWORKS
IEEE Communications Surveys & Tutorials
Quality-of-service routing for supporting multimedia applications
IEEE Journal on Selected Areas in Communications
Multipoint communication: a survey of protocols, functions, and mechanisms
IEEE Journal on Selected Areas in Communications
A Survey of Routing Protocols that Support QoS in Mobile Ad Hoc Networks
IEEE Network: The Magazine of Global Internetworking
High-dimensional objective optimizer: An evolutionary algorithm and its nonlinear analysis
Expert Systems with Applications: An International Journal
A tree-growth based ant colony algorithm for QoS multicast routing problem
Expert Systems with Applications: An International Journal
QoS routing algorithms using fully polynomial time approximation scheme
Proceedings of the Nineteenth International Workshop on Quality of Service
A novel acknowledgment-based approach against collude attacks in MANET
Expert Systems with Applications: An International Journal
Mathematical and Computer Modelling: An International Journal
| Hi-index | 12.06 |
Multicast routing is regarded as a critical component in networks especially the real-time applications become increasingly popular in recent years. This paper proposes a novel fast multi-objective evolutionary algorithm called MOEAQ for solving multicast routing problem (MRP) in MANET. The strengths and limitations of the well-known multicast model are analyzed firstly in this work. Specifically, the ''Greedy'' and ''family competition'' approach are integrated into MOEAQ to speed up the convergence and to maintain the diversity of population. The theoretical validations for the proposed method are presented to show its efficiency. After that, a CBT-based improved protocol is then proposed to simplify the MRP, and finally, the performance of MANET scaled from 20 to 200 nodes with different types of service is evaluated by OPNET, experimental results show that the proposed method is capable of achieving faster convergence and more preferable for multicast routing in MANET compared with other GA-based protocol well-known in the literature.