Multicast Optimization Techniques using Best Effort Genetic Algorithms
Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
[1] Jorge Crichigno and Benjamin baran , " Multi objective Multi cast
Routing Algorithm for Traffic Engineering, IEEE 2004.
[2] Luca S Randaccio, Luigi Atzori, "A Genetic Algorithms Based
Approach for Group Multicast Routing, ACADEMY PUBLISHER
2006.
[3] Xuinxue Cui, Chuang Lin, Yaya Wei, "A Multi objective Model for QoS
Multi Cast Routing Based on Genetic Algorithm". Conference on
Computernetworks and Mobile computing. IEEE 2003
[4] Dimitri Bertsekas , Robert Gallager, Ch. 5,pp 363-385,Second Edition
Data Networks,PHI.
[5] S M Guosong Chu, Deng Wang, "A qos architecture for the MAC
protocol of IEEE 802.16 BWA system," IEEE International conference
on communication, circuits and systems and West Sino Expostions, vol.
I june 2002
[6] C. Eklund , R.B Marks, K.L Stanwood, and S. Wang , "IEEE Standard
802.16 : A Technical Overview of the wireless MAN-TM Air interface
for Broadband Wireless Acess, " IEEE communications, june 2002
[7] Andrew S. Tanenbaum, Pp. 150-160, Third Edition,
ComputerNetworks,PHI
[1] Jorge Crichigno and Benjamin baran , " Multi objective Multi cast
Routing Algorithm for Traffic Engineering, IEEE 2004.
[2] Luca S Randaccio, Luigi Atzori, "A Genetic Algorithms Based
Approach for Group Multicast Routing, ACADEMY PUBLISHER
2006.
[3] Xuinxue Cui, Chuang Lin, Yaya Wei, "A Multi objective Model for QoS
Multi Cast Routing Based on Genetic Algorithm". Conference on
Computernetworks and Mobile computing. IEEE 2003
[4] Dimitri Bertsekas , Robert Gallager, Ch. 5,pp 363-385,Second Edition
Data Networks,PHI.
[5] S M Guosong Chu, Deng Wang, "A qos architecture for the MAC
protocol of IEEE 802.16 BWA system," IEEE International conference
on communication, circuits and systems and West Sino Expostions, vol.
I june 2002
[6] C. Eklund , R.B Marks, K.L Stanwood, and S. Wang , "IEEE Standard
802.16 : A Technical Overview of the wireless MAN-TM Air interface
for Broadband Wireless Acess, " IEEE communications, june 2002
[7] Andrew S. Tanenbaum, Pp. 150-160, Third Edition,
ComputerNetworks,PHI
@article{"International Journal of Electrical, Electronic and Communication Sciences:55089", author = "Dinesh Kumar and Y. S. Brar and V. K. Banga", title = "Multicast Optimization Techniques using Best Effort Genetic Algorithms", abstract = "Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.", keywords = "GA (genetic Algorithms), Quality of Service,MOGA, Steiner Tree.", volume = "3", number = "2", pages = "228-3", }