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CLC number: TP391

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Received: 2005-05-21

Revision Accepted: 2005-09-10

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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.2 P.156~163

10.1631/jzus.2006.A0156


Effective multicasting algorithm for dynamic membership with delay constraint


Author(s):  Chen Lin, Xu Zheng-quan

Affiliation(s):  Computer College, Yangtze University, Jingzhou 434102, China; more

Corresponding email(s):   chan_@sohu.com, xuzq@firstlink.com.cn

Key Words:  Multicast, Routing, Delay constraint, Quality of Service (QoS)


Chen Lin, Xu Zheng-quan. Effective multicasting algorithm for dynamic membership with delay constraint[J]. Journal of Zhejiang University Science A, 2006, 7(2): 156~163.

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author="Chen Lin, Xu Zheng-quan",
journal="Journal of Zhejiang University Science A",
volume="7",
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pages="156~163",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A0156"
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%T Effective multicasting algorithm for dynamic membership with delay constraint
%A Chen Lin
%A Xu Zheng-quan
%J Journal of Zhejiang University SCIENCE A
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%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A0156

TY - JOUR
T1 - Effective multicasting algorithm for dynamic membership with delay constraint
A1 - Chen Lin
A1 - Xu Zheng-quan
J0 - Journal of Zhejiang University Science A
VL - 7
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SP - 156
EP - 163
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2006.A0156


Abstract: 
This paper proposes an effective heuristic algorithm for dynamic multicast routing with delay-constrained DDMR. The tree constructed by DDMR has the following characteristics: (1) multicast tree changes with the dynamic memberships; (2) the cost of the tree is as small as possible at each node addition/removal event; (3) all of the path delay meet a fixed delay constraint; (4) minimal perturbation to an existing tree. The proposed algorithm is based on “damage” and “usefulness” concepts proposed in previous work, and has a new parameter bf (Balancing Factor) for judging whether or not to rearrange a tree region when membership changes. Mutation operation in Genetic Algorithm (GA) is also employed to find an attached node for a new adding node. Simulation showed that our algorithm performs well and is better than static heuristic algorithms, in term of cost especially.

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Reference

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