A framework for allocating clients to rate-constrained multicast servers

Zongming Fei; Mengkun Yang; Mostafa H. Ammar; Ellen W. Zegura

doi:10.1016/S0140-3664(02)00263-3

A framework for allocating clients to rate-constrained multicast servers

Zongming Fei
, Mengkun Yang
, Mostafa H. Ammar
, Ellen W. Zegura

Producción científica: Article › revisión exhaustiva

6 Citas (Scopus)

Resumen

Forming multiple multicast groups is a technique often used to deal with the problem of heterogeneous client capacities by allocating clients with different capacities to different groups. In this paper, we investigate the problem of allocating clients to constrained multicast servers, which, similar to clients, have different capacities. We explore several interesting issues caused by these constraints and propose a framework for generating optimal solutions to the allocation problem. We evaluate the method by simulation and show a substantial performance gain of our algorithm over those considering the server constraints separately.

Idioma original	English
Páginas (desde-hasta)	1255-1262
Número de páginas	8
Publicación	Computer Communications
Volumen	26
N.º	12
DOI	https://doi.org/10.1016/S0140-3664(02)00263-3
Estado	Published - jul 21 2003

Nota bibliográfica

Funding Information:
The work of Zongming Fei and Mengkun Yang was supported in part by the National Science Foundation under Grants CCR-0204304 and EIA-0101242. The work of Mostafa H. Ammar and Ellen W. Zegura was supported in part by the National Science Foundation under Grant ANI-9973115. We also want to thank anonymous reviewers for their valuable comments that help improve the paper.

Financiación

The work of Zongming Fei and Mengkun Yang was supported in part by the National Science Foundation under Grants CCR-0204304 and EIA-0101242. The work of Mostafa H. Ammar and Ellen W. Zegura was supported in part by the National Science Foundation under Grant ANI-9973115. We also want to thank anonymous reviewers for their valuable comments that help improve the paper.

Financiadores	Número del financiador
National Science Foundation (NSF)	EIA-0101242, ANI-9973115, CCR-0204304

ASJC Scopus subject areas

Computer Networks and Communications

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10.1016/S0140-3664(02)00263-3

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title = "A framework for allocating clients to rate-constrained multicast servers",

abstract = "Forming multiple multicast groups is a technique often used to deal with the problem of heterogeneous client capacities by allocating clients with different capacities to different groups. In this paper, we investigate the problem of allocating clients to constrained multicast servers, which, similar to clients, have different capacities. We explore several interesting issues caused by these constraints and propose a framework for generating optimal solutions to the allocation problem. We evaluate the method by simulation and show a substantial performance gain of our algorithm over those considering the server constraints separately.",

keywords = "Multicast, Rate constraint, Replication, Server selection",

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AU - Ammar, Mostafa H.

AU - Zegura, Ellen W.

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N2 - Forming multiple multicast groups is a technique often used to deal with the problem of heterogeneous client capacities by allocating clients with different capacities to different groups. In this paper, we investigate the problem of allocating clients to constrained multicast servers, which, similar to clients, have different capacities. We explore several interesting issues caused by these constraints and propose a framework for generating optimal solutions to the allocation problem. We evaluate the method by simulation and show a substantial performance gain of our algorithm over those considering the server constraints separately.

AB - Forming multiple multicast groups is a technique often used to deal with the problem of heterogeneous client capacities by allocating clients with different capacities to different groups. In this paper, we investigate the problem of allocating clients to constrained multicast servers, which, similar to clients, have different capacities. We explore several interesting issues caused by these constraints and propose a framework for generating optimal solutions to the allocation problem. We evaluate the method by simulation and show a substantial performance gain of our algorithm over those considering the server constraints separately.

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KW - Rate constraint

KW - Replication

KW - Server selection

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A framework for allocating clients to rate-constrained multicast servers

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ASJC Scopus subject areas

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