Approximation algorithms for channel allocation problems in broadcast networks

We study two packing problems that arise in the area of dissemination‐based information systems; a second theme is the study of distributed approximation algorithms. The problems considered have the property that the space occupied by a collection of objects together could be significantly less than...

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Veröffentlicht in:Networks Jg. 47; H. 4; S. 225 - 236
Hauptverfasser: Gandhi, Rajiv, Khuller, Samir, Srinivasan, Aravind, Wang, Nan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.07.2006
John Wiley & Sons
Schlagworte:
Applied sciences
channel allocation problem
Computer science; control theory; systems
Computer systems and distributed systems. User interface
distributed approximation algorithm
edge partitioning problem
Exact sciences and technology
Software
Hypergraph
Edge(graph)
Information system
channel allocation problem
edge partitioning problem
Resource allocation
Transmission channel
Layout problem
Approximation algorithm
Information dissemination
distributed approximation algorithm
Distributed algorithm
Channel allocation
ISSN:0028-3045, 1097-0037
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Zusammenfassung:We study two packing problems that arise in the area of dissemination‐based information systems; a second theme is the study of distributed approximation algorithms. The problems considered have the property that the space occupied by a collection of objects together could be significantly less than the sum of the sizes of the individual objects. In the Channel Allocation Problem, there are requests that are subsets of topics. There are a fixed number of channels that can carry an arbitrary number of topics. All the topics of each request must be broadcast on some channel. The load on any channel is the number of topics that are broadcast on that channel; the objective is to minimize the maximum load on any channel. We present approximation algorithms for this problem, and also show that the problem is MAX‐SNP hard. The second problem is the Edge Partitioning Problem addressed by Goldschmidt, Hochbaum, Levin, and Olinick (Networks, 41:13–23, 2003). Each channel here can deliver topics for at most k requests, and we aim to minimize the total load on all channels. We present an O(n1/3)–approximation algorithm, and also show that the algorithm can be made fully distributed with the same approximation guarantee; we also generalize the (nondistributed) Edge Partitioning Problem of graphs to the case of hypergraphs. © 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 47(4), 225–236 2006
Bibliographie:istex:29260E96B9F20F541DE904CDB7AFF782172DABDC
NSF - No. 0208055
ITR Award - No. CNS-0426683
ArticleID:NET20111
NSF - No. CCR-9820965
NSF CAREER Award - No. CCR-9501355
ark:/67375/WNG-P3F0K2L5-K
ISSN:0028-3045
1097-0037
DOI:10.1002/net.20111