A sqrt(N/G) Method for Generating Communication Sets

In the fully meshed network, where every node is connected directly to every other node, network traffic is very high because in the fully meshed network, number of communication links is $\frac{N\times (N-1)}{2}$ and communication cost is $2\times N\times (N-1)$, where $N$ is total number of nodes...

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Main Authors: Rupali Bhardwaj, V.S. Dixit, Anil Kr. Upadhyay
Format: Article
Language:English
Published: Institute of Mathematics and Computer Science of the Academy of Sciences of Moldova 2012-02-01
Series:Computer Science Journal of Moldova
Subjects:
Online Access:http://www.math.md/files/csjm/v19-n3/v19-n3-(pp288-303).pdf
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spelling doaj-800c0b1f69674be794443fac979e62902020-11-24T22:41:45ZengInstitute of Mathematics and Computer Science of the Academy of Sciences of MoldovaComputer Science Journal of Moldova1561-40422012-02-01193(57)288303A sqrt(N/G) Method for Generating Communication SetsRupali Bhardwaj0V.S. Dixit1Anil Kr. Upadhyay2Krishna Institute of Engineering and Technology, Mahamaya Technical University, Noida, IndiaAtmaram Sanatan Dharmshala, Delhi University, Delhi, IndiaMata Rajkaur Institute of Engineering and Technology, Mahrishi Dayanand University, Rohtak, Haryana, IndiaIn the fully meshed network, where every node is connected directly to every other node, network traffic is very high because in the fully meshed network, number of communication links is $\frac{N\times (N-1)}{2}$ and communication cost is $2\times N\times (N-1)$, where $N$ is total number of nodes in the network. To minimize network traffic, we propose an algorithm for generation of communication sets that allows any two nodes to communicate by traversing at most two nodes regardless of the network size by dividing the nodes in the system into subgroups of size $G$ where $G\ge 1$, which are then organized into quorum groups of size $k_{1} = \left(\sqrt{\frac{N}{G} \, } approx.\right)$ in a method similar to that used in Maekawa's algorithm except that now quorum groups are constructed out of subgroups instead of nodes. The performance analysis of the proposed partitioning algorithm shows that it significantly reduces network traffic as well as total number of communication links required for a node to communicate with other nodes in the system.http://www.math.md/files/csjm/v19-n3/v19-n3-(pp288-303).pdfQuorumCoterieCommunication setsNetwork traffic
collection DOAJ
language English
format Article
sources DOAJ
author Rupali Bhardwaj
V.S. Dixit
Anil Kr. Upadhyay
spellingShingle Rupali Bhardwaj
V.S. Dixit
Anil Kr. Upadhyay
A sqrt(N/G) Method for Generating Communication Sets
Computer Science Journal of Moldova
Quorum
Coterie
Communication sets
Network traffic
author_facet Rupali Bhardwaj
V.S. Dixit
Anil Kr. Upadhyay
author_sort Rupali Bhardwaj
title A sqrt(N/G) Method for Generating Communication Sets
title_short A sqrt(N/G) Method for Generating Communication Sets
title_full A sqrt(N/G) Method for Generating Communication Sets
title_fullStr A sqrt(N/G) Method for Generating Communication Sets
title_full_unstemmed A sqrt(N/G) Method for Generating Communication Sets
title_sort sqrt(n/g) method for generating communication sets
publisher Institute of Mathematics and Computer Science of the Academy of Sciences of Moldova
series Computer Science Journal of Moldova
issn 1561-4042
publishDate 2012-02-01
description In the fully meshed network, where every node is connected directly to every other node, network traffic is very high because in the fully meshed network, number of communication links is $\frac{N\times (N-1)}{2}$ and communication cost is $2\times N\times (N-1)$, where $N$ is total number of nodes in the network. To minimize network traffic, we propose an algorithm for generation of communication sets that allows any two nodes to communicate by traversing at most two nodes regardless of the network size by dividing the nodes in the system into subgroups of size $G$ where $G\ge 1$, which are then organized into quorum groups of size $k_{1} = \left(\sqrt{\frac{N}{G} \, } approx.\right)$ in a method similar to that used in Maekawa's algorithm except that now quorum groups are constructed out of subgroups instead of nodes. The performance analysis of the proposed partitioning algorithm shows that it significantly reduces network traffic as well as total number of communication links required for a node to communicate with other nodes in the system.
topic Quorum
Coterie
Communication sets
Network traffic
url http://www.math.md/files/csjm/v19-n3/v19-n3-(pp288-303).pdf
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