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Multi-agent Optimized Load Balancing Using Spanning Tree for Mobile Services

by Pradeep Kumar Sinha, Sunil R Dhore
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 6
Year of Publication: 2010
Authors: Pradeep Kumar Sinha, Sunil R Dhore
10.5120/145-265

Pradeep Kumar Sinha, Sunil R Dhore . Multi-agent Optimized Load Balancing Using Spanning Tree for Mobile Services. International Journal of Computer Applications. 1, 6 ( February 2010), 33-40. DOI=10.5120/145-265

@article{ 10.5120/145-265,
author = { Pradeep Kumar Sinha, Sunil R Dhore },
title = { Multi-agent Optimized Load Balancing Using Spanning Tree for Mobile Services },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 6 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 33-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number6/145-265/ },
doi = { 10.5120/145-265 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:44:39.315721+05:30
%A Pradeep Kumar Sinha
%A Sunil R Dhore
%T Multi-agent Optimized Load Balancing Using Spanning Tree for Mobile Services
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 6
%P 33-40
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Various communication and computing tasks in the fields can be integrated and applied in a distributed system. However, those resources are heterogeneous and dynamic in nature, connecting a broad range of resources. This study proposed a hybrid load balancing policy to maintain performance and stability of distributed system in Mobile services. Proposed work suggests to opt the use of some of advanced and efficient technologies like Multiagent. In this proposed implementation a two models are developed. The worker model is used to describe the workload and its current distribution within the system. The master model defines for a given algorithm at any instant of time and shows the formal context for obtaining and evaluating the load distribution decisions. Multiagent computing on a cluster of workstations is widely envisioned to be a powerful paradigm for building useful distributed applications. The Mobile agents of the system span across all the machines of a cluster. Just like the case of traditional distributed systems. With different characteristics between ordinary processes and agents, it is interesting and useful to investigate whether conventional load-balancing strategies are also applicable and sufficient to cope with the newly emerging needs, such as coping with temporally continuous agents, devising a performance metric for multi agent systems, and taking into account the vast amount of communication and interaction among agent. This work discusses the above issues with reference to agent properties and load balancing techniques and outlines the space of load-balancing design choices in the arena of multi agent computing. The proposed algorithm works by associating a credit value with each agent. The credit of an agent depends on its affinity to a machine, its current workload, its communication behavior, and mobility. When a load imbalance occurs, the credits of all agents are examined and an agent with a lower credit value is migrated to relatively lightly loaded machine in the system. Proposed work consider the problem of load balancing to minimize the cost of dynamic computations, including the cost of migrations. We propose the Ripple load balancing paradigm, The load balancing service presented is a generic tool for enhancing performance of accessing distributed objects from the WAP interface.

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Index Terms

Computer Science
Information Sciences

Keywords

Load balancing Multiagent WAP Spanning Tree

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