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A Comparative Study of Various Load Balancing Algorithm in Parallel and Distributed Multiprocessor System

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Mamta Kumari, Rakesh Kumar Katare

Mamta Kumari and Rakesh Kumar Katare. A Comparative Study of Various Load Balancing Algorithm in Parallel and Distributed Multiprocessor System. International Journal of Computer Applications 169(10):31-35, July 2017. BibTeX

	author = {Mamta Kumari and Rakesh Kumar Katare},
	title = {A Comparative Study of Various Load Balancing Algorithm in Parallel and Distributed Multiprocessor System},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {10},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {31-35},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017914901},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In modern days parallel and distributed computing is one of the greatest platform for research and innovation in the field of computer science. Rapid growth of communication network and need to solve large scale problem, complexity and efficiency of the system as a whole is the key issue. Load balancing is one of the most important problem in attaining high performance in parallel and distributed systems which may consist of many heterogeneous resources connected via one or more communication networks. Load balancing is the process of distributing or reassigning of load over the different nodes which provide good recourse utilization and better throughput. Although intense work has been done in the algorithm design of load balancing and its performance measure issues, we present a brief overview of various load balancing conditions and its algorithmic classification for tailor made applications. Various criteria were discussed for the classification of load balancing helping designers to compare and choose the most suitable algorithm for the application.


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Load–balancing, Hetrogeneous-resourse, Resource-utilization