An efficient adaptative predictive load balancing method for distributed systems

When allocating processors to processes in a distributed system, load balancing is a main concern of designers. By its implementation, system performance can be enhanced by equally distributing the dynamically changing workload and consequently user expectation are improved through an additional r...

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Detalles Bibliográficos
Autores principales:	Esquivel, Susana Cecilia, Pereyra, C., Gallard, Raúl Hector
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	1998
Materias:	Ciencias Informáticas Informática distributed systems load balancing strategies mean response time acceptance hit ratio migration failures Modeling and prediction
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/24365
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-24365
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Informática distributed systems load balancing strategies mean response time acceptance hit ratio migration failures Modeling and prediction
spellingShingle	Ciencias Informáticas Informática distributed systems load balancing strategies mean response time acceptance hit ratio migration failures Modeling and prediction Esquivel, Susana Cecilia Pereyra, C. Gallard, Raúl Hector An efficient adaptative predictive load balancing method for distributed systems
topic_facet	Ciencias Informáticas Informática distributed systems load balancing strategies mean response time acceptance hit ratio migration failures Modeling and prediction
description	When allocating processors to processes in a distributed system, load balancing is a main concern of designers. By its implementation, system performance can be enhanced by equally distributing the dynamically changing workload and consequently user expectation are improved through an additional reduction on mean response time. In this way, through process migration, a rational and equitable use of the system computational power is achieved, preventing degradation of system performance due to unbalanced work of processors. This article presents an Adaptative Predictive Load Balancing Strategy (APLBS), a variation of Predictive Load Balancing Strategy (PLBS) reported elsewhere [1]. As PLBS, APLBS is a sender initiated, prediction-based strategy for load balancing. The predictive approach is based on estimates given by a weighted exponential average [12] of the load condition of each node in the system. The new approach tries to minimise traffic en the network selecting the most suitable subset of candidates to request migration and the novel aspect is that the size of this subset is adaptative with respect to the system workload. APLBS was contrasted against Random (R), PLBS and Flexible Load Sharing (FLS) [7] strategies on diverse scenarios where the load can be characterised as static or dynamic. A comparative analysis of mean response time, acceptance hit ratio and number of migration failures under each strategy is reported.
format	Objeto de conferencia Objeto de conferencia
author	Esquivel, Susana Cecilia Pereyra, C. Gallard, Raúl Hector
author_facet	Esquivel, Susana Cecilia Pereyra, C. Gallard, Raúl Hector
author_sort	Esquivel, Susana Cecilia
title	An efficient adaptative predictive load balancing method for distributed systems
title_short	An efficient adaptative predictive load balancing method for distributed systems
title_full	An efficient adaptative predictive load balancing method for distributed systems
title_fullStr	An efficient adaptative predictive load balancing method for distributed systems
title_full_unstemmed	An efficient adaptative predictive load balancing method for distributed systems
title_sort	efficient adaptative predictive load balancing method for distributed systems
publishDate	1998
url	http://sedici.unlp.edu.ar/handle/10915/24365
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bdutipo_str	Repositorios
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An efficient adaptative predictive load balancing method for distributed systems

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