Load Balancing of Java Applications by Forecasting Garbage Collections - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Load Balancing of Java Applications by Forecasting Garbage Collections

Résumé

Modern computer applications, especially at enterprise-level, are commonly deployed with a big number of clustered instances to achieve a higher system performance, in which case single machine based solutions are less cost-effective. However, how to effectively manage these clustered applications has become a new challenge. A common approach is to deploy a front-end load balancer to optimise the workload distribution between each clustered application. Since then, many research efforts have been carried out to study effective load balancing algorithms which can control the workload based on various resource usages such as CPU and memory. The aim of this paper is to propose a new load balancing approach to improve the overall distributed system performance by avoiding potential performance impacts caused by Major Java Garbage Collection. The experimental results have shown that the proposed load balancing algorithm can achieve a significant higher throughput and lower response time compared to the round-robin approach. In addition, the proposed solution only has a small overhead introduced to the distributed system, where unused resources are available to enable other load balancing algorithms together to achieve a better system performance.
Fichier principal
Vignette du fichier
portillo-ispdc2014.pdf (2.6 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01009399 , version 1 (03-11-2017)

Identifiants

Citer

Omar Portillo-Dominguez, Miao Wang, Damien Magoni, Philip Perry, John Murphy. Load Balancing of Java Applications by Forecasting Garbage Collections. 13th International Symposium on Parallel and Distributed Computing, Jun 2014, Porquerolles, France. pp.127-134, ⟨10.1109/ISPDC.2014.20⟩. ⟨hal-01009399⟩

Collections

CNRS
73 Consultations
175 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More