Load management with mobile agents

Obelöer, Wolfgang; Grewe, Claus; Pals, Holger

doi:10.1109/eurmic.1998.708134

Cited by 19 publications

(9 citation statements)

References 8 publications

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“…Dynamic methods are able to redistribute workload among nodes at run time, depending on changes in the system state. The work of Rajagopalan et al [28] and Obeloer et al [25] are agent-based techniques. These are flexible and configurable approaches but the amount of resources needed for agent implementation is considerably large.…”

Section: Previous Workmentioning

confidence: 98%

Parallel CBIR implementations with load balancing algorithms

Bosque¹,

Robles²,

Pastor³

et al. 2006

Journal of Parallel and Distributed Computing

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Section: Previous Workmentioning

confidence: 98%

Parallel CBIR implementations with load balancing algorithms

Bosque¹,

Robles²,

Pastor³

et al. 2006

Journal of Parallel and Distributed Computing

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“…MALD [8] uses the mobile agent technology to implement a scalable load balancing approach with the distributed web servers. FLASH [12] is a framework developed to apply load balancing to the cluster system. In addition, there exists a macroscopic characterization of agent-based load balancing in homogeneous mini-grid environments [13].…”

Section: B Load Balancingmentioning

confidence: 99%

Reducing Response Time with Dynamic Load Balancing and Agent Pool in Multi-Agent System

Lee

Moon

Yong

et al. 2011

2011 14th IEEE International Conference on Computational Science and Engineering

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Recently, the ubiquitous computing paradigm rapidly evolves and the agent technology attracts lots of researchers applying it to various applications. In the ubiquitous environment, the multiple agent system is able to provide customized service to the users by effectively utilizing the distributed system resource. In this paper we propose a dynamic prediction-based approach for both load balancing and agent pool management. It can reduce the response time for service request by avoiding unnecessary agent migration and creation of agents. The experiments reveal that the proposed scheme significantly reduces the response time compared with the existing scheme.

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“…It supports load balancing and dynamic resource utilization. Flash [33] is a framework for the creation of load balanced distributed application in heterogeneous cluster system.…”

Section: Methodsmentioning

confidence: 99%

A Framework for Distributed Dynamic Load Balancing in Heterogeneous Cluster

Nehra¹,

Patel²,

Bhat³

2007

J. of Computer Science

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Distributed Dynamic load balancing (DDLB) is an important system function destined to distribute workload among available processors to improve throughput and/or execution times of parallel computer in Cluster Computing. Instead of balancing the load in cluster by process migration, or by moving an entire process to a less loaded computer, we make an attempt to balance load by splitting processes into separate jobs and then balance them to nodes. In order to get target, we use mobile agent (MA) to distribute load among nodes in a cluster. In this study, a multi-agent framework for load balancing in heterogeneous cluster is given. Total load on node is calculated using queue length which is measured as the total number of processes in queue. We introduce types of agents along with policies needed to meet the requirements of the proposed load-balancing. Different metrics are used to compare load balancing mechanism with the existing message passing technology. The experiment is carried out on cluster of PC's divided into multiple LAN's using PMADE (Platform for Mobile agent distribution and execution). Preliminary experimental results demonstrated that the proposed framework is effective than the existing ones.

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Load management with mobile agents

Cited by 19 publications

References 8 publications

Parallel CBIR implementations with load balancing algorithms

Parallel CBIR implementations with load balancing algorithms

Reducing Response Time with Dynamic Load Balancing and Agent Pool in Multi-Agent System

A Framework for Distributed Dynamic Load Balancing in Heterogeneous Cluster

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