A dynamic load dispersion algorithm for load-balancing in a heterogeneous grid system

Acker, D.S.; Kulkarni, Sarvesh

doi:10.1109/sarnof.2007.4567375

Cited by 14 publications

(9 citation statements)

References 4 publications

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“…There are several inspiring load balancing approaches which have presented interesting results. Some of them are proposed for distributed systems [8], grid [9], [10], P2P systems [11], [12], and also for cloud computing systems [13], [14], and heterogeneous computing systems [15], [16], [17]. The main idea behind the considered challenge is the effective method for task assignment.…”

Section: Related Workmentioning

confidence: 99%

A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems

Benchara¹,

Youssfi²

2019

IJACSA

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The aim of this paper is to present a load balancing middleware for parallel and distributed systems. The great challenge is to balance the tasks between heterogeneous distributed nodes for parallel and distributed computing models based distributed systems, by the way to ensure HPC (High performance computing) of these models. Accordingly, the proposed middleware is based on mobile agent team work which implements an efficient method with two strategies: (i) Load balancing Strategy that determines the node tasks assignment based on node performance, and (ii) Rebalancing Strategy that detects the unbalanced nodes and enables tasks migration. The paper focuses on the proposed middleware and its cooperative mobile agent team work model strategies to dynamically balance the nodes, and scale up distributed computing systems. Indeed, some experimental results that highlight the performance and efficiency of the proposed middleware are presented.

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Section: Related Workmentioning

confidence: 99%

A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems

Benchara¹,

Youssfi²

2019

IJACSA

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“…We denote this term ΔLi. (13) e) Determine the required migrations in order to rebalance de distributed system…”

Section: Rebalancing Proceduresmentioning

confidence: 99%

“…In other works, authors proposed to transmit a constant number of loads [10,11] to balance the system. To carry the loads in a distributed system, the authors have used in [12,13] a mobile agent, which migrate the loads from overloaded nodes to under loaded ones and considering that nodes are homogeneous. In this paper, our approach is to present, first, the parallel virtual machine model where we have implemented the proposed load balancing algorithm.…”

Section: Introductionmentioning

confidence: 99%

Efficient load balancing algorithm for distributed systems using mobile agents

Youssfi¹,

Bouattane²,

Bensalah³

2015

astp

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In this paper, we present a new load balancing algorithm for parallel virtual architectures based on mobile agents. The proposed model is based on a reference diagnostic test performed by the host agent at the deployment time of the parallel application. This diagnostic test allows evaluating the computation performance and the communication latency of each node of the distributed system. The parallel tasks to execute are assigned to the distributed virtual processing units (VPUs) according to the performance offered by each node. The VPUs, represented by mobile agents, are associated in a parallel virtual layer, according to the parallel architecture topology required by the application. This model can also use metadata, of the parallel tasks to be distributed, to estimate more accurately the required times to perform the current parallel task. This feature allows predicting the performance offered by the distributed system according to the selected configuration of the selected computational model. When the system detects unbalanced loads, during the execution of any iterative computation, the system determines the required migrations of the VPUs from overloaded to under loaded nodes in order to keep the distributed system in a perfect balanced stat. To describe the proposed approach, the established mathematical model and a SPMD parallel application example are presented to prove the effectiveness of the proposed model. 246M. Youssfi, O. Bouattane and M. O. Bensalah

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“…al. [9] proposed a control protocol to obtain neighbor nodes information by periodically query and store the information of its neighboring nodes to assist in formulating the job distribution decision. Information that are stored at one node increase along with the size of the system which cause the increase of communication overheads during information exchange.…”

Section: Related Workmentioning

confidence: 99%

Neighbor's load prediction for dynamic load balancing in a distributed computational environment

Lim

Hoong

Yeoh

2012

TENCON 2012 IEEE Region 10 Conference

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In distributed computing environment, divisible load technique is used to speedup the completion time of a parallel task by splitting a huge task into a smaller grain size jobs where jobs can be executed remotely by other nodes. Due to the heterogeneity of computing nodes, load balancing technique is employed to distribute workload evenly across distributed nodes in order to reduce the overall response time and maximize the resource utilization. Load information plays an important role in heterogeneous computing environment to formulate a job distribution decision. In this paper, we propose a dynamic load balancing algorithm where its information policy for those nodes that have an empty neighbors' list to discover and predict other neighbors' load information. Simulation results from various scenarios show that our approach able to reduce the overall average response time of each job.

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A dynamic load dispersion algorithm for load-balancing in a heterogeneous grid system

Cited by 14 publications

References 4 publications

A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems

A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems

Efficient load balancing algorithm for distributed systems using mobile agents

Neighbor's load prediction for dynamic load balancing in a distributed computational environment

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