A fully distributed Grid meta scheduling method for non dedicated resources

Barkallah, Haitham; Gzara, Mariem; Ben-Abdallah, Hanêne

doi:10.1109/wccais.2014.6916613

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…-Improved scalability/reliability: by avoiding dependency on centralized points and inducing maximum load distribution [28].…”

Section: ) Goalsmentioning

confidence: 99%

Evolution of the Distributed Computing Paradigms: a Brief Road Map

Barkallah¹

2017

IJCDS

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Today's computing development is being characterized by the rapid development of high speed networks and the increase in computing power. Computing is not any more limited to the supercomputers, PCs and laptops but also smart phones and tablets which are available for billions of users offering high computing performances at low cost and interconnected via Internet. This continuing technological development is leading the increase importance of the distributed computing paradigms and the apparition of new ones. This paper aims to review the most important distributed computing paradigms and the principal similarities and differences between them. This survey is a kind of a brief road map that would be useful for researchers, students, and commercial users.

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“…-Improved scalability/reliability: by avoiding dependency on centralized points and inducing maximum load distribution [28].…”

Section: ) Goalsmentioning

confidence: 99%

Evolution of the Distributed Computing Paradigms: a Brief Road Map

Barkallah¹

2017

IJCDS

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“…In [15], an excellent survey on Grid resource allocation mechanisms is presented in [24,25]. As examined in these detailed works, some of the proposed methods use agents [5], [11], [14], [26 -29] to take profit from their decentralized, autonomous, and interacting character and thus avoid the "single point of failure". Some methods use genetic algorithms [5 -7], [30] as a means to approximate solutions in polynomial complexity of the problem that can "evolve" during the operation of the parallel computing system.…”

Section: Related Workmentioning

confidence: 99%

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2016

IJGCA

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Load balancing functionalities are crucial for best Grid performance and utilization. Accordingly,this paper presents a new meta-scheduling method called TunSys. It is inspired from the natural phenomenon of heat propagation and thermal equilibrium. TunSys is based on a Grid polyhedron model with a spherical like structure used to ensure load balancing through a local neighborhood propagation strategy. Furthermore, experimental results compared to FCFS, DGA and HGA show encouraging results in terms of system performance and scalability and in terms of load balancing efficiency.

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“…The motivation behind this paperis based on the observation that the load balancing problem can be improved by simply improving the classical used models tree, star, and P2Pand further proposing a new one; a polyhedron sphere like model that was introduced for the first time in [14]. This logical model has the merit of providing optimized load balancing in a stateless context.…”

Section: Introductionmentioning

confidence: 99%

“…This topology/model defines how the different grid entities communicate and work in order to achieve the received jobs/tasks. R. Buyyaet al proclaimed that the choice of the right model for the resource management architecture plays a major role in its eventual (commercial) success [4].The motivation behind this paperis based on the observation that the load balancing problem can be improved by simply improving the classical used models tree, star, and P2Pand further proposing a new one; a polyhedron sphere like model that was introduced for the first time in [14]. This logical model has the merit of providing optimized load balancing in a stateless context.…”

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confidence: 99%

Topology Aware Load Balancing for Grids

Barkallah

Gzara

Ben-Abdallah

2017

IJGCA

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KEYWORDSGrid computing, meta-scheduling, distributed load balancing, topology-aware. 1.INTRODUCTIONGrid computing[1] extends existing distributed computing to a more unified and collaborative structure. It enables multiple computing resources, that are geographically distributed and owned by different individuals or organizations, to be logically coupled to form the illusion of a powerful super computer with infinite capacity [2].Scheduling and load balancingare essential grid software infrastructure services. Theseservices assigntasks to nodes(i.e. computing resources) and transfer tasks from overloaded to under-loaded nodesin orderto maximizeresource utilization on one hand,and minimizing the total task's execution time on the other hand. Considering the grid load balancing problem, several solutions have been proposed using different methods and strategies, e.g., [3] Among the most critical issues pertaining to grids is how to manage the resources [4]. In the proposed solution, the grid resources are organized according to a logical topology called theresource managementmodel [4]. This topology/model defines how the different grid entities communicate and work in order to achieve the received jobs/tasks. R. Buyyaet al. proclaimed that the choice of the right model for the resource management architecture plays a major role in its eventual (commercial) success [4].The motivation behind this paperis based on the observation that the load balancing problem can be improved by simply improving the classical used models tree, star, and P2Pand further proposing a new one; a polyhedron sphere like model that was introduced for the first time in [14]. This logical model has the merit of providing optimized load balancing in a stateless context. It guarantees a high level of decentralization and scalability of the load balancing process leading tobetter resource utilization rates and minimum tasks execution time. Therefore,this work proposes adecentralizedtopology-awareload balancing solutionfor independent tasks in a grid environment

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A fully distributed Grid meta scheduling method for non dedicated resources

Cited by 3 publications

References 11 publications

Evolution of the Distributed Computing Paradigms: a Brief Road Map

Evolution of the Distributed Computing Paradigms: a Brief Road Map

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Topology Aware Load Balancing for Grids

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