A Fuzzy Reputation Based Ant Algorithm for Grid Scheduling

Zhou, Zhurong; Deng, Wei; Lu, Linrui

doi:10.1109/cso.2009.33

Cited by 4 publications

(3 citation statements)

References 3 publications

(2 reference statements)

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“…A fuzzy reputation-based ant algorithm for Grid scheduling has been designed in [42]. A fuzzy logic trust model for trust value aggregation through fuzzification has been used.…”

Section: Resource Scheduling With Securitymentioning

confidence: 99%

A hyper-heuristic approach for resource provisioning-based scheduling in grid environment

2015

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Grid computing being immensely based on the concept of resource sharing has always been closely associated with a lot many challenges. Growth of Resource provisioning-based scheduling in large-scale distributed environments like Grid computing brings in new requirement challenges that are not being considered in traditional distributed computing environments. Resources being the backbone of the system, their efficient management plays quite an important role in its execution environment. Many constraints such as heterogeneity and dynamic nature of resources need to be taken care as steps toward managing Grid resources efficiently. The most important challenge in Grids being the job-resource mapping as per the users' requirement in the most secure way. The mapping of the jobs to appropriate resources for execution of the applications in Grid computing is found to be an NP-complete problem. Novel algorithm is required to schedule the jobs on the resources to provide reduced execution time, increased security and reliability. The main aim of this paper is to present an efficient strategy for secure scheduling of jobs on appropriate resources. A novel particle swarm optimization-based hyper-heuristic resource scheduling algorithm has been designed and used to schedule jobs effectively on available resources without violating any of the security norms. Performance of the proposed algorithm has also been evaluated through the GridSim toolkit. We have compared our resource scheduling 123 R. Aron et al.algorithm with existing common heuristic-based scheduling algorithms experimentally. The results thus obtained have shown a better performance by our algorithm than the existing algorithms, in terms of giving more reduced cost and makespan of user's application being submitted to the Grids.

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“…A fuzzy reputation-based ant algorithm for Grid scheduling has been designed in [42]. A fuzzy logic trust model for trust value aggregation through fuzzification has been used.…”

Section: Resource Scheduling With Securitymentioning

confidence: 99%

A hyper-heuristic approach for resource provisioning-based scheduling in grid environment

2015

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“…Other proposals have involved distributed solutions that use intelligent agents, ant colonies, genetic algorithms, etc. For example, [24] proposes a scheduling algorithm using ant colonies based on a node reputation fuzzy model to make better decisions. The algorithm proposed in [25] is focused on monitoring resources to distribute tasks by balancing and adjusting the load at the nodes.…”

Section: Existing Approaches To the Grid Scheduling Problemmentioning

confidence: 99%

A Multiagent-Based Approach to the Grid-Scheduling Problem

Solar

Rojas²,

Mendoza³

et al. 2012

CLEIej

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Computer grids are systems containing heterogeneous, autonomous and geographically distributed nodes. The proper functioning of a grid depends mainly on the efficient management of grid resources to carry out the various jobs that users send to the grid. This paper proposes an algorithm that uses intelligent agents in each node to perform global scheduling in a collaborative and coordinated way. The algorithm was implemented in a grid simulation environment that allows the incorporation of intelligent agents. This simulation environment was designed and developed to run and analyze the behavior of the proposed algorithm, which outperforms the numerical performance of two well-known algorithms in terms of balancing the load and making use of the grid's capacity without giving preference to any node.

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“…Authors illustrated that GA performs better than TS and SA for scheduling of the jobs to exact resources but hybrid heuristic algorithms perform better than GA approach as it minimizes the time required for scheduling the job [5]. A fuzzy reputation based ant algorithm for Grid scheduling has been designed in [14]. Authors used fuzzy logic trust model for trust value aggregation through fuzzification.…”

Section: Related Workmentioning

confidence: 99%

Hyper-heuristic Based Resource Scheduling in Grid Environment

Aron

Chana

Abraham

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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Abstract-An efficient management of the resources in Grid computing crucially depends on the efficient mapping of the jobs to resources according to the user's requirements. Grid resources scheduling has become a challenge in the computational Grid. The mapping of the jobs to appropriate resources for execution of the application in Grid computing is an NP-Complete problem. In this paper, hyper-heuristic based resource scheduling algorithm is designed to effectively schedule the jobs on available resources in a Grid environment. The performance of the proposed algorithm is evaluated using the GridSim toolkit. Empirical results illustrate that our algorithm outperformed the existing algorithm by minimizing cost and makespan of user's submitted applications.

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A Fuzzy Reputation Based Ant Algorithm for Grid Scheduling

Cited by 4 publications

References 3 publications

A hyper-heuristic approach for resource provisioning-based scheduling in grid environment

A hyper-heuristic approach for resource provisioning-based scheduling in grid environment

A Multiagent-Based Approach to the Grid-Scheduling Problem

Hyper-heuristic Based Resource Scheduling in Grid Environment

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