Reliability Based Scheduling Model (RSM) for Computational Grids

Raza, Zahid; Vidyarthi, Deo Prakash

doi:10.4018/jdst.2011040102

Cited by 10 publications

(12 citation statements)

References 22 publications

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“…The completion time estimation depends on two factors: execution time 'E' of the module on a node and the intermodule communication time 'B' in form of data exchange between the modules of the job allocated on the nodes having a distance 'D' between them [7,14,20].…”

Section: Load Balancing Allocation (Lba) Methodsmentioning

confidence: 99%

“…makespan, reliability, availability, throughput, energy consumption for job scheduling in computational grid [6,7,14,[16][17][18]. Most of these models did scheduling with a single objective.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For makespan minimization, it is warranted to effectively deal with the load balancing as well [6]. Further, the heterogeneous hardware components of the grid are more prone to failure and therefore reliability of such systems decreases with the increase in the number of geographically distributed resources [7]. The heterogeneity of the system demands varying energy consumption based on their hardware profile [8].…”

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confidence: 99%

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An energy-efficient reliable grid scheduling model using NSGA-II

Kaushik

Vidyarthi

2015

Engineering with Computers

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parameters by effectively managing the available grid resources. In general, it is unusual to assume a single criterion for the decision making in a grid system which is governed by various related factors. The scheduling problem in the grid system may have several conflicting objectives, e.g., makespan, reliability, energy consumption, cost, security, etc., which need to be optimized simultaneously [1][2][3][4].The outcome values of different objectives, viz. execution time of any job, the energy consumption by the job and the reliability offered by the system to the job may vary from one allocation to another [5]. The distributed nature of grid resources and the dynamic nature of the grid workload make the makespan of the job unpredictable. For makespan minimization, it is warranted to effectively deal with the load balancing as well [6]. Further, the heterogeneous hardware components of the grid are more prone to failure and therefore reliability of such systems decreases with the increase in the number of geographically distributed resources [7]. The heterogeneity of the system demands varying energy consumption based on their hardware profile [8]. It necessitates choosing those nodes/machines that are able to execute the job quickly, reliably and with least energy consumption.Since these objectives are conflicting in nature, any approach adopted to optimize one objective may not result in the overall optimized solution with respect to other objectives. All the conflicting objectives need to be addressed simultaneously and the best way for this is to have the trade-off solutions with all the objectives [9, 10]. A good solution corresponding to all the objectives is desired. This solution may not offer the best of all the objectives, but certainly better when seen as a trade-off among the objectives. This approach is referred as multiobjective optimization technique [5]. As such, job scheduling in the grid is an NP-hard problem and traditional Abstract Job scheduling in computational grid is a complex problem and various heuristics and meta-heuristics have been proposed for the same. These approaches usually optimize specific characteristic parameters while allocating the jobs on the grid resources. Many a times, it is desired to optimize multiple parameters during job scheduling. Nondominated sorting genetic algorithm (NSGA-II) has been observed to be the best meta-heuristic to solve such multiobjective optimization problem. The proposed work applies NSGA-II for job scheduling in computational grid with three conflicting objectives: maximizing reliability of the system for job allocation, minimizing energy consumption and balancing the load on the system. Performance study of the proposed model is done by simulating it on some real data. The result indicates that the proposed model performs well with multiple objectives.

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Section: Load Balancing Allocation (Lba) Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

mentioning

confidence: 99%

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An energy-efficient reliable grid scheduling model using NSGA-II

Kaushik

Vidyarthi

2015

Engineering with Computers

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“…It also proposes a solution integrated with grid monitoring and optimization tool. Reliability-based scheduling is proposed in [28,30] with an objective of maximizing reliability. Reliability-based scheduling is proposed in [28,30] with an objective of maximizing reliability.…”

Section: Related Workmentioning

confidence: 99%

“…In , CG scheduling that gives priority to security is discussed. Reliability‐based scheduling is proposed in with an objective of maximizing reliability. Reliability‐based scheduling using modified GA is discussed in .…”

Section: Related Workmentioning

confidence: 99%

Maximizing availability for task scheduling in computational grid using genetic algorithm

Prakash

Vidyarthi

2014

Concurrency and Computation

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Computational grid provides a wide distributed platform for high-end compute intensive applications. Grid scheduling is often carried out to schedule the submitted jobs on the nodes of the grid so that some characteristic parameter is optimized. Availability of the computational nodes is one of the important characteristic parameters and measures the probability of the node availability for job execution. This paper addresses the availability of the grid computational nodes for the job execution and proposes a model to maximize it. As such, the task scheduling problem in grid is nondeterministic polynomial-time hard, and often, metaheuristics techniques are applied to solve it. Genetic algorithm, a metaheuristic technique based on evolutionary computation, has been used to solve such complex optimization problem. This work proposes a technique for the grid scheduling problem using genetic algorithm with the objective to maximize availability. Simulation experiment, to evaluate the performance of the proposed algorithm, is conducted, and results reveal the effectiveness of the model. A comparative study has also been performed.

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A model for resource management in computational grid using sequential auction and bargaining procurement

Kaushik

Vidyarthi

2017

Cluster Comput

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Reliability Based Scheduling Model (RSM) for Computational Grids

Cited by 10 publications

References 22 publications

An energy-efficient reliable grid scheduling model using NSGA-II

An energy-efficient reliable grid scheduling model using NSGA-II

Maximizing availability for task scheduling in computational grid using genetic algorithm

A model for resource management in computational grid using sequential auction and bargaining procurement

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