Practical Scheduling Algorithms of Independent Tasks on Tree-Based Grid Computing Platform

Around the world there have recently been new and more powerful computing platforms created that can be used to work with computer science problems. Some of these problems that are dealt with are real problems of the industry; most are classified by complexity theory as hard problems. One such problem is the vehicle routing problem with time windows (VRPTW). The computational Grid is a platform which has recently ventured into the treatment of hard problems to find the best solution for these. This chapter presents a genetic algorithm for the vehicle routing problem with time windows. The algorithm iteratively applies a mutation operator, first of the intelligent type and second of the restricting type. The algorithm takes advantage of Grid computing to increase the exploration and exploitation of the solution space of the problem. The Grid performance is analyzed for a genetic algorithm and a measurement of the latencies that affect the algorithm is studied. The convenience of applying this new computing platform to the execution of algorithms specially designed for Grid computing is presented.

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Comparative Study of Job Scheduling Algorithms in Grid Computing

Advances in Power Systems and Energy Management - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-15-7504-4_1 ◽

2021 ◽

pp. 1-7

Author(s):

M. Ashok Kumar ◽

T. Sai Srinivas ◽

Raksha Pandey

Keyword(s):

Comparative Study ◽

Grid Computing ◽

Job Scheduling ◽

Scheduling Algorithms

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Balanced Job Scheduling Based on Ant Algorithm for Grid Network

International Journal of Grid and High Performance Computing ◽

10.4018/jghpc.2010092803 ◽

2010 ◽

Vol 2 (1) ◽

pp. 34-50 ◽

Cited By ~ 1

Author(s):

Nikolaos Preve

Keyword(s):

Grid Computing ◽

Ant Colony Optimization ◽

Job Scheduling ◽

Scheduling Algorithm ◽

Scheduling Algorithms ◽

Experimental Results ◽

Ant Algorithm ◽

Entire System ◽

Grid Environment ◽

Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this article is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

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The Cost-Based Resource Management in Combination with Qos For Grid Computing

Quantitative Quality of Service for Grid Computing ◽

10.4018/978-1-60566-370-8.ch004 ◽

2011 ◽

pp. 74-90

Author(s):

Chuliang Weng ◽

Jian Cao ◽

Minglu Li

Keyword(s):

Resource Management ◽

Grid Computing ◽

Scheduling Algorithms ◽

Computational Grid ◽

Online Scheduling ◽

Management Issue ◽

Job Assignment ◽

The Cost

In the grid context, the scheduling can be grouped into two categories: offline scheduling and online scheduling. In the offline scheduling scenario, the sequence of jobs is known in advance, scheduling is based on information about all jobs in the sequence. While, in the online scheduling scenario a job is known only after all predecessors have been scheduled, and a job is scheduled only according to information of its predecessors in the sequence. This chapter focuses on resource management issue in the grid context, and introduces the two cost-based scheduling algorithms for offline job assignment and online job assignment on the computational grid, respectively.

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Design of a multi-agent opportunistic grid computing platform

Multiagent and Grid Systems ◽

10.3233/mgs-140223 ◽

2015 ◽

Vol 10 (4) ◽

pp. 199-212

Author(s):

Raymond Muranganwa ◽

Mamello Thinyane

Keyword(s):

Grid Computing ◽

Computing Platform ◽

Multi Agent

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