A Survey on Dynamic Job Scheduling in Grid Environment Based on Heuristic Algorithms
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paper_title: Ten actions when Grid scheduling: the user as a Grid scheduler

paper_content:

In this chapter we present a general architecture or plan for scheduling on a Grid. A Grid scheduler (or broker) must make resource selection decisions in an environment where it has no control over the local resources, the resources are distributed, and information about the systems is often limited or dated. These interactions are also closely tied to the functionality of the Grid Information Services. This Grid scheduling approach has three phases: resource discovery, system selection, and job execution. We detail the steps involved in each phase.
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paper_title: An Improved Genetic Algorithm with Limited Iteration for Grid Scheduling

paper_content:

In grid environment the numbers of resources and tasks to be scheduled are usually variable. This kind of characteristics of grid makes the scheduling approach a complex optimization problem. Genetic algorithm (GA) has been widely used to solve these difficult NP-complete problems. However the conventional GA is too slow to be used in a realistic scheduling due to its time-consuming iteration. This paper presents an improved genetic algorithm for scheduling independent tasks in grid environment, which can increase search efficiency with limited number of iteration by improving the evolutionary process while meeting a feasible result.
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Title: A Survey on Dynamic Job Scheduling in Grid Environment Based on Heuristic Algorithms

Section 1: Introduction
Description 1: Introduce the fundamentals of grid computing, its differentiators from conventional high-performance computing, and the role of heuristic algorithms in job scheduling within grid environments.

Section 2: Grid Scheduling Process
Description 2: Describe the phases involved in the grid scheduling process: resource discovery, information gathering, and job execution, including the steps involved in each phase.

Section 3: Heuristic Algorithms for Job Scheduling in Grid
Description 3: Discuss various heuristic algorithms used for job scheduling in grid environments, such as Opportunistic Load Balancing (OLB), Max-min, Min-min, Minimum Execution Time (MET), Minimum Completion Time (MCT), and others.

Section 4: Conclusion
Description 4: Summarize the survey, emphasizing key findings, the effectiveness of heuristic algorithms in grid job scheduling, and potential areas for future research.