Grouping Based Job Scheduling Algorithm Using Priority Queue and Hybrid Algorithm in Grid Computing

Rosemarry, Pinky; Singh, Ravinder; Singhal, Payal; Sisodia, Dilip

doi:10.5121/ijgca.2012.3405

Cited by 6 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Rosemarry et al [15], the authors proposed an enhanced approach based on tasks priorities for queue schedule where the performance parameters were tasks waiting time in queue and utilization rate for the grid available resources. The approach was introducing new clustering mechanism where ten priorities levels were identified, then, the new proposed scheduling is compared with other four conventional algorithms i. e., SJFs, FCFSs, RR and priority-based Scheduling.…”

Section: Related Workmentioning

confidence: 99%

Scheduling Algorithm for Grid Computing Using Shortest Job First with Time Quantum

Yosuf¹,

Mokhtar²,

Saeed³

et al. 2022

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

The grid computing is one of the strong initiatives and technologies that has been introduced in the last decade for improve the resources utilization, optimization and provide very high throughput computation for wide range of applications. To attain these goals an effective scheduling for grid systems is a vital issue to realize the intended performance. The processes scheduling could be executed in various methods and protocols that have been extensively address in the literature. This works utilized shortest process first (SPF) protocol which gives the shortest jobs the highest priorities. For longer jobs, it should have lower priorities and wait in the queue longer time. With too many smallest tasks reach the queue, the long tasks can't have an opportunity to be processed and the number of tasks continue growing in front of them, which is well-known issue called Starvations. In this work we introduce a new time quantum-based for shortest process first to avoid the starvation problem. The objective of the model is to optimize the utilization of resources by reducing end time of the job and enhancing performance of job scheduling. The model introduces fair treatment for all the processes. A simulation environment for the proposed model is developed and implemented. The results show that the quantum time-based solution has improved the starvation issues severely in terms of time delay, optimization of grid resources and fairness. The results show that SJF with time quantum outperform the SJF in terms of end time process, resources utilization, delay to transmission and Fair treatment for all the processes. But in term of waiting time Shortest Job First is better, SJF does not always minimize waiting time.

show abstract

Section: Related Workmentioning

confidence: 99%

Scheduling Algorithm for Grid Computing Using Shortest Job First with Time Quantum

Yosuf¹,

Mokhtar²,

Saeed³

et al. 2022

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

show abstract

“…Serve On Time algorithm proposed in [14] is based on the idea of combining all the dynamic multi tasks so that all the tasks will obtain the rights to be served as soon as possible. Group based Job Scheduling algorithm [15] provides an optimize algorithm to queue of the scheduler using various scheduling methods like Shortest Job First, First Come First Serve, Round Robin algorithms for jobs. [16] discusses concepts of resource scheduling and application scheduling and presents a classification of scheduling algorithms.…”

Section: Related Workmentioning

confidence: 99%

Job Scheduling Using Coupling in Grid

Anitha¹

2015

JCC

View full text Add to dashboard Cite

The grid computing main concern is to use the resources efficiently. For achieving this many grid resource scheduling algorithms are used for the efficient use of unused resources, especially CPU. The scheduling algorithms assign single complete job to a single resource. Instead, if these algorithms consider the degree of dependency among the modules of a job, they can be allocated parallel to the different resources. This reduces the completion time of the job and the resources can be utilized to its maximum extent. Towards this, the job scheduling using coupling algorithm is proposed. This algorithm puts forward the idea of considering the coupling degree while allocating the modules of a job parallel to different resources. In this algorithm, resource selection is done by using both its functional and non-functional properties. The algorithm works in 3 phases. It groups the interdependent modules of a job into different sets using coupling in the first phase. It checks the non-functional property i.e. availability of a resource using echo procedure in the second phase and in the third phase, the sets created in first phase, are allocated parallel to different available and matching resources. From the simulation results it is observed that job scheduling using coupling algorithm gives better performance in terms of reduced turnaround time as compared to First Come First Served, Largest Task First and Minimum Execution Time scheduling algorithms.

show abstract

“…This dynamic grouping strategy based on the processing requirements of each application, Grid resources availability and their processing capability and granularity size. In [9] Rosemarry et al states that, allocating large number of jobs to one resource will increase the processing time. So to avoid this situation during job grouping activity, the total number of jobs group should be created such that the processing loads among the selected resource are balance.…”

Section: Related Workmentioning

confidence: 99%

Cost-based Job grouping and Scheduling Algorithm for Grid computing Environments

Yadav¹,

Agarwal²,

Rastogi³

2014

IJCA

View full text Add to dashboard Cite

The integration of remote and diverse resources and the increasing computational needs of Grand challenges problems combined with faster growth of the internet and communication technologies leads to the development of global computational grids. Grid computing is a prevailing technology, which unites underutilized resources in order to support sharing of resources and services distributed across numerous administrative region. An efficient and effective scheduling system is essentially required in order to achieve the promising capacity of grids. The main goal of scheduling is to maximize the resource utilization and minimize processing time and cost of the jobs. In this research, the objective is to prioritize the jobs based on execution cost and then allocate over the resources with minimum cost by merging it with conventional job grouping strategy to provide solution for better and more efficient job scheduling which is beneficial to both user and resource broker. The proposed scheduling approach in grid computing employs a dynamic cost-based job scheduling algorithm for making efficient mapping of job to available resources in grid. It also improves communication to computation ratio (CCR) and utilization of available resources by grouping the user jobs before resource allocation. General TermsAlgorithm, GridSim.

show abstract

Grouping Based Job Scheduling Algorithm Using Priority Queue and Hybrid Algorithm in Grid Computing

Abstract: ABSTRACT

Cited by 6 publications

References 6 publications

Scheduling Algorithm for Grid Computing Using Shortest Job First with Time Quantum

Scheduling Algorithm for Grid Computing Using Shortest Job First with Time Quantum

Job Scheduling Using Coupling in Grid

Cost-based Job grouping and Scheduling Algorithm for Grid computing Environments

Contact Info

Product

Resources

About