An Adaptive Counting Job Scheduling algorithm for grid computing

International Journal of Computer Trends and Technology (IJCTT)          
© 2016 by IJCTT Journal
Volume-32 Number-1
Year of Publication : 2016
Authors : S. Jagadesan, M.Vanitha


S. Jagadesan, M.Vanitha "An Adaptive Counting Job Scheduling algorithm for grid computing". International Journal of Computer Trends and Technology (IJCTT) V32(1):36-43, February 2016. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
In contrast to the traditional notion of using supercomputers, grid computing is proposed. Distributed computing supports resource sharing. Parallel computing supports computing power. Grid computing aims to harness the power of both distributed computing and parallel computing. The goal of grid computing is to aggregate idle resources on the Internet such as significant Processing Unit (CPU) cycles and storage spaces to facilitate utilization.. Grid technology, which connects a number of personal computer clusters with high speed networks, can achieve the same computing power as a supercomputer does, also with a lower cost. However, grid is a heterogeneous system. Scheduling independent tasks on it is more complicated. In order to utilize the power of grid completely, we need an efficient job scheduling algorithm to assign jobs to resources in a grid. This project proposes an Adaptive Scoring Job Scheduling algorithm (ASJS) for the grid environment. Compared to other methods, it can decrease the completion time of submitted jobs, which may compose of computing-intensive jobs and dataintensive jobs.

[1] Buyya1, James Broberg, AndrzejGoscinski, Cloud Computing: Principles and Paradigms, John Wiley & Sons, Inc., 2011.
[2] Ruay-Shiung Chang, Jih-Sheng Chang, Po-Sheng Lin, Balanced job assignment based on ant algorithm for computing grids, in: Asia-Pacific Service Computing Conference, 11–14 December 2007, pp. 291–295.
[3] M. Dorigo, Optimization, learning and natural algorithms, Ph.D. Thesis, Dipartimeto di Elettronica, Politecnico di Milano, Italy, 1992 (in Italian).
[4] Ye Huang, NikBessis, Peter Norrington, Pierre Kuonen, Beat Hirsbrunner, Exploring decentralized dynamic scheduling for grids and clouds using the community-aware scheduling algorithm, Future Generation Computer Systems. Available online 13 May 2011.
[5] E.L. Lawler, J.K. Lenstra, A.H.G. Rinnooy-Kan, D.B. Shmoys (Eds.), The Traveling Salesman Problem, Wiley, New York, 1985..
[6] Syed Nasir Mehmood Shah, Ahmad Kamil Bin Mahmood, Alan Oxley, Dynamic multilevel hybrid scheduling algorithms for grid computing, Procedia Computer Science 4 (2011) 402– 411.
[7] D. Saha, D. Menasce, S. Porto, Static and dynamic processor scheduling disciplines in heterogeneous parallel architectures, Journal of Parallel and Distributed Computing 28 (1) (1995) 1– 18.
[8] E. Salari, K. Eshghi, An ACO algorithm for graph coloring problem, in: Congress on Computational Intelligence Methods and Applications, December 2005, pp. 15–17.
[9] Abraham Silberschatz, Peter Baer Galvin, Greg Gagne, Operating System Concepts, eighth ed., John Wiley & Sons, 2011.
[10] A Somayeh., P Hossein., M Notes in Computer Science, vol. 2790, 2003, pp. 169-180Somayeh.,(2010), ‘The impact of data replication on job scheduling performance in hierarchical data grid ‘,International journal on applications graph theory in wireless ad hoc networks and sensor networks, Vol.2, No.3
[11].D. Paranhos, W. Cirne, F. Brasileiro, ‘Trading cycles for information: using replication to schedule bag-to-tasks applications on computational grids’,International Conference on Parallel and Distributed Computing (Euro-Par), Lecture
[12].H Yuan., X Qin., Li X., M HWu, (2005),‘An improved ant algorithm for job scheduling in gird computing’, in: Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vol. 5, 18-21, pp. 2957-2967.
[13].Ruay-Shiung Chang , Chih-Yuan Lin, Chun-Fu Lin, ‘An Adaptive Scoring Job Scheduling algorithm for grid computing’, Information Sciences 207 (2012) 79-89.
[14].Ruay-Shiung Chang, Jih-Sheng Chang, Po-Sheng Lin,’ An ant algorithm for balanced job scheduling in grids’, Future Generation Computer Systems 25(2009) 20-27
[15]. N M Shah ., M N B Zakaria., H Nazleein., A K B Mahmood., N Ken.,(2012), ‘Design and Evaluation of Agent Based Prioritzed Dynamic Round Robin Scheduling algorithm for computational grids’, AARI Procedia 1, pp. 531-543.
[16].S Wang., I Hsu, Z I Huang., (2005), ‘Dynamic scheduling methods for computational grid environment’, International Conference on Parallel and Distributed Systems.
[17].Wei L., Zhang X., Li Y., Li Y,(2012), ‘An improved ant algorithm for grid task scheduling strategy’, Physics Procedia 2, pp.1974- 1981.
[18].Li Y., Yang Y. and Zhou L. (2009), ‘A hybrid load balancing strategy of sequential tasks for grid computing Environments’, Future Generation Computer Systems, Vol.25, pp. 819-828

Grid computing, Resources, Scheduling Replication.