Abstract
Effective and efficient job scheduling is an important aspect of Grid computing. Task scheduling becomes more complicated in a Grid environment, due to geographically distribution, heterogeneity and dynamic nature of grid resources. In this paper, a new computational scheduling policy called Multilevel Feedback Queue (MLFQ) scheduling, which is designed to support the allocation of resources for gridlets (jobs) is proposed. Gridlets provided by the users are assigned to processing elements (PEs), and gridlets whose remaining service time is shifted between queues of the MLFQ scheduler to get completed. In MLFQ, the total architecture is divided into multiple prioritized queues. This approach provides gridlets which starve in the lower priority queue for long time to get resources. As a result, the response time of the starved gridlets decreases and overall turnaround time of the scheduling process decreases. This scheduling policy is simulated using Alea GridSim toolkit to test the performance.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure, IInd edn. Elsevier and Morgan Kaufmann Press (2004)
Hoschek, W., Jaen-Martinez, J., Samar, A., Stockinger, H., Stockinger, K.: Data Management in an International Data Grid Project. In: Buyya, R., Baker, M. (eds.) GRID 2000. LNCS, vol. 1971, pp. 77–90. Springer, Heidelberg (2000)
Buyya, R., Steve Chapin, S., DiNucci, D.: Architectural Models for Resource Management in the Grid. In: IEEE/ACM International Workshop on Grid Computing (2000)
Mohammad Khanli, L., Analoui, M.: Resource Scheduling in Desktop Grid by Grid-JQA. In: The IEEE 3rd International Conference on Grid and Pervasive Computing (2008)
Mohammad Khanli, L., Analoui, M.: Grid_JQA: A QoS Guided Scheduling Algorithm for Grid Computing. In: The 6th IEEE International Symp. on Parallel and Distributed Computing (2007)
Dong, F., et al.: A Grid Task Scheduling Algorithm Based on QoS Priority Grouping. In: Proc. of the 5th IEEE International Conf. on Grid and Cooperative Computing (2006)
Etminani, K., Naghibzadeh, M.: A Min-min Max-min Selective Algorithm for Grid Task Scheduling. In: The 3rd IEEE/IFIP International Conf. on Internet, Uzbekistan (2007)
Hoganson, K.: In: Reducing MLFQ Scheduling Starvation with Feedback and Exponential Averaging Consortium for Computing Sciences in Colleges, Southeastern Conference, Georgia (2009)
He, X., Sun, X.-H., Laszewski, G.V.: QoS Guided Min-min Heuristic for Grid Task Scheduling. J. Computer Science and Technology 18, 442–451 (2003)
Mohammad Khanli, L., Analoui, M.: Resource Scheduling in Desktop Grid by Grid-JQA. In: The 3rd IEEE International Conf. on Grid and Pervasive Computing (2008)
Mohammad Khanli, L., Analoui, M.: Grid_JQA: A QoS Guided Scheduling Algorithm for Grid Computing. In: The 6th IEEE International Symp. on Parallel and Distributed Computing (2007)
Dong, F., Luo, J., et al.: A Grid Task Scheduling Algorithm Based on QoS Priority Grouping. In: Proc. of 5th IEEE International Conf. on Grid and Cooperative Computing (2006)
Ullah Munir, E., Li, J., Shi, S.: QoS Sufferage Heuristic for Independent Task Scheduling. Grid J. Information Technology 6(8), 1166–1170 (2007)
Etminani, K., Naghibzadeh, M.: A Min-min Max-min Selective Algorithm for Grid Task Scheduling. In: 3rd IEEE/IFIP International Conf. on Internet, Uzbekistan (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer India
About this paper
Cite this paper
Chouhan, D., Dilip Kumar, S.M., Vijaya Kumar, B.P. (2013). Multilevel Feedback Queue Scheduling Technique for Grid Computing Environments. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_1
Download citation
DOI: https://doi.org/10.1007/978-81-322-0740-5_1
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-0739-9
Online ISBN: 978-81-322-0740-5
eBook Packages: EngineeringEngineering (R0)