Abstract
Grid computing is the enabling technology for high performance computing in scientific and large scale applications. Grid computing introduces a number of fascinating issues to resource management. Grid scheduling is a vital component of a Grid infrastructure. Reliability, efficiency (in terms of time consumption) and effectiveness in resource utilization are the desired quality attributes of Grid scheduling systems. Many algorithms have been developed for Grid scheduling. In our previous work, we proposed two scheduling algorithms (the Multilevel Hybrid Scheduling Algorithm and the Multilevel Dual Queue Scheduling Algorithm) for optimum utilization of CPUs in a Grid computing environment. In this paper, we propose two more flavours of Multilevel Dual Queue scheduling algorithms, i.e. the Dynamic Multilevel Dual Queue Scheduling Algorithm using Median and the Dynamic Multilevel Dual Queue Scheduling Algorithm using Square root. We evaluate our proposed Grid scheduling, in comparison to other well known scheduling algorithms, on an SGI super computer using parts of the ‘AuverGrid’ workload trace.
The main purpose of scheduling algorithms is to execute jobs optimally, i.e. with minimum average waiting, turnaround and response times. An extensive performance comparison is presented using real workload traces to evaluate the efficiency of the scheduling algorithms. To facilitate the research, a software tool has been developed which produces a comprehensive simulation of a number of Grid scheduling algorithms. The tool’s output is in the form of scheduling performance metrics. The experimental results, based on performance metrics, demonstrate that our proposed scheduling algorithms yield improvements in terms of performance and efficiency.
Our proposed scheduling algorithms also support true scalability, that is, they maintain an efficient approach when increasing the number of CPUs or nodes. This paper also includes a statistical analysis of the ‘AuverGrid’ real workload traces to show the nature and behavior of jobs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure, 2nd edn. Morgan-Kaufmann Publishers, San Francisco (2003)
Jang, S.H., Lee, J.-S.: Predictive Grid Process Scheduling Model in Computational Grid. In: Shen, H.T., Li, J., Li, M., Ni, J., Wang, W. (eds.) APWeb Workshops 2006. LNCS, vol. 3842, pp. 525–533. Springer, Heidelberg (2006)
Grid Scheduling Use Cases, http://www.ogf.org/documents/GFD.64.pdf
Dong, F., Akl, S.G.: Scheduling Algorithms for Grid Computing: State of the Art and Open Problems, Technical Report No. 2006-504, Queens University, Canada (2006)
Haines, S.: Pro Java EE 5 Performance Management and Optimization. Apress (2006)
Li, H., Buyya, R.: Model-Driven Simulation of Grid Scheduling Strategies. In: Third IEEE International Conference on E-Science and Grid Computing (2007)
Shah, S.N.M., Mahmood, A.K.B., Oxley, A.: Development and Performance Analysis of Grid Scheduling Algorithms. Communications in Computer and Information Science 55, 170–181 (2009)
Lu, L., Yang, S.: DIRSS-G: An Intelligent Resource Scheduling System for Grid Environment Based on Dynamic Pricing. International Journal of Information Technology 12(4), 120–127 (2006)
Huang, P., Peng, H., Lin, P., Li, X.: Static Strategy and Dynamic Adjustment: An Effective Method for Grid Task Scheduling. Journal of Future Generation Computer Systems 25(8), 392–884 (2009)
Krauter, K., Buyya, R., Maheswaran, M.: A taxonomy and survey of grid resource management systems for distributed computing. Software Practice and Experience 32(2), 135–164 (2002)
Buyya, R., Abramson, D., Giddy, J.: Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid. In: Proceedings, High Performance Computing in the Asia-Pacific Region, vol. 1, pp. 283–289 (2000)
Chunlin, L., Xiu, Z.J., Layuan, L.: Resource Scheduling with Conflicting Objectives in Grid Environments: Model and Evaluation. Journal of Network and Computer Applications 32(3), 760–769 (2009)
Shmueli, E., Feitelson, D.G.: Backfilling with look ahead to optimize the packing of parallel jobs. Journal of Parallel and Distributed Computing 65(9), 1090–1107 (2005)
Lawson, B., Smirni, E., Puiu, D.: Self-adaptive backfill scheduling for parallel systems. In: Proceedings of the International Conference on Parallel Processing (ICPP 2002), pp. 583–592 (2002)
Tsafrir, D., Etsion, Y., Feitelson, D.G.: Backfilling using system-generated predictions rather than user runtime estimates. IEEE Transactions on Parallel and Distributed Systems 18(6), 789–803 (2007)
Abawajy, J.H.: Job Scheduling Policy for High Throughput Grid Computing. In: Hobbs, M., Goscinski, A.M., Zhou, W. (eds.) ICA3PP 2005. LNCS, vol. 3719, pp. 184–192. Springer, Heidelberg (2005)
Mu’alem, A.W., Feitelson, D.G.: Utilization, Predictability, Workloads, and User Runtime Estimates in Scheduling the IBM SP2 with Backfilling. IEEE Transactions on Parallel and Distributed Systems 12(16), 529–543 (2001)
Rawat, S.S., Rajamani, L.: Experiments with CPU Scheduling Algorithm on a Computational Grid. In: IEEE International Advance Computing Conference, IACC 2009 (2009)
Sharma, R., Soni, V.K., Mishra, M.K.: An Improved Resource Scheduling Approach Using Job Grouping strategy in Grid Computing. In: 2010 International Conference on Educational and Network Technology (2010)
Laurence, T., Yang, M.G.: High-Performance Computing: Paradigm and Infrastructure. Wiley, Chichester (2005), ISBN: 978-0-471-65471-1
Matarneh, R.J.: Self-Adjustment Time Quantum in Round Robin Algorithm Depending on Burst Time of the Now Running Processes. American Journal of Applied Sciences 6(10), 1831–1837 (2009)
Tchernykh, A., Trystram, D., Brizuela, C., Scherson, I.: Idle regulation in non-clairvoyant scheduling of parallel jobs. Discrete Applied Mathematics 157(2), 364–376 (2009)
Feitelson, D.G.: Metric and workload effects on computer systems evaluation. IEEE Computer 36(9), 18–25 (2003)
Shah, S.N.M., Mahmood, A.K.B., Oxley, A.: Hybrid Scheduling and Dual Queue Scheduling. In: 2009 the 2nd IEEE International Conference on Computer Science and Information Technology, IEEE ICCSIT 2009 (2009)
Shah, S.N.M., Mahmood, A.K.B., Oxley, A.: Analysis and Evaluation of Grid Scheduling Algorithms using Real Workload Traces. In: The International ACM Conference on Management of Emergent Digital EcoSystems, MEDES 2010 (2010)
Li, H.: Workload dynamics on clusters and grids. The Journal of Supercomputing 47(1), 1–20 (2009)
Trace analysis report, http://gwa.ewi.tudelft.nl/pmwiki/reports/gwa-t-4/trace_analysis_report.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mehmood Shah, S.N., Bin Mahmood, A.K., Oxley, A. (2011). Dynamic Multilevel Dual Queue Scheduling Algorithms for Grid Computing. In: Mohamad Zain, J., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22170-5_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-22170-5_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22169-9
Online ISBN: 978-3-642-22170-5
eBook Packages: Computer ScienceComputer Science (R0)