Abstract
Grid can be thought of as a network of heterogeneous interactive computational resources from multiple administrative domains that collectively works towards achieving a common goal. Inefficient scheduling and work load distribution among the various computational resources in a network is one of the major issues that affect grid performance. Some resources may tend to be heavily loaded while some are kept idle, thus affecting the overall performance of the grid. Balanced load scheduling is thus a serious issue which needs to be properly addressed in the grid. Balancing the load affects some factors like job execution and service selection, thus making it all the more necessary to be well implemented. In this paper we propose a distributed, dynamic and balanced load scheduling scheme on grids which considers deadline of jobs. Our approach for solving the problem goes as follows: The resources first check their state and make a request to the Grid Broker based on the change in state of their load. Then, the Grid Broker assigns Jobs (Gridlets) among resources, provides schedules for load balancing and selecting best node of a resource for execution under the given deadline. We applied our balanced job scheduling mechanisms into a popular simulation platform called GridSim Tool kit. Experimental results prove that our balanced job scheduling mechanism can reduces the make span, failure tendency, and resubmitted time by maximizing the throughput.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Xu C (1997) Load Balancing in parallel comp: theory and practice. Boston
Yagoubi B, Slimani Y (2007) Task load balancing strategy in grid environment. J Compt Sci 3(3):186–194
Yagoubi B (2007) Load balancing strategy in grid environment. J IT App 4:285–296
Cao J (2004) Self-organizing agents for grid load balancing. In: 5th IEEE/ACM international workshop on grid computing
Hao Y (2012) Enhanced load balancing mechanism based on deadline control on GridSim. FGCS 28:657–665
Naik KJ (2012) Scheduling tasks on most suitable fault tolerant resource for execution in computational grid. IJGDC 5(3)
Naik KJ (2013) A novel fault-tolerant task scheduling algorithm for computational grid (15th ICACT-978-1-4673-2818-0/13 ©2013 IEEE)
Yagoubi B, Slimani Y (2006) Dynamic load balancing strategy for grid computing. Eng Technol 90–95
http://www.lenders.ch/publications/books/thesis.pdf [visit:2011–04-01]
Erdil D, Lewis M (2010) Dynamic grid load sharing with adaptive dissemination protocols. J Supercomput 1–28
Ludwig S, Moallem A (2011) Swarm intelligence approaches for grid load balancing. J Grid Comp 1–23
Buyya R, Murshed M (2012) GridSim: practice and experience 14:13–15
Qureshi K, Rehman A, Manuel P (2010) Enhanced GridSim architecture with load balancing. J Supercomput 1–11
http://www.buyya.com/GridSim/ [visit:2011-1-27]
Howell F (1998) SimJava: a discrete Java event simulation package with applications in computer systems modelling. In: 1st international conference on web-based modelling and simulation, Society for Computer Simulation, San Diego, CA
Li Y (2009) A hybrid load balancing strategy of sequential tasks for grid computing environment. FGCS (ISSN: 0167-739X) 25(8):819–828
Subrata R (2008) Game-theoretic approach for load balancing in computational grids. IEEE Trans Parallel Distrib Sys 19(1):66–76
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this paper
Cite this paper
Jairam Naik, K., Jagan, A., Satyanarayana, N. (2017). An Enhanced Mechanism for Balanced Job Scheduling Based on Deadline Control in Computational Grid. In: Attele, K., Kumar, A., Sankar, V., Rao, N., Sarma, T. (eds) Emerging Trends in Electrical, Communications and Information Technologies. Lecture Notes in Electrical Engineering, vol 394. Springer, Singapore. https://doi.org/10.1007/978-981-10-1540-3_1
Download citation
DOI: https://doi.org/10.1007/978-981-10-1540-3_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-1538-0
Online ISBN: 978-981-10-1540-3
eBook Packages: EngineeringEngineering (R0)