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An improved approach for load balancing among heterogeneous resources in computational grids

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Abstract

In recent days, due to the rapid technological advancements, the grid computing has become an important area of research in distributed systems. The load balancing is a very important and complex problem in grid computing. In this paper, we propose a dynamic-distributed load-balancing technique called the improved load balancing on enhanced GridSim with deadline control (IEGDC) for computational grids. Here, we provide a new mechanism of scheduling to enhance the utilization of the resources and to prevent the resource overloading. A selection method for scheduling by considering the state of resource bandwidth and capacity of various resources is presented. We simulate the proposed load-balancing strategy on the GridSim platform. The proposed mechanism on comparison is found to outperform the existing schemes in terms of response time, resubmitted time, finished and unfinished Gridlets. The simulation results are presented.

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References

  1. Khanli LM, Razzaghzadeh S, Zargari SV (2012) A new step toward load balancing based on competency rank and transitional phases in grid networks. Future Gener Comp Syst 28:682–688

    Article  Google Scholar 

  2. Malarvizhi N, Uthariaraj VR (2009) Hierarchical load balancing scheme for computational intensive jobs in grid computing environment. In: Proceedings of the first IEEE international conference on advanced computing, pp 97–104

  3. Yagoubi B, Lilia HT, Maussa HS (2006) Load balancing in grid computing. Asian J Inf Technol 5(10):1095–1103

    Google Scholar 

  4. Shah R, Veeravalli B, Misra M (2007) On the design of adaptive and decentralized load-balancing algorithms with load estimation for computational grid environments. IEEE Trans Parallel Distrib Syst 18(12):1675–1686

    Article  Google Scholar 

  5. Cao J (2004) Self-organizing agents for grid load balancing. In: Proceedings of the fifth IEEE/ACM international workshop on grid computing, GRID′04, Pittsburgh, PA

  6. Erdil D, Lewis M (2012) Dynamic grid load sharing with adaptive dissemination protocols. J Supercomput:1–28

  7. Subrata R, Zomaya AY, Landfeldt B (2008) Game-theoretic approach for load balancing in computational grids. IEEE Trans Parallel Distrib Syst 19(1):66–76

    Article  Google Scholar 

  8. Ludwig S, Moallem A (2011) Swarm intelligence approaches for grid load balancing. J Grid Comput:1–23

  9. Zikos S, Karatza HD (2009) Communication cost effective scheduling policies of nonclairvoyant jobs with load balancing in a Grid. J Syst Softw 82:2103–2116

    Article  Google Scholar 

  10. Fernandes de Mello R, Senger LJ, Yang LT (2006) A routing load balancing policy for grid computing environments. In: Proceedings of the twentieth international conference on advanced information networking and applications (Aina′06), vol 1. pp 18–20

  11. Balasangameshwara J, Raju N (2012) A hybrid policy for fault tolerant load balancing in grid computing environments. J Netw Comput Appl 35:412–422

    Article  Google Scholar 

  12. Subrata R, Zomaya AY, Landfeldt B (2007) Artificial life techniques for load balancing in computational grids. J Comput Syst Sci 73:1176–1190

    Article  MATH  Google Scholar 

  13. Hao Y, Liu G, Wen N (2012) An enhanced load balancing mechanism based on deadline control on GridSim. Future Gener Comput Syst 28:657–665

    Article  Google Scholar 

  14. Yagoubi B, Slimani Y (2006) Dynamic load balancing strategy for grid computing. World Acad Sci, Eng Technol:90–95

  15. Qureshi K, Rehman A, Manuel P (2010) Enhanced GridSim architecture with load balancing. J Supercomput:1–11

  16. Bharadwaj V, Ghose D, Robertazzi TG (2003) Divisible load theory: a new paradigm for load scheduling in distributed systems. Clust Comput 6:7–17

    Article  Google Scholar 

  17. Anand L, Ghose D, Mani V (1999) ELISA: an estimated load information scheduling algorithm for distributed computing systems. Comput Math Appl 37:57–85

    Article  MathSciNet  MATH  Google Scholar 

  18. Li Y, Yang Y, Ma M, Jhou L (2009) A hybrid load balancing strategy of sequential tasks for grid computing environments. Future Gener Comput Syst 25:819–828

    Article  Google Scholar 

  19. Yan KQ, Wang SS, Wang SC, Chang CP (2009) Towards a hybrid load balancing policy in grid computing system. Expert Syst Appl 36:12054–12064

    Article  Google Scholar 

  20. Cao J, Spooner DP, Jarvis SA, Nudd GR (2005) Grid load balancing using intelligent agents. Future Gener Comput Syst 21:135–149

    Article  Google Scholar 

  21. Wu J, Xu X, Zhang P, Liu C (2011) A novel multi-agent reinforcement learning approach for job scheduling in grid computing. Future Gener Comput Syst 27:430–439

    Article  Google Scholar 

  22. Zheng Q, Tham CK, Veeravalli B (2008) Dynamic load balancing and pricing in grid computing with communication delay. J Grid Comput 6:239–253

    Article  Google Scholar 

  23. Li K (2008) Optimal load distribution in nondedicated heterogeneous cluster and grid computing environments. J Syst Architect 54:111–123

    Article  Google Scholar 

  24. Murshed M, Buyya R, Abramson D (2001) GridSim: a toolkit for the modeling and simulation of global grids. Technical Report, Monash

    Google Scholar 

  25. http://www.buyya.com/gridsim/. Accessed 15 July 2013

  26. Sulistio A, Poduval G, Buyya R, Tham CK (2007) On incorporating differentiated levels of network service into GridSim. Future Gener Comput Syst 23:606–615

    Article  Google Scholar 

  27. Howell F, McNab R (1998) SimJava: a discrete event simulation package for Java with applications in computer systems modeling. In: Proceedings of the first international conference on web-based modelling and simulation, Society for Computer Simulation, San Diego, CA

  28. Yagoubi B, Slimani Y (2007) Task Load balancing strategy in grid environment. J Comput Sci 3(3):186–194

    Article  Google Scholar 

  29. Yagoubi B, Slimani Y (2007) Load balancing strategy in grid environment. J Inf Technol Appl 4:285–296

    Google Scholar 

  30. Behera I, Tripathy CR (2014) Performance modeling and analysis of mobile grid computing systems. Int J Grid Util Comput 5(1):11–20

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, 768018, India

    Deepak Kumar Patel & Chitaranjan Tripathy

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  1. Deepak Kumar Patel
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  2. Chitaranjan Tripathy
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Correspondence to Deepak Kumar Patel.

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Patel, D.K., Tripathy, C. An improved approach for load balancing among heterogeneous resources in computational grids. Engineering with Computers 31, 825–839 (2015). https://doi.org/10.1007/s00366-014-0391-9

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  • DOI: https://doi.org/10.1007/s00366-014-0391-9

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