Document Type : Technical Note


Computer Engineering Department, Kerman Branch, Islamic Azad University, IRAN.


Cloud computing is the latest technology that involves distributed computation over the Internet. It meets the needs of users through sharing resources and using virtual technology. The workflow user applications refer to a set of tasks to be processed within the cloud environment. Scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of suitable resources and assignment of workflows to them. Given the factors affecting their efficiency, these algorithms try to use resources optimally and increase the efficiency of this environment. The palbimm algorithm provides a scheduling method that meets the majority of the requirements of this environment and its users. In this article, we improved the efficiency of the algorithm by adding fault tolerance capability to it. Since this capability is used in parallel with task scheduling, it has no negative impact on the makespan. This is supported by simulation results in CloudSim environment.


Main Subjects

[1] Y. Luo and S. Zhou ,” Power Consumption Optimization Strategy of Cloud Workflow Scheduling Based on SLA” wseas transactions on systems, E-ISSN: 2224-2678 , Volume 13, 2014.
[2] S. Qaisar and K. Khawaja, ”cloud computing: network/security threats and countermeasures”, interdisciplinary journal of contemporary research in business - january 2012 vol 3, no 9.
[3] B. Rashidi and M. Sharifi and T. Jafari , “A Survey on Interoperability in the Cloud Computing Environments” Published Online July 2013 in MECS ( DOI: 10.5815/ijmecs.2013.06.03.
[4] P. Sareen, “ Cloud Computing: Types, Architecture, Applications, Concerns, Virtualization and Role of IT Governance in Cloud” , International Journal of Advanced Research in Computer Science and Software Engineering ,Volume 3, Issue 3, March 2013.
[5] M. soltanshahi and A. niknafs, " A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms", Ciência e Natura, v. 37 Part 2, p. 427−433, december 2015, DOI:
[6] D. Tracy, Braun, "A comparison of eleven static heuristics for mapping a class ofindependent tasks onto heterogeneous distributed computing systems", Journal of Parallel and Distributed computing , Volume 61, Issue 6, Pages 810 – 837, 2001.
[7] H. Chen, F. Wang, N. Helian and G. Akanmu, "User-priority guided Min-Min scheduling algorithm for load balancing in cloud computing," Parallel Computing Technologies (PARCOMPTECH), 2013 National Conference on, Bangalore, 2013, pp. 1-8. doi:10.1109/ParCompTech.2013.6621389,publisher:IEEE URL:
[8] S. Meraji and M. Salehnamadi , “A Batch Mode Scheduling Algorithm for Grid Computing” , J. Basic. Appl. Sci. Res., 3(4)173-181, 2013 © 2013, textroad Publication , ISSN 2090-4304 ,Journal of Basic and Applied Scientific Research ,
[9] T. Kokilavani, D.I. George Amalarethinam, “Load Balanced Min-Min Algorithm for Static Meta-Task Scheduling in Grid Computing”, International Journal of Computer Applications (0975 – 8887) , Volume 20– No.2, April 2011.
[10] P. Warstein and H. Situ and Z. Huang, “Load balancing in a cluster computer”, In proceeding of the seventh International Conference on Parallel and Distributed Computing, Applications and Technologies IEEE 2010.
[11] Er. Rajeev Mangla , Er. Harpreet Singh , “recovery and user priority based load balancing in cloud computing” , international journal of engineering sciences & research technology , ISSN: 2277-9655 Scientific Journal Impact Factor: 3.449(ISRA), Impact Factor: 2.114 , Mangla, 4(2): February, 2015.
[12] R.N.Calheiros, R.Ranjan, A.Beloglazov,C.A.F.De Rose and R. Buyya."Cloudsim:a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms.",Software: Practice and Experience, 41(1):23–50,2011.