A New Algorithm for Minimizing Makespan within Cloud Computing | ||||
| Al-Azhar Bulletin of Science | ||||
| Article 5, Volume 2022, Issue 6, June 2022, Page 57-63 PDF (374.8 K) | ||||
| Document Type: Review Article | ||||
| DOI: 10.21608/absb.2022.110327.1159 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Afaf A. Abdelhafiz 
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| Department of Mathematics, Division of Computer Science, Faculty of Science, Al-Azhar University (Branch of Girls), Cairo, Egypt. | ||||
| Abstract | ||||
| :The environment of cloud computing has become widely used in a variety of applications and fields in recent years. Task and resource scheduling, on the other hand, is an area where there is still room for development. Task scheduling methods that allow the mapping of incoming tasks to resources are required to meet good performance data mapping in a heterogeneous computing system. Makespan is reduced and resource usage is maximized when resources and tasks are efficiently mapped. A novel scheduling approach is proposed in this work, which improves the makespan. There are two phases to the recommended method. The Tuples algorithm is used in the first phase that schedules tasks on resources. The second phase rearranges some tasks in order to improve the overall timeframe. The outcomes of the simulation show that the new approach for heterogeneous systems outperforms MASA, max-min, e-MASA, Tuples and Enhanced max-min algorithms in terms of makespan and time complexity. | ||||
| Keywords | ||||
| Scheduling algorithm; Max-min; Tuples; makespan; complexity | ||||
| References | ||||
|
[1] Sa’ad S, Muhammed A, Abdullahi M, Abdullah A, Ayob FH. An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud. Algorithms. 2021;14(7):1–24.
[2] Sasikaladevi N. Minimum makespan task scheduling algorithm in cloud computing. Int J Grid Distrib Comput. 2016;9(11):61–70.
[3] Morariu O, Morariu C, Borangiu T. A genetic algorithm for workload scheduling in cloud based e-Learning. Proc 2nd Int Work Cloud Comput Platforms, CloudCP 2012 - Co-located with EuroSys 2012. 2012;1–6.
[4] Sana MU, Li Z. Efficiency aware scheduling techniques in cloud computing: A descriptive literature review. PeerJ Comput Sci. 2021;7:1–37.
[5] Gundu SR, Panem CA, Thimmapuram A. Real-Time Cloud-Based Load Balance Algorithms and an Analysis. SN Comput Sci [Internet]. 2020;1(4):1–9. Available from: https://doi.org/10.1007/s42979-020-00199-8
[6] Ibrahim M, Nabi S, Baz A, Naveed N, Alhakami H. Towards a task and resource aware task scheduling in Cloud Computing: An experimental comparative evaluation. Int J Networked Distrib Comput. 2020;8(3):131–138.
[7] Mahmoud H, Thabet M, Khafagy MH, Omara FA. An efficient load balancing technique for task scheduling in heterogeneous cloud environment. Cluster Comput [Internet]. 2021;24(4):3405–3419. Available from: https://doi.org/10.1007/s10586-021-03334-z
[8] Arif KI. An Effective Load Balancing Algorithm Based on Deadline Constraint under Cloud Computing. IOP Conf Ser Mater Sci Eng. 2020;928(3).
[9] Van Den Bossche R, Vanmechelen K, Broeckhove J. Cost-optimal scheduling in hybrid IaaS clouds for deadline constrained workloads. Proc - 2010 IEEE 3rd Int Conf Cloud Comput CLOUD 2010. 2010;(May 2014):228–235.
[10] Li J, Su S, Cheng X, Huang Q, Zhang Z. Cost-conscious scheduling for large graph processing in the cloud. Proc- 2011 IEEE Int Conf HPCC 2011 - 2011 IEEE Int Work FTDCS 2011 -Workshops 2011 Int Conf UIC 2011- Work 2011 Int Conf ATC 2011. 2011;808–813.
[11] Kim SS, Byeon JH, Yu H, Liu H. Biogeography-based optimization for optimal job scheduling in cloud computing. Appl Math Comput. 2014;247:266–280.
[16] Li J, Qiu M, Ming Z, Quan G, Qin X, Gu Z. Online optimization for scheduling preemptable tasks on IaaS cloud systems. J Parallel Distrib Comput. 2012;72(5):666–677.
[15] Amudha T, Dhivyaprabha TT. QoS priority based scheduling algorithm and proposed framework for task scheduling in a grid environment. Int Conf Recent Trends Inf Technol ICRTIT 2011. 2011;650–655.
[14] Kang L, Ting X. Application of adaptive load balancing algorithm based on minimum traffic in cloud computing architecture. 2015 Int Conf Logist Informatics Serv Sci LISS 2015. 2015;
[15] Bhoi U, Ramanuj P. Enhanced Max-min Task Scheduling Algorithm in Cloud Computing. Int J Appl or Innov … [Internet]. 2013;2(4):259–264. Available from: http://ijaiem.org/Volume2Issue4/IJAIEM-2013-04-30-130.pdf
[16] Eldahshan K, El-kader AA, Ghazy N. Minimum Average Scheduling Algorithm , MASA , Performance Boosting Approach. 2016;(1):23–29.
[17] Elkader AA. Enhancing the Minimum Average Scheduling Algorithm ( MASA ) based on Makespan Minimizing Set of all Tasks. 2017;(1):9–13.
[18] Abd A. ACTA: Average of Completion Times Algorithm. Int J Comput Appl. 2017;172(8):18–22.
[19] Elhafiz AAEA. HASA: Half The Average Scheduling Algorithm. Circ Comput Sci. 2017;2(9):35–39.
[20] Abdelkader Abdelhafiz A. Tuples: A New Scheduling Algorithm. J Comput. 2018; 13 (11): 1309–1315. | ||||
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