A job scheduling algorithm for delay and performance optimization in fog computing

2019 ◽  
Vol 32 (7) ◽  
Author(s):  
Bushra Jamil ◽  
Mohammad Shojafar ◽  
Israr Ahmed ◽  
Atta Ullah ◽  
Kashif Munir ◽  
...  
Keyword(s):  
Performance Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
And Performance ◽  
Job Scheduling Algorithm

scholarly journals A New Fuzzy-based Job Scheduling Algorithm for Cluster Computing

2013 ◽  
Vol 77 (1) ◽  
pp. 33-36
Author(s):  
Behzad Azizpour ◽  
Mehdi Effatparvar ◽  
Mohammad Sadeq Garshasbi
Keyword(s):  
Cluster Computing ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Job Scheduling Algorithm

scholarly journals ROA-CONS: Raccoon Optimization for Job Scheduling

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2270
Author(s):  
Sina Zangbari Koohi ◽  
Nor Asilah Wati Abdul Hamid ◽  
Mohamed Othman ◽  
Gafurjan Ibragimov
Keyword(s):  
User Satisfaction ◽  
High Performance ◽  
Job Scheduling ◽  
Response Times ◽  
Scheduling Algorithm ◽  
Desktop Computer ◽  
Network Heterogeneity ◽  
Parallel Job Scheduling ◽  
Scheduling Method ◽  
And Performance

High-performance computing comprises thousands of processing powers in order to deliver higher performance computation than a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. The scheduling of these machines has an important impact on their performance. HPC’s job scheduling is intended to develop an operational strategy which utilises resources efficiently and avoids delays. An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. Another problem for parallel job scheduling is user fairness. One of the issues in this field of study is providing a balanced schedule that enhances efficiency and user fairness. ROA-CONS is a new job scheduling method proposed in this paper. It describes a new scheduling approach, which is a combination of an updated conservative backfilling approach further optimised by the raccoon optimisation algorithm. This algorithm also proposes a technique of selection that combines job waiting and response time optimisation with user fairness. It contributes to the development of a symmetrical schedule that increases user satisfaction and performance. In comparison with other well-known job scheduling algorithms, the simulation assesses the effectiveness of the proposed method. The results demonstrate that the proposed strategy offers improved schedules that reduce the overall system’s job waiting and response times.

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