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008			230821t20232023my a|||fr|||| 000 0 eng d
020			_aTHE0009692 (Local) _qHardback
040			_aUMP _beng _cUMP _erda
090			_aFKOM .S29 2023 r Thesis
100	1		_aSaydul Akbar Murad, _eauthor.
245	1	0	_aA new priority rule cloud scheduling technique that utilizes gaps to increase the efficiency of jobs distribution / _cSaydul Akbar Murad
264		1	_aKuantan, Pahang : _bUMP, _c2023
264		4	_c©2023
300			_axiii, 117 pages : _billustrations (some color) ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
337			_2rdamedia _acomputer
338			_2rdacarrier _avolume
338			_2rdacarrier _acomputer disc
347			_2rda _atext file _bPDF
500			_aFaculty of Computing
502			_aThesis (Master of Science) -- Universiti Malaysia Pahang – 2023
504			_aIncludes bibliographical references
520	3		_aIn recent years, the concept of cloud computing has been gaining traction to provide dynamically increasing access to shared computing resources (software and hardware) via the internet. It’s no secret that cloud computing’s ability to supply mission-critical services has made job scheduling a hot subject in the industry right now. However, the efficient utilization of these cloud resources has been a challenge, often resulting in wastage or degraded service performance due to poor scheduling. To solve this issue, existing research has been focused on queue-based job scheduling techniques, where jobs are scheduled based on specific deadlines or job lengths. To overcome this challenge, numerous researchers have focused on improving existing Priority Rule (PR) cloud schedulers by developing dynamic scheduling algorithms, but they have fallen short of meeting user satisfaction, such as flowtime, makespan, and total tardiness. These are the limitations of the current implementation of existing Priority Rule (PR) schedulers, mainly caused by blocking made by jobs at the head of the queue. These limitations lead to the poor performance of cloud-based mobile applications and other cloud services. To address this issue, the main objective of this research is to improve the existing PR cloud schedulers by developing a new dynamic scheduling algorithm by manipulating the gaps in the cloud job schedule. In this thesis, first a Priority-Based Fair Scheduling (PBFS) algorithm has been introduced to schedule jobs so that jobs get access to the required resources at optimal times. Then, a backfilling strategy called Shortest Gap Priority-Based Fair Scheduling (SG-PBFS) is proposed that attempts to manipulate the gaps in the schedule of cloud jobs. Finally, the performance evaluation demonstrates that the proposed SG-PBFS algorithm outperforms SG-SJF, SG-LJF, SG-FCFS, SG-EDF, and SG-(MAX-MIN) in terms of flow time, makespan time, and total tardiness, which conclusively demonstrates its effectiveness. The experiment result shows that for 500 jobs, SG-PBFS flow time, makespan time, and tardiness time are 9%, 4%, and 7% less than PBFS gradually.
610	2	0	_xDissertations _aFaculty of Computing
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses
942			_2lcc _cTHESIS