A Behavioral Study of Task Scheduling Algorithms in Cloud Computing

• Published in: International journal of advanced computer science & applications Vol. 10; no. 7
• Main Authors: Belgaum, Mohammad Riyaz, Musa, Shahrulniza, S., M., Alam, Muhammad
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 2019
• Subjects: Algorithms; Cloud computing; Consumers; Data centers; Preempting; Response time; Task scheduling
• ISSN: 2158-107X; 2156-5570
• DOI: 10.14569/IJACSA.2019.0100768

All the services offered by cloud computing are bundled into one service know as IT as a Service (ITaaS). The user’s processes are executed using these services. The scheduling techniques used in the cloud computing environment execute the tasks at different datacenters considering the needs of the consumers. As the requirements vary from one to one, and so the priorities also change. The jobs are executed either in a preemptive or non-preemptive way. The tasks in cloud computing also migrate from one datacenter to another considering load balancing. This research mainly focused on the study of how the Round Robin (RR) and Throttled (TR) scheduling techniques function subject to different tasks given for processing. An analysis is carried out to measure the performance based on the metrics like response time and service time at different userbases and data centers. The consumers have the option to select the server broker policy as they are the ultimate users and payers.