Open AccessTime Efficient Round Robin Job Scheduling (NARR) in Cloud Computing
Author(s) -
Jahan Ali,
. Ritika,
Rakesh Kumar Saini
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1235.109119
Subject(s) - computer science , distributed computing , human multitasking , fair share scheduling , scheduling (production processes) , dynamic priority scheduling , weighted round robin , round robin scheduling , two level scheduling , cloud computing , earliest deadline first scheduling , rate monotonic scheduling , fixed priority pre emptive scheduling , response time , parallel computing , computer network , operating system , mathematical optimization , quality of service , mathematics , psychology , cognitive psychology
Cloud computing simply means the advancement of distributed computing which takes data processing computational aspects over networks to centralized high-power data centers. It refers to the use of a centralized pool of resources that are distributed on a pay-per-view model to a large number of customers. This requires scheduling algorithms that allow us to define which task processes, among which resources are first allocated for performance. The Round Robin (RR) scheduling algorithm is the common scheduling algorithm used in multitasking and real-time environments. Its performance is largely determined by the amount of time it takes to carry out a specific task assigned by the CPU. If the less time is chosen the context switch is high and the higher time is chosen, the first-come first-server (FCFS) is selected. System's performance thus totally depends on the optimal quantum time to choose from. In this paper, I'm examining a different way of improving the performance of the round robin scheduling algorithm by means of a dynamic time quantum and comparison of different performance.