Modified Median Round Robin Algorithm (MMRRA)

CPU scheduling involves a careful examination of pending processes to determine the most efficient way to service the requests. This research works in the field of Round Robin (RR) CPU scheduling by carefully studying various popular RR scheduling algorithms to propose an option, Modified Median Rou...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2017 13th International Conference on Electronics, Computer and Computation (ICECCO) s. 1 - 7
Hlavní autoři: Mora, Hafsatu, Abdullahi, Saleh E., Junaidu, Sahalu B.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.11.2017
Témata:
Central Processing Unit
Context switching
CPU scheduling
Dynamic scheduling
Heuristic algorithms
Response time
Round robin
Round Robin CPU scheduling algorithm
Time factors
Turnaround time
Waiting time
ISBN:1538624990, 9781538624999
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:CPU scheduling involves a careful examination of pending processes to determine the most efficient way to service the requests. This research works in the field of Round Robin (RR) CPU scheduling by carefully studying various popular RR scheduling algorithms to propose an option, Modified Median Round Robin Algorithm (MMRRA), to compete alongside others. A lot of research papers on dynamic RR have been published and they provide better solution to the Classical RR. Some major challenges to most of these dynamic RR scheduling are: They do not include Average Response Time (ART) as a criteria for comparison, they do not bother much on preempting processes with negligible left over of burst time which will lead to an increase on the number of context switching (NCS). Using MMRRA, variable quantum time is used to eliminate these shortcomings. A simulator program has been designed and tested against five selected algorithms, which in turns proved to perform better in most of the criteria.
ISBN:1538624990
9781538624999
DOI:10.1109/ICECCO.2017.8333325