Abstract: In recent years, cloud computing has changed the way that resources are used, allowing users to request resources whenever they need them. The scheduler of cloud computing uses task scheduling and resource allocation algorithms for efficient and effective load balancing of a workload among cloud resources to improve the overall performance of the cloud system when the highly incoming user requests are coming for the resources. But cloud providers are limited by the amount of resources they have, and are thus compelled to strive to maximum utilization. In this paper we have designed the hybrid approach of combination of credit based task length & priority algorithm and credit based deadline algorithm as well as compare the results with FCFS, SJF and task length & priority scheduling algorithms. When we use the credit based task length & priority scheduling algorithm to schedule the task without knowing the deadline of the task, it will cause the dead of the least deadline task. The deadline credit is also included so that assigning number of resources to the tasks in such a way that there will be maximum resource utilization and minimum processing time achieved. This paper presents the simulation results of the proposed methodology implemented with the help of Cloudsim and Net beansIDE8.0 and analysis of results.
Keyword: Task length & Priority, Hybrid TLPD, FCFS, SJF, Cloudsim
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DOI:
10.17148/IJARCCE.2022.11816
