A Modified Round Robin Method to Enhance the Performance in Cloud Computing

Cloud computing is a new age technology. The quality of services in the cloud depends on priority of the job, time taken to transfer the specific task, length of the task, number of CPUs available for every virtual machine and capacity of virtual machine. Previously, there were many researches done on the issue of task scheduling, about workflow and job scheduling in cloud computing. Scheduling in cloud has to cope with many issues like allocation of small request, workload characterization, different types of request, real-time allocation and provision for queuing. Throughput of the system depends on resources allocation to process which is performed by the CPU scheduling algorithms. The objective of scheduling algorithm is to minimize the waiting time, turnaround time, response time and context switching and highest degree of utilization of CPU. Round Robin is a pre-emptive algorithm which works on fixed time quantum and used in time sharing system. Round Robin is also known for its fairness task distribution and optimum utilization of CPU. In this paper, we have tried to introduce an improved Round Robin algorithm by calculating the quantum number by taking the average of burst time of all tasks which arrive at the same time and finish the execution of the tasks which have less quantum number and the task which has greater quantum number will be executed as per the existing Round Robin method. By simulating the proposed algorithm, we have observed that the waiting time and turnaround time decrease considerably.

[1]  Medhat A. Tawfeek,et al.  Cloud task scheduling based on ant colony optimization , 2013, 2013 8th International Conference on Computer Engineering & Systems (ICCES).

[2]  Ramandeep Kaur,et al.  Enhanced Round Robin Technique for Task Scheduling in Cloud Computing Environment , 2016 .

[3]  Abhimanyu Jindal,et al.  Optimization of Task Scheduling Algorithm through QoS Parameters for Cloud Computing , 2016 .

[4]  Sakshi.  Cloud Computing Concept, Technology and Architecture , 2018 .

[5]  Aarti Singh,et al.  A Comparative Analysis of Resource Scheduling Algorithms in Cloud Computing , 2013 .

[6]  Danilo Ardagna,et al.  Quality-of-service in cloud computing: modeling techniques and their applications , 2014, Journal of Internet Services and Applications.

[7]  Yike Guo,et al.  Optimization of Resource Scheduling in Cloud Computing , 2010, 2010 12th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing.

[8]  Farookh Khadeer Hussain,et al.  Task Scheduling Optimization in Cloud Computing Applying Multi-Objective Particle Swarm Optimization , 2013, ICSOC.

[9]  Amanpreet Kaur,et al.  Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment , 2019, J. King Saud Univ. Comput. Inf. Sci..

[10]  Seema Bawa,et al.  Review of Efficient Resource Scheduling Algorithms in Cloud Computing , 2013 .

[11]  Shigen Shen,et al.  Task Scheduling Optimization in Cloud Computing Based on Heuristic Algorithm , 2012, J. Networks.

[12]  Deepesh Kumar,et al.  A survey on resource allocation techniques in cloud computing , 2015, International Conference on Computing, Communication & Automation.

[13]  Renfa Li,et al.  A priority constrained scheduling strategy of multiple workflows for cloud computing , 2012, 2012 14th International Conference on Advanced Communication Technology (ICACT).

[14]  Shahenda Sarhan,et al.  A novel hybrid of Shortest job first and round Robin with dynamic variable quantum time task scheduling technique , 2017, Journal of Cloud Computing.

[15]  Antoine Bagula,et al.  Optimization of virtual resources allocation in cloud computing environment , 2017, 2017 IEEE AFRICON.

[16]  Javad Vahidi,et al.  Optimization of Resource Allocation in Cloud Computing by Grasshopper Optimization Algorithm , 2019, 2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI).

[17]  Seyyed Mohsen Hashemi,et al.  A Review of Workflow Scheduling in Cloud Computing Environment , 2012 .

[18]  Tharam S. Dillon,et al.  SLA-Based Trust Model for Cloud Computing , 2010, 2010 13th International Conference on Network-Based Information Systems.

[19]  Santwana Sagnika,et al.  Workflow scheduling in cloud computing environment using Cat Swarm Optimization , 2014, 2014 IEEE International Advance Computing Conference (IACC).