Dynamic Time Slice Round Robin Scheduling Algorithm with Unknown Burst Time

Muraleedharan, Anju; Antony, Neenu; Nandakumar, Ratna

doi:10.17485/ijst/2016/v9i8/76368

Cited by 17 publications

(4 citation statements)

References 4 publications

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“…The suggested method gives better result in context of AWT and ATAT.Author. in [18] suggested the proposed approach gives better result in minimizing AWT, ATAT and NCS. In [19] Author proposed a modification on RR algorithm where TQ is equal to the BT of the first process.…”

Section: Literature Surveymentioning

confidence: 92%

“…Algorithms Parameters Description [10] Priority based RR algorithm Priority based RR algorithm Better results as compared to traditional RR algorithms [11] Nonlinear mathematical model in RR Nonlinear mathematical model in RR Better performance as compared to other algorithms [12] ISRBRR ISRBRR Better performance as compared to other algorithms [13] SRBRR SRBRR Minimizing AWT, ATAT and NCS [14] HLVQTRR HLVQTRR Proposed method reduces context switches [15] IRRVQ IRRVQ Proposed method performs better than conventional RR [16] Improved dynamic RR scheduling algorithm Improved dynamic RR algorithm Minimizing AWT, ATAT and NCS [17] Improved RR algorithm Improved RR algorithm Minimizing AWT and ATAT [18] Dynamic Time slice RR algorithm Dynamic Time slice RR algorithm Minimizing AWT, ATAT and NCS [19] Modified RR algorithm Modified RR algorithm Minimizing WT and TAT [20] Genetic Algorithm Genetic algorithm Minimizing WT [21] Efficient Dynamic RR algorithm Efficient dynamic RR algorithm Minimizing AWT, ATAT and NCS [22] Modified RR with vigorous TQ Modified RR with vigorous TQ Better results as compared to traditional algorithms [23] Best TQ RR CPU Scheduling algorithm Best TQ RR CPU scheduling algorithm Minimizing AWT, ATAT and NCS [24] Amended Dynamic RR (ADRR) Amended dynamic RR(ADRR) Better performance as compared to other algorithms [25] Hybrid dynamic SJF and RR algorithm Hybrid dynamic SJF and RR algorithm Minimizing WT and RT [26] A new Cloudlet Scheduling Algorithm A new cloudlet scheduling algorithm Minimizing WT, TAT and NCS [27] Improved RR Scheduling Improved RR scheduling Better results in terms of WT and TAT [28] Priority Based Efficient RR Algorithm Priority based efficient RR algorithm Reduces AWT, ATAT and NCS [29] Dynamic Calculated TQ for each VM Dynamic calculated TQ for each VM Better utilization of resources [30] Modified The WT, TAT and RT is being calculated for each process. The WT is calculated by Eq.…”

Section: Reference Yearmentioning

confidence: 99%

“…The RT for job P1 is (0), RT for job P2 is (5), RT for job P3 is (11), RT for job P4 is (18) and RT for job P5 is (28). The total RT for all 5 jobs is 62, then the ART is being calculated by Eq.…”

Section: Reference Yearmentioning

confidence: 99%

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Cloud Task Scheduling using Static Time Quantum Approach

Sharma¹,

Kumar²,

Sharma³

2022

INDJCSE

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Cloud Computing is the delivery of various services via internet namely hardware, software, servers, databases, network and data storage. Cloud Computing is the technology that allows users to access resources through Internet. Storing data on data cloud is growing more popular among individuals and businesses who need bulk storage space. In our daily life Cloud Computing plays a vital role. Cloud Computing is differentiated from conventional computing by its Scalability, Accessibility, Reliability, and On-demand pay-as-you-go services. At present Cloud Computing technology is used by Google, Amazon, Yahoo. In Cloud Computing Process Scheduling is an important aspect. Minimizing Waiting Time (WT), Minimizing Turnaround Time (TAT), Minimizing Response Time (RT) and Improves Resource Utilization are the important parameter for Task Scheduling. As an outcome various strategies have been suggested and implemented in order to improve scheduling performance. Because of its simplicity and fairness Round Robin (RR) is treated as the best scheduling algorithm. Our proposed algorithm named Enhanced Round Robin Algorithm for Cloud Scheduling (ERACS). The proposed algorithm reduces Average Waiting Time (AWT), Average Turnaround Time (ATAT), Average Response Time (ART) and Number of Context Switches (NCS). Comparative Analysis is being done with existing algorithms and get better result of our prosed algorithm in terms of AWT (28.2), ATAT (44.2), ART (24.2) and NCS (7).

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Section: Literature Surveymentioning

confidence: 92%

Section: Reference Yearmentioning

confidence: 99%

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Cloud Task Scheduling using Static Time Quantum Approach

Sharma¹,

Kumar²,

Sharma³

2022

INDJCSE

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“…The proposed algorithm's main flaw is that its RT was high when compared to other algorithms. With an unknown BT, [23] offer a DTSRR scheduling algorithm. This algorithm shows that the queue is attended to using a dynamic time quantum for all processes.…”

Section: Introductionmentioning

confidence: 99%

Improved Round Robin CPU Scheduling Algorithm with Different Arrival Times Based on Dynamic Quantum

Ahmad

2022

JES

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Modern operating systems are based on the principle of time-sharing in executing simultaneous operations. Determining the length of the time slice, and the times when processes arrive at the ready queue are problems that affect metrics as the average waiting time (AWT), average turnaround time (ATAT), response time (RT) and the number of context switches (NCS) of the time-sharing round robin RR algorithms. The research aims to propose an algorithm that achieves a short waiting time while maintaining a reasonable response time, which is the most important characteristic of timesharing algorithms. The Different Arrival-Dynamic Quantum Round Robin (DADQRR) algorithm bases its work on different parameters to adjust the time slice value dynamically. The algorithm has been compared to three other algorithms that are similar in terms of dealing with different arrival times, namely AN, MARR, RR. The algorithm outperformed the three algorithms at range from 6.155% to 31.409% in term of AWT. It achieved an outperformance of 5.924% to 30.850%, considering the TAT. The ranges of outperformance values resulted from the difference in the ranges of arrival times, as well as in the ranges of burst times.

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