Modified Round Robin algorithm (MRR)
01 Sep 2017-pp 2832-2839
TL;DR: The proposed algorithm improves the efficiency of the traditional RR algorithm by considering all the factors like priority, burst time and arrival time of the processes to arrange them in the ready queue and generating TQ accordingly; which effectively reduces the Waiting time, Turn-around time, and the number of context switches.
Abstract: CPU Scheduling Algorithms form the basic and fundamental concepts of Operating Systems. A scheduling algorithm is used to produce effective switches between the processes present in the ready queue. Round Robin algorithm is one among the many CPU scheduling algorithms where every process executes for a given time quantum (TQ). Therefore the system efficiency and performance are completely dependent on the value of TQ. If this value is static in nature, then the CPU performance decreases. This paper uses the dynamic TQ to create an efficient Round Robin Algorithm. This goal was achieved by using the concept of median. The traditional RR algorithm does not take priority under the consideration, which further reduces the CPU performance. The proposed algorithm improves the efficiency of the traditional RR algorithm by considering all the factors like priority, burst time and arrival time of the processes to arrange them in the ready queue and generating TQ accordingly; which effectively reduces the Waiting time, Turn-around time, and the number of context switches. The paper also presents a detailed comparison between the proposed algorithm and existing algorithms.
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TL;DR: Task scheduling algorithms can also be applied in the cloud-computing environment; it is one of the most important activities in this environment.
Abstract: Nowadays, operating systems have become more complex and more efficient due to the multitasking functionality, which allows several processes to run simultaneously. The Operating System (OS) chooses a task from the Ready Queue (RQ) and allocates it to a processor, this process is known as scheduling. When several processes are in the RQ, the OS plays an important role in choosing the correct order of execution of the processes for achieving better Average Turnaround Time (ATAT) and Average Waiting Time (AWT). Task scheduling algorithms can also be applied in the cloud-computing environment; it is one of the most important activities in this environment.
9 citations
08 Oct 2018
TL;DR: An interactive event-driven dashboard is developed for real-time edge node registration, system monitoring, service initiation and migration, and an application profiling feature has been introduced which assigns the needed quota for an application requirement in terms of CPU, GPU and RAM.
Abstract: of Master’s Thesis Author: Muhammad Farooq Tufail Title: Resource Management in Container-based Mobile Edge Computing Date: August 14, 2018 Pages: vii + 67 Major: Communications Engineering Code: ELEC3029 Supervisor: Professor Yu Xiao Advisor: Marius Noreikis M.Sc. (Tech.) Mobile edge computing is a promising technology which provides support to time-sensitive applications by pushing centralized cloud processing capabilities to distributed Fog nodes. These fog nodes are deployed at one-hop distance from end-user and provide real-time data processing capabilities at the edge of network. Due to service provisioning at the edge of network, no congestion occurs at the core of network, quality of service (QoS) is improved and the overall network operational cost is significantly reduced. However, these nodes have limited capabilities such as processing, storage and coverage so, they face challenge of mobility support for a mobile user when continued service (i.e. zero downtime) is required during handovers between edge nodes. Furthermore, they also need an effective task allocation and resource management strategy to ensure smooth operation of edge services. Unlike traditional VM based environment in Fog Computing, this work explores lightweight Docker containers to deploy and migrate services. In this work, an interactive event-driven dashboard is developed for real-time edge node registration, system monitoring, service initiation and migration. Then, motivated by Fog Following Me [47], a couple of resource allocation schemes (i.e. algorithm-I & II) have been introduced to dynamically manage the compute resources among fog nodes. For smooth service operation and stable migration, an application profiling feature has been introduced which assigns the needed quota for an application requirement in terms of CPU, GPU and RAM. The developed system′s performance is evaluated by conducting various experiments. The experimental results clearly demonstrate and verify the working feasibility of the whole system′s operation in context of edge computing. However, the observed processing delays during service migration marks the limitation of Docker and suggest the need to use latest optimization tools to cut down the network delays and ensure zero-downtime service migration.
1 citations
01 Nov 2020
References
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01 Jan 2012
TL;DR: In this article, Abraham Silberschatz and Peter Galvin discuss key concepts that are applicable to a variety of operating systems and present a large number of examples taken from common operating systems, including WindowsNT and Solaris 2.
Abstract: From the Publisher:
This best-selling book, now in its fifth edition, provides a solid theoretical foundation for understanding operating systems. Authors Abraham Silberschatz and Peter Galvin discuss key concepts that are applicable to a variety of systems. They also present a large number of examples taken from common operating systems, including WindowsNT and Solaris 2. This book teaches general principles in operating systems while giving the teacher and students the flexibility to choose the implementation system.
2,475 citations
01 Jan 2010
TL;DR: The author strongly feel that the proposed architecture solves all the problem encountered in simple round robin architecture by decreasing the performance parameters to desirable extent and thereby increasing the system throughput.
Abstract: The main objective of this paper is to develop a new approach for round robin scheduling which help to improve the CPU efficiency in real time and time sharing operating system. There are many algorithms available for CPU scheduling. But we cannot implemented in real time operating system because of high context switch rates, large waiting time, large response time, large trn around time and less throughput. The proposed algorithm improves all the drawback of simple round robin architecture. The author have also given comparative analysis of proposed with simple round robin scheduling algorithm. Therefore, the author strongly feel that the proposed architecture solves all the problem encountered in simple round robin architecture by decreasing the performance parameters to desirable extent and thereby increasing the system throughput.
85 citations
"Modified Round Robin algorithm (MRR..." refers background in this paper
...Ajit Singh [7], proposed an algorithm in which the allocation in the first cycle is done for the initial TQ similar as RR scheduling....
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...[7] Singh, A., Goyal, P., & Batra, S. (2010)....
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01 Jan 2012
TL;DR: The main objective of this paper is to develop a new approach for round robin C P U scheduling which improves the performance of CPU in real time operating system and implements the concept of aging by assigning new priorities to the processes.
Abstract: The main objective of this paper is to develop a new approach for round robin C P U scheduling a l g o r i t h m which improves the performance of CPU in real time operating system. The proposed Priority based Round-Robin CPU Scheduling algorithm is based on the integration of round-robin and priority scheduling algorithm. It retains the advantage of round robin in reducing starvation and also integrates the advantage of priority scheduling. The proposed algorithm also implements the concept of aging by assigning new priorities to the processes. Existing round robin CPU scheduling algorithm cannot be implemented in real time operating system due to their high context switch rates, large waiting time, large response time, large turnaround time and less throughput. The proposed algorithm improves all the drawbacks of round robin C P U scheduling algorithm. The paper also presents the comparative analysis of proposed algorithm with existing round robin scheduling algorithm on the basis of varying time quantum, average waiting time, average turnaround time and number of context switches.
78 citations
Journal Article•
TL;DR: After improvement in Round Robin it has been found that the waiting time and turnaround time have been reduced drastically and this paper describes an improvement in RR.
Abstract: One of the most important components of the computer resource is the CPU. CPU scheduling involves a careful examination of pending processes to determine the most efficient way to service the requests. CPU scheduling is the basis of multiprogrammed operating systems. Most CPU scheduling algorithms concentrate on maximizing CPU utilization and throughput and minimizing turnaround time, waiting time, response time and number of context switching for a set of requests. Some of the popular CPU scheduling algorithms are First-Come-First-Served (FCFS), Shortest Job First (SJF), Priority Scheduling and Round Robin (RR). FCFS is the simplest form of CPU scheduling algorithm. This algorithm is simple to implement, but it generally does not provide the fastest service. Round Robin being the most popular choice in time shared system, but it may not be suitable for real time systems because of larger waiting time, turnaround time and more number of context switches. This paper describes an improvement in RR. A simulator program has been designed and tested the Improved Round Robin (IRR). After improvement in RR it has been found that the waiting time and turnaround time have been reduced drastically.
75 citations
"Modified Round Robin algorithm (MRR..." refers background or methods in this paper
...TABLE IV: Comparison of RR with IRR [5] and MRR....
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...Manish Kumar [5], introduces an algorithm called “Improved Round Robin (IRR)” where the allocation of the process, which is leading the queue, is done at the beginning and is allocated for fixed TQ....
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...The comparison between RR, IRR [5] and MRR is depicted in Table IV....
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...The above comparison shows that MRR performs comparatively better with respect to RR and IRR [5]....
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...Also, it can be said MRR shows the lesser number of CS, lesser Average TAT and lesser Average WT than the other two algorithms (RR and IRR [5])....
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Posted Content•
TL;DR: In this paper, a new variant of RR scheduling algorithm, known as Dynamic Quantum with Readjusted Round Robin (DQRRR) algorithm is proposed, which is better than RR by reducing number of context switching, average waiting time and average turn around time.
Abstract: Scheduling is the central concept used frequently in Operating System. It helps in choosing the processes for execution. Round Robin (RR) is one of the most widely used CPU scheduling algorithm. But, its performance degrades with respect to context switching, which is an overhead and it occurs during each scheduling. Overall performance of the system depends on choice of an optimal time quantum, so that context switching can be reduced. In this paper, we have proposed a new variant of RR scheduling algorithm, known as Dynamic Quantum with Readjusted Round Robin (DQRRR) algorithm. We have experimentally shown that performance of DQRRR is better than RR by reducing number of context switching, average waiting time and average turn around time.
72 citations