Dynamic Round Robin Scheduling Research Articles

Improvised Dynamic Round-Robin Scheduling for Optimum Resource Utilization in Cloud Systems

Improvised Dynamic Round-Robin Scheduling for Optimum Resource Utilization in Cloud Systems

A Novel Amended Dynamic Round Robin Scheduling Algorithm for Timeshared Systems

Central Processing Unit (CPU) is the most significant resource and its scheduling is one of the main functions of an operating system. In timeshared systems, Round Robin (RR) is most widely used scheduling algorithm. The efficiency of RR algorithm is influenced by the quantum time, if quantum is small, there will be overheads of more context switches and if quantum time is large, then given algorithm will perform as First Come First Served (FCFS) in which there is more risk of starvation. In this paper, a new CPU scheduling algorithm is proposed named as Amended Dynamic Round Robin (ADRR) based on CPU burst time. The primary goal of ADRR is to improve the conventional RR scheduling algorithm using the active quantum time notion. Quantum time is cyclically adjusted based on CPU burst time. We evaluate and compare the performance of our proposed ADRR algorithm based on certain parameters such as, waiting time, turnaround time etc. and compare the performance of our proposed algorithm. Our numerical analysis and simulation results in MATLAB reveals that ADRR outperforms other well-known algorithms such as conventional Round Robin, Improved Round Robin (IRR), Optimum Multilevel Dynamic Round Robin (OMDRR) and Priority Based Round Robin (PRR)

Improvised Optimum Multilevel Dynamic Round Robin Algorithm for Optimizing CPU Scheduling

scheduling has strong effect on resource utilization as well as overall performance of the system. In order to simulate the behavior of multiple jobs in a multiprogramming computer system needs to be specified. The most important aspect of job scheduling is the ability to create a multi-tasking environment. The intention should be allowed as many as possible running processes at all time in order to make best use of CPU. Round Robin algorithm performs optimally in timeshared systems, but it is not suitable for soft real time systems, because it gives more number of context switches, larger waiting time and larger response time. The main objective of this paper is to improve the previous OMDRRS with calculates intelligent time slice and warps after every round of execution and assumed that all the processes were come at randomly as well as all the processes have priority. In order to simulate the behavior of various CPU scheduling algorithms and to improve Round Robin scheduling algorithm using dynamic time slice concept, we purpose new improved CPU scheduling algorithm called Optimum Dynamic Round Robin Scheduling (OMDRR). Our experimental results show that our proposed algorithm performs better in terms of reducing the number of context switch, average waiting time and average turnaround time.

Hierarchical Particle Swarm Optimization with Ortho-Cyclic Circles

Cloud computing is an emerging technology which deals with real world problems that changes dynamically. The users of dynamically changing applications in cloud demand for rapid and efficient service at any instance of time. To deal with this paper proposes a new modified Particle Swarm Optimization (PSO) algorithm that work efficiently in dynamic environments. The proposed Hierarchical Particle Swarm Optimization with Ortho Cyclic Circles (HPSO-OCC) receives the request in cloud from various resources, employs multiple swarm interaction and implements cyclic and orthogonal properties in a hierarchical manner to provide the near optimal solution. HPSO-OCC is tested and analysed in both static and dynamic environments using seven benchmark optimization functions. The proposed algorithm gives the best solution and outperforms in terms of accuracy and convergence speed when compared with the performance of existing PSO algorithms in dynamic scenarios. As a case study, HPSO-OCC is implemented in remote health monitoring application for optimal service scheduling in cloud. The near optimal solution from HPSO-OCC and Dynamic Round Robin Scheduling algorithm is implemented to schedule the services in healthcare.

Simulation of an Optimum Multilevel Dynamic Round Robin Scheduling Algorithm

CPU scheduling has valiant effect on resource utilization as well as overall quality of the system. Round Robin algorithm performs optimally in time shared systems, but it performs more number of context switches, larger waiting time and larger response time. In order to simulate the behavior of various CPU scheduling algorithms and to improve Round Robin scheduling algorithm using dynamic time slice concept, in this paper we produce the implementation of new CPU scheduling algorithm called An Optimum Multilevel Dynamic Round Robin Scheduling (OMDRRS), which calculates intelligent time slice and warps after every round of execution. The results display the robustness of this software, especially for academic, research and experimental use, as well as proving the desirability and efficiency of the probabilistic algorithm over the other existing techniques and it is observed that this OMDRRS projects good performance as compared to the other existing CPU scheduling algorithms.

Stability analysis of networked control systems with round-robin scheduling and packet dropouts

In this paper, the stability of networked control systems (NCSs) with communication constraints at both channels is investigated. A Conventional Round-Robin Scheduling (CRRS) is applied to deal with the communication constraints issue for its simple structure. Furthermore, a Dynamic Round-Robin Scheduling (DRRS), which can preserve the controllability and the detectability of the systems, is considered. For the unreliable communication channels, two independent homogeneous Markov chains are selected to model the packet dropouts phenomenon in the sensor-to-controller (S/C) channel and the controller-to-actuator (C/A) channel. According to the periodic property of the Round-Robin Scheduling (RRS), an auxiliary system with augmented Markov chain is established by the lifting technique to facilitate the stability analysis of the closed-loop system. A necessary and sufficient condition of the exponential mean-square stability for the NCSs is derived. Two illustrative examples are shown to demonstrate the effectiveness of the proposed stability analysis method.

Design and Evaluation of Agent Based Prioritized Dynamic Round Robin Scheduling Algorithm on Computational Grids

Grid computing enables sharing, selection and aggregation of computing resources for solving complex and large-scale scientific problems. Grid scheduling is playing a vital role for the efficient and effective execution of jobs on computational grids. Most of the scheduling algorithms do not consider user and system objectives at the same time. Therefore, in this paper we introduce a concept of fairness to scheduling and present a new agent based job scheduling algorithm called Agent based Prioritized Dynamic Round Robin (APDRR). APDRR is designed and developed by combining the best features of round robin and priority job scheduling algorithm using agent technology. APDRR is fair scheduling algorithm from a user point of view while also regarding the optimization criteria that are anticipated from the system perspective. This paper also presents the comparative performance analysis of our proposed APDRR along with other well known job scheduling algorithms, considering the performance metrics comprised of average waiting time, average turnaround time, average response time, total completion time, average bounded slowdown time and maximum job stretch time. Performance evaluation of job scheduling algorithms has been carried out on a computational grid using real workload traces. Experimental evaluation confirmed that the proposed APDRR scheduling algorithm posses a high degree of optimality in performance, efficiency and scalability. This paper also includes a statistical analysis of real workload traces to present the nature and behavior of jobs

A Fair Service and Dynamic Round Robin Scheduling Algorithm

调度策略是核心路由交换设备性能的重要保证.针对联合输入交叉节点排队(combined input and cross-point queuing,简称CICQ)交换结构现有调度策略在复杂度或性能方面存在的缺陷,深入探讨了CICQ交换结构调度策略设计的基本准则,并提出了CICQ下虚拟通道的概念.基于基本准则和虚拟通道概念,提出一种简单、高效和公平服务的动态轮询调度策略——FDR(fair service and dynamic round robin).其算法复杂度为O(1),具有良好的可扩展性;并依据虚拟通道的状态为其分配调度份额,具有良好的动态实时性能,能够适应流量负载非均衡的网络环境.SPES(switching performance evaluation system)仿真结果表明,该算法具有良好的时延、吞吐量和抗突发性能.;Scheduling policies are playing significant roles in guaranteeing the performance of core routing and switching devices. The limitations in complexities and extensibilities of current combined input and cross-point queueing switching fabric's scheduling policies are first analyzed. Then, based on this analysis, the principle for designing high extensible scheduling policies and the concept of virtual channel are proposed. Based on the principle and virtual channel, it comes up with a dynamic round robin scheduling algorithm-FDR (fair service and dynamic round robin), which is simple, and of high efficiency and fair service. FDR is based on round robin mechanism, whose complexity is only O(1). It allocates the scheduling share for each virtual channel according to its current states, thus, FDR has good dynamic and real-time performance, and it can adapt to unbalanced traffic load network environment. Simulation results under SPES (switching performance evaluation system) show that FDR exhibits good delay, throughput and anti-burst performance.