Dynamic Round Robin Research Articles

Dynamic round robin with adaptive time quanta (DRRATQ): A proposed algorithm

The CPU scheduling technique influences the performance and efficiency of operating systems. Round-robin scheduling algorithm is ideal for time-shared systems, but it is not optimal for real-time operating systems since it yields more context switching, longer waiting time, and high turnaround time. The performance of the algorithm is predominantly influenced by the designated time quantum; however, determining a suitable time quantum is extremely challenging. This paper presents a CPU scheduling algorithm that provides a better tradeoff between waiting time, turnaround time, response time, and number of context switch by using hypothesis-based quanta generation approach. It combines the CPU burst requirements of actual processes with some noisy data and plots them against the presumed CPU quanta to get quanta densities so that a polynomial regression model can fit the data points with the highest adjusted R-squared. Then applying some complex inferential statistic, the required quanta is obtained. The scheduling is dynamic in nature because it generates the next CPU quanta in reference to the quanta that have been used in the previous cycle with remaining CPU burst requirements of the process, and it is also adaptive in nature because, at each cycle, it uses ‘d’ (5, 5, 4, 3, 2) degree of freedom to calculate the Jarque-Bera Statistics to accept/reject the hypothesis. The algorithm is implemented in ‘R’ and the performance has been evaluated on a sample size of five processes with some noisy data which outperforms the conventional RR and significantly reduces the performance parameters mentioned above. Implementing this algorithm to a time-sharing or distributed environment will undoubtedly improve system performance and will help to avoid issues like thrashing, incorporate aging, CPU affinity, and starvation. Since the proposed algorithm is work-conservative, therefore can be implemented in network packet switching, statistical multiplexing, and real-time systems.

Security sliding mode control for T-S fuzzy systems under attack probability-dependent dynamic round-robin protocol

In this paper, the security control problem for T-S fuzzy systems is investigated through the sliding mode control (SMC) strategy. Consider deception attacks occurring randomly, a multi-modes round-robin protocol is proposed on the sensor-to-controller channel. Under this protocol, the number of transmitted nodes can be dynamically adjusted according to attack probability and system state so as to balance the relationship between system performance and communication transmission. The fuzzy sliding mode controller depending on the scheduling signal is constructed, whose membership functions (MFs) are different from the ones of the controlled system. In addition, by using the membership-function-dependent (MFD) stability analysis method, appropriate sufficient conditions are derived to ensure both the stochastic stability and the reachability. Finally, simulation results are presented to prove the proposed SMC strategy.

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 New Enhanced IGBTQ-based Model for CPU Scheduling

CPU scheduling is concerned with how to efficiently exploit processors by executing the largest number of operations in the shortest possible time. The efficiency of CPU scheduling depends on the algorithm used. Round Robin (RR) is one of the most popular algorithms, which is primarily based on determining the period of execution time for the operation. In this work, we develop a new enhancement algorithm for modifying the RR algorithm based on IGBTQ model to solve the CPU scheduling problem. Therefore, the main objective is to improve the Average waiting Time (AWT) and the Average Turnaround Time (ATT). The final results are successful when reached the lowest scores of AWT and ATT measurements. The experiments used two cases of a different number of processes, which obtained better outputs compared to other state-of-the-art models like; the dynamic RR with Control Preemption (DRRCP), Group Based Time Quantum (GBTQ), and IGBTQ algorithm.

Optimized Round Robin Scheduling Algorithm Using Dynamic Time Quantum Approach in Cloud Computing Environment

Cloud computing refers to a sophisticated technology that deals with the manipulation of data in internet-based servers dynamically and efficiently. The utilization of the cloud computing has been rapidly increased because of its scalability, accessibility, and incredible flexibility. Dynamic usage and process sharing facilities require task scheduling which is a prominent issue and plays a significant role in developing an optimal cloud computing environment. Round robin is generally an efficient task scheduling algorithm that has a powerful impact on the performance of the cloud computing environment. This paper introduces a new approach for round robin based task scheduling algorithm which is suitable for cloud computing environment. The proposed algorithm determines time quantum dynamically based on the differences among three maximum burst time of tasks in the ready queue for each round. The concerning part of the proposed method is utilizing additive manner among the differences, and the burst times of the processes during determining the time quantum. The experimental results showed that the proposed approach has enhanced the performance of the round robin task scheduling algorithm in reducing average turn-around time, diminishing average waiting time, and minimizing number of contexts switching. Moreover, a comparative study has been conducted which showed that the proposed approach outperforms some of the similar existing round robin approaches. Finally, it can be concluded based on the experiment and comparative study that the proposed dynamic round robin scheduling algorithm is comparatively better, acceptable and optimal for cloud environment.

Enhanced Round-Robin Algorithm in the Cloud Computing Environment for Optimal Task Scheduling

Recently, there has been significant growth in the popularity of cloud computing systems. One of the main issues in building cloud computing systems is task scheduling. It plays a critical role in achieving high-level performance and outstanding throughput by having the greatest benefit from the resources. Therefore, enhancing task scheduling algorithms will enhance the QoS, thus leading to more sustainability of cloud computing systems. This paper introduces a novel technique called the dynamic round-robin heuristic algorithm (DRRHA) by utilizing the round-robin algorithm and tuning its time quantum in a dynamic manner based on the mean of the time quantum. Moreover, we applied the remaining burst time of the task as a factor to decide the continuity of executing the task during the current round. The experimental results obtained using the CloudSim Plus tool showed that the DRRHA significantly outperformed the competition in terms of the average waiting time, turnaround time, and response time compared with several studied algorithms, including IRRVQ, dynamic time slice round-robin, improved RR, and SRDQ algorithms.

Characteristic Specific Prioritized Dynamic Average Burst Round Robin Scheduling for Uniprocessor and Multiprocessor Environment

Characteristic Specific Prioritized Dynamic Average Burst Round Robin Scheduling for Uniprocessor and Multiprocessor Environment

Dynamic Round Robin CPU Scheduling Algorithm Based on K-Means Clustering Technique

Minimizing time cost in time-shared operating system is the main aim of the researchers interested in CPU scheduling. CPU scheduling is the basic job within any operating system. Scheduling criteria (e.g., waiting time, turnaround time and number of context switches (NCS)) are used to compare CPU scheduling algorithms. Round robin (RR) is the most common preemptive scheduling policy used in time-shared operating systems. In this paper, a modified version of the RR algorithm is introduced to combine the advantageous of favor short process and low scheduling overhead of RR for the sake of minimizing average waiting time, turnaround time and NCS. The proposed work starts by clustering the processes into clusters where each cluster contains processes that are similar in attributes (e.g., CPU service period, weights and number of allocations to CPU). Every process in a cluster is assigned the same time slice depending on the weight of its cluster and its CPU service period. The authors performed comparative study of the proposed approach and popular scheduling algorithms on nine groups of processes vary in their attributes. The evaluation was measured in terms of waiting time, turnaround time, and NCS. The experiments showed that the proposed approach gives better results.

Dynamic Queue Synchronization for Congestion Control Over Wireless Sensor Networks

Congestion control over resource constrained sensor network is a critical challenge and it is also quite hard to fulfill the QoS constraints for end users. In this paper, a dynamic queue synchronization (DQS) scheme is introduced that can alter the data rate dynamically as per the current buffer length. Its performance is compared with existing schemes i.e., Dynamic Round Robin (DRR) and Random Early Discard (RED) using different routing protocols i.e., LEACH/PEGASIS/TEEN under various constraints (Throughput/End-to-End Delay/Routing Load/Energy).

Fittest Job First Dynamic Round Robin (FJFDRR) scheduling algorithm using dual queue and arrival time factor: a comparison

The Fittest Job First Dynamic Round Robin (FJFDRR) was introduced as a CPU scheduling algorithm whose performance evaluation reduces the number of context switches (CS), average waiting time (AWT), and average turnaround time (ATAT) of processes in a single CPU environment. In this paper, we explored improvements on the FJFDRR by including the process arrival time as an algorithmic factor implemented using a dual queue. We then compared the performance of the proposed algorithm called enhanced Fittest Job First Dynamic Round Robin (eFJFDRR) as with the FJFDRR algorithm together with the other CPU scheduling algorithms. Trial results showed that eFJFDRR scheduling algorithm performed better in reducing average waiting time, average turnaround time, and average response time in some cases. It was also found to balance the number of context switches of the processor during execution.

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)

An Optimal Approach to Selecting the Time Quantum for Dynamic Round Robin

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

LDDWRR: Least Delay Dynamic Weighted Round-Robin Load Balancing in Software Defined Networking

In traditional network devices, tight coupling of data plane with the control plane so large amount of traffic on the web is not correctly handled by the Traditional network devices. The emerging strategy that decoupled the data plane from control plane is called Software Defined Networking (SDN). Control plane of these devices act like a brain or master. It is also called Software Defined networking controller or Openflow controller. Data plane is called slave that behave according to the instructions given by the master or control plane. To convert a data plane into powerful network devices we have to create Firewall, Load balancer, Intrusion Detection system applications and then run that applications at management plane that is on top of control plane. In such a manner we can convert data plane into powerful network devices according to the application. The application that we have created on the top of control plane is load balancer application that convert the dumb data plane into load balancer. Load balancer architecture consists of number of servers and clients which distributed the client traffic among number of servers based on particular strategy. There are number of strategies are available such as Round Robin, random policy. Each load balancing policy has some advantages and disadvantages. We created “least delay dynamic weighted round robin (LDDWRR)” strategy in this paper and run on the top of SDN controller. Then we evaluate the result of our load balancing strategy by comparing with the round robin strategy. Mininet is used for the experiment and controller that is used as control plane is called POX controller.

Routing and Fault Tolerance in Z-Fat Tree

Fat tree topologies have been extensively used as interconnection networks for high performance computing, cluster and data center systems, with their most recent variants able to fairly extend and scale to accommodate higher processing power. While each progressive and evolved fat-tree topology includes some extra advancements, these networks do not fully address all the issues of large scale HPC. We propose a topology called Zoned-Fat tree ( Z -Fat tree,) which is a further extension to the fat trees. The extension relates to the provision of extra degree of connectivity to utilize the extra ports per switches (routing nodes), that are, in some cases, not utilized by the architectural constraints of other variants of fat trees, and hence increases the bisection bandwidth, reduces the latency and supplies additional paths for fault tolerance. To support and profit from the extra links, we propose an adaptive low latency routing for up traffic which is based on a series of leading direction bits predefined at the source; furthermore we suggest a deterministic routing by implementing a dynamic round robin algorithm that overtakes D-mod-K in same cases and guarantees the utilization of all the extra links. We also propose a fault tolerance algorithm, named recoil-and-reroute which makes use of the extra links to ensure higher message delivery even in the presence of faulty links and switches.

SURVEY ON POWER AWARE LOAD BALANCING IN CLOUD COMPUTING

Cloud computing in the current years has been taking its development from the logical to the non logical and business applications. Control utilization and Load adjusting are essential and complex issue in computational Cloud. Load Balancing is an imperative segment in the item benefits based cloud computing. There is a need to create calculations that can catch this multifaceted nature yet can be effortlessly actualized and used to fathom an extensive variety of load adjusting situations in a Data and Computing escalated applications. Because of increment in the quantity of server farms, which relate to electrical vitality cost, crest control scattering, cooling and carbon emanation. These days, control utilization is one of the significant issues for the operation and upkeep of server farms. Vitality costs for server farms are multiplying like clockwork and have effectively crossed $19 billion. Be that as it may, a lot of this power is squandered as servers are for the most part sit. Sit without moving servers can likewise expend as much as 60% of pinnacle power utilization. To measure the energy consumed by processor, and we call these are a load balancing techniques, we introduced many algorithm like Power Aware Load balancing (PALB), Double Threshold- Power Aware Load balancing (DT-PALB), Dynamic Round-Robin (DRR), Equally Spread Active Execution( ESCE ),Minimum Cost Maximum flow (MCMF). In this paper we compare algorithm and we will conclude which algorithm is best for power aware load balancing in cloud.

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.

A Dynamic Round-Robin Packet Scheduling Algorithm

This paper puts forward a new dynamic round-robin (DYRR) packet scheduling algorithm with high efficiency and good fairness. DYRR algorithm introduces dynamic round-robin concept, that is, the allowance given to each of the flows in a given round is not fixed, but is related with the number of bytes sent of this and other flows of the last round scheduling. The time complexity of the DYRR algorithm is O(1). Results from performance simulation analysis shows that DYRR algorithm can effectively smooth output burst, realize fair scheduling, and have a good time delay characteristic.

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.