Enhanced Precedence Scheduling Algorithm with Dynamic Time Quantum (EPSADTQ)

Background: The most popular time-sharing operating systems scheduling technique, whose efficiency heavily dependent on time slice selection, is the round robin CPU scheduling algorithm. The time slice works similar to the First-Come-First-Serve (FCFS) scheduling or processor sharing algorithm if it is large or extremely too small. Some of the existing research papers have an algorithm called Improved Round Robin with Highest Response Ratio Next (IRRHRRN) which made use of response ratio with a predefined time quantum of 10ms with the major aim of avoiding starvation. However, the IRRHRRN algorithm favors processes with shorter burst time than the ones with longer burst time, and gave no regard to the process arrival time, thus leading to starvation. Aim: This study tries to improve on the IRRHRRN algorithm by proposing the Modified Round Robin with Highest Response Ratio Next (MRRHRRN) CPU Scheduling Algorithm using Dynamic Time Quantum in order to reduce the problem of starvation. Method: Dynamic method of determining the time quantum was adopted. Results: The proposed algorithm was compared with four other existing algorisms such as Standard Round Robin (RR), Improved Round Robin (IRR), An Additional Improvement in Round Robin (AAIRR), and the Improved Round Robin with Highest Response Ratio Next (IRRHRRN) and it provided some promising results in terms of the Average Waiting Time of 35407.6 ms, Average Turnaround Time of 36117.6 ms, Average Response Time of 10894.8 ms and Number of Context Switch of 301for the Non-Zero Arrival Times Processes

Cloud computing is one of the most emerging technologies which has created a revolution in the High performance Computing (HPC) domain. The term Quality of Service (QoS) plays a vital role in the formation of more flexible integration of various technologies. The Waiting Time (WT), Turnaround Time (TAT), Context Switching (CS) and Makespan (MS) are the primary parameter that has great impact on the scheduling of cloudlets. The Proposed algorithm has improved the resource utilization system of the existing Round Robin Algorithm (RRA) and Improved Round Robin Cloudlet Scheduling Algorithm (IRRCSA) by introducing the concept of dynamically calculated Time Quantum (TQ) for each virtual machine (VM) according to the allocated cloudlets. This new approach in cloudlet scheduling drastically reduced average WT, average TAT and Number of CS of the VMs, which further enhanced the capability of cloud service providers (CSPs) to provide better QoS.

A multitasking operating system allows many programs to run at the same time. We need to schedule our Central Processing Units (CPUs) efficiently to handle these services. CPU scheduling algorithms come in a score of forms and any strategy has advantages and disadvantages. We implemented a Multi-Level Feedback Queue (MLFQ) algorithm with static time quantum for the first queue, making an efficient scheduling algorithm of MLFQ dynamic time quantum used in the second queue. Other than that, we compared both results and observed which dynamic time quantum delivers the best result. In the first queue, we used the Round Robin (RR) algorithm with less quantum time for processes that have a short burst time. The process that had more burst time than the defined quantum in the first queue was allowed to move into the second queue. Here, we calculated the average burst time of all remaining processes and defined that burst time as a quantum for the second queue after the Shortest Job First (SJF) scheme was applied in this queue. As a result, 70% of the processes in the second queue was received CPU. Other processes moved into the lower queue (the last queue). Hence, this technique prevented the starvation problem for those processes which have large burst times.

In this paper, a new variant of Round Robin (RR) algorithm is proposed which is suitable for soft real time systems. RR 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. We have proposed a novel algorithm, known as Priority Based Dynamic Round Robin Algorithm(PBDRR), which calculates intelligent time slice for individual processes and changes after every round of execution. The proposed scheduling algorithm is developed by taking dynamic time quantum concept into account. Our experimental results show that our proposed algorithm performs better than algorithm in [8] in terms of reducing the number of context switches, average waiting time and average turnaround time.

In the realm of real-time and multitasking environments, the Round Robin (RR) CPU scheduling algorithm is extensively utilized. Renowned for its fairness and avoidance of process starvation, RR allocates a specific time quantum to each process. However, the frequent context switching between processes during CPU scheduling, owing to the short time quantum, can adversely impact system performance by increasing average waiting time and response waiting time. To address these concerns, this paper introduces "Improving Round Robin Scheduling Using Dynamic Time Quantum (IRRDQ)," a modified version of RR aimed at diminishing turnaround time, average waiting time, and context switching. In our proposed approach, we arrange all incoming processes based on minimum burst time and dynamically assign an optimal time quantum to each process using the Shortest Job First (SJF) algorithm. The computation of time quantum is tailored to the burst times of individual processes. Through experimental demonstrations, we showcase the significant performance improvement of our algorithm compared to RR and other existing algorithms.

The Shortest Job First (SJF) algorithm reduces the average waiting time of processes in a CPU environment; however, it may lead to the starvation of long processes. The Round Robin (RR) algorithm solves starvation by equally distributing processing time. This paper explores user-friendly improvements by allowing users to specify which processes should be finished first. The SJF, RR, and the user-priority SJFRR were compared using four test cases in the following criteria: context switching, average waiting time, and average turnaround time. The user-priority SJFRR was found to have reduced average waiting time and average turnaround time in all test cases except for the first. Further research is also recommended in order to find out whether the algorithm's performance is attributed to the randomized assignment of priority and to find a proper basis for user designation of priority tasks.

In Round Robin Scheduling the time quantum is fixed and then processes are scheduled such that no process get CPU time more than one time quantum in one go. If time quantum is too large, the response time of the processes is too much which may not be tolerated in interactive environment. If time quantum is too small, it causes unnecessarily frequent context switch leading to more overheads resulting in less throughput. In this paper a method using fuzzy logic has been proposed that decides a value that is neither too large nor too small such that every process has got reasonable response time and the throughput of the system is not decreased due to unnecessarily context switches.

These days, the problems of scheduling and security are increasingly pressing as a result of the rapidly growing number of implementations that are operated in operating systems. Process scheduling and scheduling security is the most effective methodology of operating a system which can improve and degrade the performance of the computer system. The performance of scheduling algorithm in operating system can be measured by scheduling principles like average waiting time, average turnaround time, response time, throughput etc. Much research carried out over operating system security and round robin scheduling used in time sharing operating system in previous years to resolve the issues regarding to improvement in the performance of round robin (RR) scheduling and improving the security in the scheduling approach. This study discussed the security issues in operating systems, scheduling security and discrete structure of a new approach for RR scheduling. The researcher has suggested a list of policy for scheduling method security and proposed a new approach for RR scheduling and investigated the scheduling principles. The proposed methodology covers distinctive strategy for selection manner of process from ready queue than RR and used diverges time quantum. The proposed methodology has been validated experimentally by comparing with a numerous scheduling algorithm namely as Round Robin (RR), Adaptive Round Robin (ARR), Round Robin Remaining time (RRRT), improved Round Robin (IRR), an additional improvement on the improved Round Robin (AAAIRR), and an Enhanced Round Robin (ERR). Numerous simulations have been conducted to validate the effectiveness of the proposed algorithm to compelling the performance of system. At the conclusion the performance of computing system is dependent on security of operating system as well as secluding methods.

PurposeSea Lion Optimization (SLnO) algorithm involves the ability of exploration and exploitation phases, and it is able to solve combinatorial optimization problems. For these reasons, it is considered a global optimizer. The scheduling operation is completed by imitating the hunting behavior of sea lions.Design/methodology/approachCloud computing (CC) is a type of distributed computing, contributory in a massive number of available resources and demands, and its goal is sharing the resources as services over the internet. Because of the optimal using of these services is everlasting challenge, the issue of task scheduling in CC is significant. In this paper, a task scheduling technique for CC based on SLnO and multiple-objective model are proposed. It enables decreasing in overall completion time, cost and power consumption; and maximizes the resources utilization. The simulation results on the tested data illustrated that the SLnO scheduler performed better performance than other state-of-the-art schedulers in terms of makespan, cost, energy consumption, resources utilization and degree of imbalance.FindingsThe performance of the SLnO, Vocalization of Whale Optimization Algorithm (VWOA), Whale Optimization Algorithm (WOA), Grey Wolf Optimization (GWO) and Round Robin (RR) algorithms for 100, 200, 300, 400 and 500 independent cloud tasks on 8, 16 and 32 VMs was evaluated. The results show that SLnO algorithm has better performance than VWOA, WOA, GWO and RR in terms of makespan and imbalance degree. In addition, SLnO exhausts less power than VWOA, WOA, GWO and RR. More precisely, SLnO conserves 5.6, 21.96, 22.7 and 73.98% energy compared to VWOA, WOA, GWO and RR mechanisms, respectively. On the other hand, SLnO algorithm shows better performance than the VWOA and other algorithms. The SLnO algorithm's overall execution cost of scheduling the cloud tasks is minimized by 20.62, 39.9, 42.44 and 46.9% compared with VWOA, WOA, GWO and RR algorithms, respectively. Finally, the SLnO algorithm's average resource utilization is increased by 6, 10, 11.8 and 31.8% compared with those of VWOA, WOA, GWO and RR mechanisms, respectively.Originality/valueTo the best of the authors’ knowledge, this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere.

Scheduling is one of the most important factors used in scheduling processes insideCPU. CPU scheduling is a concept of multiprogramming, where the CPU is used to schedule the incoming processes alternately. Many algorithms can be used to schedule processesinside CPU, but not all can be real-time. Long waiting times and response times often be problems in scheduling processes in realtime. FIFO and Round Robin algorithms can be implemented to schedule the processes in realtime. In this paper, the authors schedule the process of several sensors that are used to collect landslide data. The data processing is sent by FIFO scheduling and Round Robin scheduling separately on the Internet of Things (IoT) device. The author only analyzes the performance of FIFO and Round Robin algorithms in scheduling the incoming processes in real-time on the IoT operating system by considering the waiting time and response time. The analysis is expected to create a quick response time and waiting time so that proper algorithm is decided to complement the IoT architecture in landslide detection. The FIFO and Round Robin algorithms are implementedat the Raspbian and Arch Linux operating systems in the IoT device, the Raspberry Pi 3 Model B, which uses a 64-bit 64-bit ARM Cortex-AS3 64-bit process at 1.2GHz.

Improved Performance of Round Robin CPU Scheduling Algorithm Using Non-preemptive SJF

Cloud computing is an advanced technology that offers types of assistance on requests. Because of the huge measure of requests got from cloud clients, all requests should be managed efficiently. Therefore, the task scheduling is critical in cloud computing. The provision of computational resources in cloud is controlled by a cloud provider. It is necessary to design high-efficiency scheduling algorithms that are compatible with the corresponding computing paradigms. This paper introduces a new task scheduling method for cloud computing called an ameliorated Round Robin algorithm (ARRA). The proposed algorithm develops an optimal time quantum based on the average of task burst time using fixed and dynamic manners. The experimental results showed that the ARRA significantly outperformed other algorithms including improved RR, enhanced RR, dynamic time quantum approach (ARR) and enhanced RR (RAST ERR) in terms of the average waiting time, average turnaround time and response time.

As can be expected in a few years the fifth generation (5G) networks will support several thousands of User Equipment (UEs). The traditional scheme of Random Access (RA) under such circumstances would fail to reduce the large delay in access. After the concept of Non-Orthogonal Multiple Access, the idea of Non-Orthogonal Random Access technique based on Successive Interference Cancellation (SIC) was proposed. This paper proposes an improvement in the delay reduction in the SIC-based NORA scheme by evolving the Preamble transmission with round-robin scheduling to improve the fast communication of NORA. The paper demonstrates how NORA with Round Robin Scheduling of Preamble is superior to simple NORA. Round Robin (RR) is one of the fundamental and widely used scheduling algorithms. The RR algorithm assigns equal portions of packet transmission time to each user in a circular order. RR algorithm achieves the best fairness performance if the users have similar channel conditions and similarly sized packet arriving at their buffers. It is on a first come first served basis. This paper attempts to provide a comparison of access delay improvement in 5G by comparing results of previous techniques to the proposed NORA with Round Robin Technique.

Developing a new scheduling algorithm and conducting the performance analysis to recognize its effect in practice can be a laborious task. CPU scheduling is crucial in achieving the operating system's (OS) design goals. There exists a variety of scheduling algorithms in the field and in this paper, a performance comparison of different existing scheduling algorithms by simulating the same bundle of tasks is carried out. A variety of algorithms under batch OS and time-sharing OS are considered. Upon the analysis, a novel task scheduling algorithm incorporating the merits of existing algorithms is proposed for a single CPU system. The performance of various algorithms is compared with the proposed algorithm for parameters viz., throughput, CPU utilization, average turnaround time, waiting time, and response time. Extensive simulation analysis for the various bundle of tasks is conducted and the proposed algorithm is found to outperform the other algorithms in terms of guaranteed reduced average response time. Thus, an efficient CPU scheduler is proposed to accommodate varying workloads at run-time making the best use of the CPU in a particular execution scenario.

Server cluster systems equipped with virtual machines are widely used to realise scalable and high-performance computing systems. In order to satisfy application requirements like response time, processing loads of virtual machines have to balance with one another in a server cluster. In addition to achieve the performance objectives, the total electric energy of a server cluster to perform application processes has to be reduced. In this paper, the Energy Consumption Laxity Based (ECLB) algorithm is proposed to allocate computation type application processes to virtual machines in a server cluster so that the total electric energy of the server cluster and response time of each process can be reduced. We evaluate the ECLB algorithm compared with basic Round-Robin (RR) algorithm. Evaluation results show the average total electric energy of a server cluster and average response time of each process in the ECLB algorithm can be more reduced than in the RR algorithm.