• International Journal of Computer Science & Network Security
• /
• v.23 no.7
• /
• pp.165-170
• /
• 2023

Scheduling algorithms plays a significant role in optimizing the CPU in operating system. Each scheduling algorithms schedules the processes in the ready queue with its own algorithm design and its properties. In this paper, the performance analysis of First come First serve scheduling, Non preemptive scheduling, Preemptive scheduling, Shortest Job scheduling and Round Robin algorithm has been discussed with an example and the results has been analyzed with the performance parameters such as minimum waiting time, minimum turnaround time and Response time.

• International Journal of Computer Science & Network Security
• /
• v.21 no.1
• /
• pp.19-26
• /
• 2021

CPU is considered the main and most important resource in the computer system. The CPU scheduling is defined as a procedure that determines which process will enter the CPU to be executed, and another process will be waiting for its turn to be performed. CPU management scheduling algorithms are the major service in the operating systems that fulfill the maximum utilization of the CPU. This article aims to review the studies on the CPU scheduling algorithms towards comparing which is the best algorithm. After we conducted a review of the Round Robin, Shortest Job First, First Come First Served, and Priority algorithms, we found that several researchers have suggested various ways to improve CPU optimization criteria through different algorithms to improve the waiting time, response time, and turnaround time but there is no algorithm is better in all criteria.

• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.941-950
• /
• 2017

The round robin algorithm is regarded as one of the most efficient and effective CPU scheduling techniques in computing. It centres on the processing time required for a CPU to execute available jobs. Although there are other CPU scheduling algorithms based on processing time which use different criteria, the round robin algorithm has gained much popularity due to its optimal time-shared environment. The effectiveness of this algorithm depends strongly on the choice of time quantum. This paper presents a new effective round robin CPU scheduling algorithm. The effectiveness here lies in the fact that the proposed algorithm depends on a dynamically allocated time quantum in each round. Its performance is compared with both traditional and enhanced round robin algorithms, and the findings demonstrate an improved performance in terms of average waiting time, average turnaround time and context switching.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.4
• /
• pp.835-842
• /
• 2012

Operating Systems is a discipline which handles abstract concepts and techniques. However, most of OS courses have been textbook-oriented theoretical classes. Theoretical classes lead to the decline in the understanding of a lecture, and hurt their concentration. Many instructors have tried to make use of educational tools to help students understand lectures and arouse interests. This paper describes the design and implementation of a CPU scheduling simulator which shows the operation of process scheduling algorithms visually. The academic achievement evaluation for 2010's students and 2011's and t-test results show that the differences of the correct answer ratio for the exam about CPU scheduling algorithms are meaningful. The survey shows that the simulator is useful as an educational tool which causes the interests and enhances the understanding of a lecture, this teaching method is effective to develop problem solving skills.

• Journal of Korea Multimedia Society
• /
• v.14 no.3
• /
• pp.449-461
• /
• 2011

In the field of computer science, operating system concept is taught in university, but we now teach it in the middle and/or high school. Computer is also taught not only in college but also in middle and high school. If we look up the education of computer that is trained in school, basic principles or core techniques of computer science is educated only with its theory. If the theoretical education of computer science is just trained, sometimes students are not interested in it because of lack of shortage of mass media. Therefore, we could say that it is important that the computer education features a diverse range of media, including prints, paintings, sculpture, digital photographs, mixed media, and a simulation program. For all this reason, we design and implement a program for simulation with computer operating systems especially, CPU scheduling. There are many CPU scheduling algorithms we suggest to make students understand scheduling with some different examples in practical use. In this paper, we practically propose a new approach to be used with a study tool to make a motivation for students. We design a simulation program for teaching computer operation systems to show CPU scheduling and we implement a program to make use of comparison of FCFS, SJFS, PS, and RR scheduling algorithms. With our simulation program we present a comparative analysis between scheduling algorithms could be possible.

• Journal of Information Technology Applications and Management
• /
• v.22 no.2
• /
• pp.1-17
• /
• 2015

In this research, we develop and suggest branch and bound algorithms for a two-machine permutation flowshop scheduling problem with the objective of minimizing makespan. In this scheduling problem, after each job is operated on the machine 1 (first machine), the job has to start its second operation on machine 2 (second machine) within its corresponding limited waiting time. In addition, each job has its corresponding ready time at the machine 1. For this scheduling problem, we develop various dominance properties and three lower bounding schemes, which are used for the suggested branch and bound algorithm. In the results of computational tests, the branch and bound algorithms with dominance properties and lower bounding schemes, which are suggested in this paper, can give optimal solution within shorter CPU times than the branch and bound algorithms without those. Therefore, we can say that the suggested dominance properties and lower bounding schemes are efficient.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.1-9
• /
• 2024

This paper proposes an integration of the ED-H scheduling algorithm, known for optimal real-time scheduling, with the LoRaEnergySim simulator. This integration facilitates the simulation of interactions between real-time scheduling algorithms for tasks with time constraints in Class-A LoRaWAN Class-A devices using a super-capacitor-based energy harvesting system. The time and energy characteristics of LoRaWAN status and state transitions are extracted in a log format, and the task model is structured to suit the time-slot-based ED-H scheduling algorithm. The algorithm is extended to perform tasks while satisfying time constraints based on CPU executions. To evaluate the proposed approach, the ED-H scheduling algorithm is executed on a set of tasks with varying time and energy characteristics and CPU occupancy rates ranging from 10% to 90%, under the same conditions as the LoRaEnergySim simulation results for packet transmission and reception. The experimental results confirmed the applicability of co-simulation by demonstrating that tasks are prioritized based on urgency without depleting the supercapacitor's energy to satisfy time constraints, depending on the scheduling algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3663-3679
• /
• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.374-388
• /
• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• The Transactions of the Korea Information Processing Society
• /
• v.1 no.3
• /
• pp.367-379
• /
• 1994

This paper describes scheduling algorithms of the UNIX operating system and shows an analytical approach to approximate the average conditional response time for a process in the UNIX operating system. The average conditional response time is the average time between the submittal of a process requiring a certain amount of the CPU time and the completion of the process. The process scheduling algorithms in thr UNIX system are based on the priority service disciplines. That is, the behavior of a process is governed by the UNIX process schuduling algorithms that (ⅰ) the time-shared computer usage is obtained by allotting each request a quantum until it completes its required CPU time, (ⅱ) the nonpreemptive switching in system mode and the preemptive switching in user mode are applied to determine the quantum, (ⅲ) the first-come-first-serve discipline is applied within the same priority level, and (ⅳ) after completing an allotted quantum the process is placed at the end of either the runnable queue corresponding to its priority or the disk queue where it sleeps. These process scheduling algorithms create the round-robin effect in user mode. Using the round-robin effect and the preemptive switching, we approximate a process delay in user mode. Using the nonpreemptive switching, we approximate a process delay in system mode. We also consider a process delay due to the disk input and output operations. The average conditional response time is then obtained by approximating the total process delay. The results show an excellent response time for the processes requiring system time at the expense of the processes requiring user time.