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1
Purnomo, Rakhmat, and Tri Dharma Putra. "Comparison Between Simple Round Robin and Improved Round Robin Algorithms." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 9, no. 3 (2022): 2205–21. http://dx.doi.org/10.35957/jatisi.v9i3.2547.
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The objective of this journal is to compare the efficiency between these two algorithms, the simple round robin and improved round robin algorithms. In real time systems algorithm, round robin plays a significant role to be used in embedded systems. Here we compare the average turn around time and average waiting time, also number of context switching between these two algorithms. Improved round robin algorithm, is an algorithm where if the remaining burst time is less than the allocated time quantum then the running process is executed. Then remove the currently running process from ready queue and put it in the tail of the ready queue while in simple round robin algorithm the remaining burst time will be executed until finish as scheduled. This comparison proves that improved round robin algorithm is more efficient, with lower average turn around time and lower average waiting time, lower context switching. There by this increases the system throughput.
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Putra, Tri Dharma, and Rakhmat Purnomo. "Comparison Between Simple Round Robin and Improved Round Robin Algorithms." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 10, no. 1 (2023): 266–72. http://dx.doi.org/10.35957/jatisi.v10i1.4824.
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The objective of this journal is to compare the efficiency between these two algorithms, the simple round robin and improved round robin algorithms. In real time systems algorithm, round robin plays a significant role to be used in embedded systems. Here we compare the average turn around time and average waiting time, also number of context switching between these two algorithms. Improved round robin algorithm, is an algorithm where if the remaining burst time is less than the allocated time quantum then the running process is executed. Then remove the currently running process from ready queue and put it in the tail of the ready queue while in simple round robin algorithm the remaining burst time will be executed until finish as scheduled. This comparison proves that improved round robin algorithm is more efficient, with lower average turn around time and lower average waiting time, lower context switching. There by this increases the system throughput.
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Supreeth, S., and Biradar Shobha. "Scheduling Virtual Machines for Load balancing in Cloud Computing Platform." International Journal of Science and Research (IJSR) 2, no. 6, June 2013 (2013): 437–41. https://doi.org/10.5281/zenodo.6423763.
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Cloud computing enables developers to automatically deploy applications during task allocation and storage distribution by using distributed computing technologies in numerous servers. To gain the maximum benefit from cloud computing, developers must design mechanisms that optimize the use of architectural and deployment paradigms. The role of Virtual Machine’s (VMs) has emerged as an important issue because, through virtualization technology, it makes cloud computing infrastructures to be scalable. Therefore developing on optimal scheduling of virtual machines is an important issue. In this paper a analysis of different existing Virtual Machine’s (VM’s) scheduling algorithms are done and proposed a weighted Round Robin algorithm over Round Robin algorithm in Virtual Machine environment of cloud computing in order to achieve better overall response time and processing time. The simulation results show the weighted round robin algorithm shows better improvements over Round-Robin algorithm. Then Comparison between Round Robin and Weighted Round Robin algorithm shows there is a improvement in Weighted Round Robin algorithm.
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Zouaoui, Sonia, Lotfi Boussaid, and Abdellatif Mtibaa. "Priority based round robin (PBRR) CPU scheduling algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 190–202. https://doi.org/10.11591/ijece.v9i1.pp190-202.
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This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, and large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.
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Zouaoui, Sonia, Lotfi Boussaid, and Abdellatif Mtibaa. "Priority based round robin (PBRR) CPU scheduling algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 190. http://dx.doi.org/10.11591/ijece.v9i1.pp190-202.
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<p>This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.</p>
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Santika, Monica, and Seng Hansun. "Implementasi Algoritma Shortest Job First dan Round Robin pada Sistem Penjadwalan Pengiriman Barang." Jurnal ULTIMATICS 6, no. 2 (2014): 94–99. http://dx.doi.org/10.31937/ti.v6i2.336.
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Delivery of goods will normally be conducted in accordance with the queuing time of booking. Sometimes, it is inefficient and results in a delay on the delivery of goods. Therefore, to make a better scheduling system, the Shortest Job First and Round Robin algorithms been implemented. From the results of experiments, Shortest Job First and Round Robin algorithms successfully applied to the scheduling delivery application. Shortest Job First algorithm is better than Round Robin scheduling in the case of delivery of goods, because the algorithm execution process which takes small time will be moved before the process which takes much time, so it needs smaller time than using Round Robin algorithm.
 Index Terms - Round Robin, Scheduling, Shipping, Shortest Job First
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Et. al., D. Gritto,. "Enhanced Time Quantum based Round Robin Algorithm for Cloudlet Scheduling in Cloud Environment." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 10 (2021): 5629–38. http://dx.doi.org/10.17762/turcomat.v12i10.5374.
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The contemporary organization integrates most of the required resources into their business environment by adopting or leasing the cloud resources that are offered by many of the remote cloud service providers. The cloud computing renders hassle free installation, deployment and maintenance of the resources. The cloud resources and services are observed to be pervasive in nature and therefore efficient technologies are to be adopted in order ensure the effective resource utilization and optimal service delivery to the cloud users. Generally virtualization, optimal scheduling techniques like cloudlet scheduling, virtual machine scheduling and load balancing strategies maximize the resource utilization and service delivery. This paper outlines the foundation concepts of cloud computing and proposes an algorithm named Enhanced Time Quantum based Round Robin Algorithm (ETQRRA). The ETQRRA is proposed to reduce the response time, waiting time, turnaround time and the number of context switching. The result of ETQRRA algorithm is compared with various versions of the existing Round Robin algorithms like Classic Round Robin Algorithm (CRR), Improved Shortest Remaining Burst Round Robin (ISRBRR), Half Life Variable Quantum Time Round Robin (HLVQTRR), Improved Round Robin Varying Quantum (IRRVQ) and Dynamic Time Quantum Round Robin (DTQRR) algorithms to prove the efficiency of ETQRRA. The comparative study shows the performance of ETQRRA outdo the other algorithms taken for the comparison.
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Putra, Tri Dharma, and Rakhmat Purnomo. "Average Max Round Robin Algorithm: A Case Study." sinkron 8, no. 4 (2023): 2662–69. http://dx.doi.org/10.33395/sinkron.v8i4.12051.
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Round Robin Algorithm is one wellknown algorithm in real time system. Several variants of round robin algorithms are in the fields. Average max round robin algorithm is a breakthrough to optimize context switching or also called quantum. Context switching is one big problem in round robin algorithm. To optimize high context switching is the key solution. This will make this algorithm efficient. There should be a way to optimize this context switching. Then the average max round robin algorithm is one solution to this problem. The average max algorithm is defined by finding the average of burst time then add the maximum burst time to the average burst time. Then calculate again the average of the two. The calculation will be iterated in the next round robin cycle. Here, in this journal, three case studies are discussed. Each with different burst times to understand this average max round robin algorithm more clearly. In the first case study we get turn around time 34 ms, and average waiting time 20.6 ms. In the second case study, we get average turn around time 21.8 ms, and the average waiting time 13 ms. And in the last case study, the third one, we get turn around time 12.2 ms, and the average waiting time 6.6 ms. There is no calculation for the second iteration for all case studies. Since the left burst time is only in one process. Optimizing the context switching, minimizing average turnaround time, and average waiting time is the key solution to round robin algorithm.
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Putra, Tri Dharma, and Rakhmat Purnomo. "Average Max Round Robin Algorithm: A Case Study." Sinkron 8, no. 3 (2023): 1230–37. http://dx.doi.org/10.33395/sinkron.v8i3.12051.
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Round Robin Algorithm is one wellknown algorithm in real time system. Several variants of round robin algorithms are in the fields. Average max round robin algorithm is a breakthrough to optimize context switching or also called quantum. Context switching is one big problem in round robin algorithm. To optimize high context switching is the key solution. This will make this algorithm efficient. There should be a way to optimize this context switching. Then the average max round robin algorithm is one solution to this problem. The average max algorithm is defined by finding the average of burst time then add the maximum burst time to the average burst time. Then calculate again the average of the two. The calculation will be iterated in the next round robin cycle. Here, in this journal, three case studies are discussed. Each with different burst times to understand this average max round robin algorithm more clearly. In the first case study we get turn around time 34 ms, and average waiting time 20.6 ms. In the second case study, we get average turn around time 21.8 ms, and the average waiting time 13 ms. And in the last case study, the third one, we get turn around time 12.2 ms, and the average waiting time 6.6 ms. There is no calculation for the second iteration for all case studies. Since the left burst time is only in one process. Optimizing the context switching, minimizing average turnaround time, and average waiting time is the key solution to round robin algorithm.
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Putra, Muhammad Taufik Dwi, Haryanto Hidayat, Naziva Septian, and Tiara Afriani. "Analisis Perbandingan Algoritma Penjadwalan CPU First Come First Serve (FCFS) Dan Round Robin." Building of Informatics, Technology and Science (BITS) 3, no. 3 (2021): 207–12. http://dx.doi.org/10.47065/bits.v3i3.1047.
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CPU scheduling is important in multitasking and multiprocessing an operating system because of the many processes that need to be run in a computer. This causes the operating system to need to divide resources for running processes. CPU scheduling has several algorithms in it such as First Come First Serve (FCFS), Shortest Job First (SJF), Priority Scheduling, and Round Robin (RR) algorithms. The writing of this study is intended to compare the First Come First Serve and Round Robin algorithms with four specified parameters namely Average Turn Around Time, Waiting Time, Throughput, and CPU Utilization. The experiment was conducted with the First Come First Serve algorithm and the Round Robin of three different Quantum Times. These calculations at different quantum times aim to find out if the differences affect the advantages of the Round Robin algorithm over the First Come First Serve algorithm. The conclusion is that the First Come First Serve (FCFS) algorithm is superior to the Round Robin (RR) algorithm. This is indicated by the average turn around time, waiting time, and throughput values of the First Come First Serve algorithm more effective in running the process
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Thirumala Rao, B., M. Susmitha, T. Swathi, and G. Akhil. "Implementation Of Hybrid Scheduler In Hadoop." International Journal of Engineering & Technology 7, no. 2.7 (2018): 868. http://dx.doi.org/10.14419/ijet.v7i2.7.11084.
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The paper focusses on priority based round robin scheduling algorithm for scheduling jobs in Hadoop environment. By Using this Proposed Scheduling Algorithm it reduces the starvation of jobs. And the advantage of priority scheduling is that the process with the highest priority will be executed first. Combining the both strategies of round robin and priority scheduling algorithm a optimized algorithm is to be implemented. Which works more efficiently even after considering all the parameters of scheduling algorithm. This proposed algorithm is also compared with existing round robin and priority scheduling algorithms.
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Shafi, Uferah, Munam Shah, Abdul Wahid, et al. "A Novel Amended Dynamic Round Robin Scheduling Algorithm for Timeshared Systems." International Arab Journal of Information Technology 17, no. 1 (2019): 90–98. http://dx.doi.org/10.34028/iajit/17/1/11.
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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)
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Putra, Tri Dharma, and Rakhmat Purnomo. "A Review on AMRR and Improved Round Robin Algorithms: Comparative Study." sinkron 8, no. 4 (2024): 2354–60. http://dx.doi.org/10.33395/sinkron.v8i4.13563.
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Round Robin Algorithm is a dominant algorithm in real time system. Improved round robin and average max round robin, which is also called AMRR are two types with a breakthrough. Improved round robin is an algorithm where if the remaining burst time of the process is less than the quantum, then the running process will continue to be executed. Afterwards the next iteration will be executed as its turn. So, each iteration will have a vary of quantum. It is called a dynamic time quantum. Different with improved round robin, in AMRR, in every iteration, the quantum will be calculated. So, for every iteration, the quantum might be different, depending upon the quantum calculation of the rest burst time. The first stage of this algorithm is to calculate the average of the existing burst times. Then this average is added with the maximum existing burst time. This addition then will be divided, then we get the quantum. This calculation will be executed again after the iteration finish. Based on our analysis, with quantum 10 in these two algorithms. It is can be shown that the improved round robin is less efficient than AMRR, because its average turnaround time and average waiting time is lower. The average turnaround time is 17.25 ms for AMRR compared to 23.25 ms in improved round robin. And the average turnaround time is 9 ms for AMRR compared to 15 ms in improved round robin.
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Abukari, Arnold Mashud, Edem Kwedzo Bankas, and Mohammed Muniru Iddrisu. "An Enhanced Load Balancing Algorithm for Cloud Enterprise Resource Planning (ERP) Data in a Multi-Cloud Environment." Asian Journal of Research in Computer Science 16, no. 3 (2023): 197–209. http://dx.doi.org/10.9734/ajrcos/2023/v16i3356.
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Businesses and individuals have seen the need to adopt the cloud and mulit-cloud environment for their businesses and storage of data. The load balancing concerns especially in the multi-cloud environment was investigated and a new algorithm proposed. In this research, a proposed new load balancing algorithm is presented and compared with the Round Robin (RR) and Weighted Round Robin (WRR) algorithms. The proposed scheduling algorithm considered several Cloud ERP Data chunks to analyse the data transmission rate or throughput, the transmission delay, data loss and the Cloud ERP Data drop ratio. The proposed algorithm performed better compared to the Round Robin (RR) and Weighted Round Robin (WRR) in a multi cloud environment with data chunks above 150 in terms of throughput. The proposed algorithm again outperformed the RR and WRR with a recorded lower transmission delays and lower data loss.
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Purnomo, Rakhmat, and Tri Dharma Putra. "Comparative Study: Preemptive Shortest Job First and Round Robin Algorithms." Sinkron 8, no. 2 (2024): 756–63. http://dx.doi.org/10.33395/sinkron.v8i2.12525.
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Abstract: Operating system is a software acting as an interface between computer hardware and user. Operating system is known as a resource manager. The main responsibility of operating system is to handle resources of computer system. Scheduling is a key concept in computer multitasking and multiprocessing operating system design by switching the CPU among process. Shortest job first (SJF) and round robin are two wellknown algorithms in CPU processing. For shortest job first, this algorithm can be preemptived. In preemptive shortest job first, when a new process coming in, the process can be interupted. Where with round robin algorithm there will be time slices, context switching, or also called quantum, between process. In this journal we wil discuss comparative study between preemptive shortest job first and round robin algorithms. Three comparative studies will be discussed to understand these two algorithms more deeply. For all comparative study, the average waiting time and average turnaround time is more for round robin algorithm. In the first comparative study, we get average waiting time 52% more. For average turnaround time, 30% more. In second comparative analysis, we get 52 % average waiting time more and we get 35 % average turnaround time more. For third comparative analysis, average waiting time we get 50% more and for average turnaround time, we get 28% more. Thus it is concluded in our comparative study for these kind of data the preemptive shortest job first is more efficient then the round robin algorithm.
 
 Keywords: comparative study, premptive shortest job first algorithm, round robin algorithm, turn around time, average waiting time, time slice
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Ramadhan, Hardiyan Kesuma, and Sukma Wardhana. "Computer Networks Optimization using Load Balancing Algorithms on the Citrix ADC Virtual Server." Jurnal Online Informatika 6, no. 1 (2021): 103. http://dx.doi.org/10.15575/join.v6i1.672.
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In the digital era and the outbreak of the COVID-19 pandemic, all activities are online. If the number of users accessing the server exceeds IT infrastructure, server down occurs. A load balancer device is required to share the traffic request load. This study compares four algorithms on Citrix ADC VPX load balancer: round-robin, least connection, least response time and least packet using GNS3. The results of testing response time and throughput parameters show that the least connection algorithm is superior. There were a 33% reduction in response time and a 53% increase in throughput. In the service hits parameter, the round-robin algorithm has the evenest traffic distribution. While least packet superior in CPU utilization with 76% reduction. So algorithm with the best response time and throughput is the least connection. The algorithm with the best service hits is round-robin. Large scale implementation is recommended using the least connection algorithm regarding response time and throughput. When emphasizing evenest distribution, use a round-robin algorithm.
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Abdelhameed, Safaa Taher, Noor Alhode Mohamed Alkikly, and Ferdaws Omar Alkharbash. "Optimizing Round Robin Using Machine Learning Models (KNN) in CPU scheduling." International Science and Technology Journal 35, no. 1 (2024): 1–10. https://doi.org/10.62341/sana0913.
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Round Robin is considered as one of the most practically recognized process scheduling algorithms in CPU scheduling because it is simple and fair. However, the efficiency of Round Robin depends a lot upon the selection of an optimal time quantum. If the quantum is too small, then frequent context switches are needed by the CPU; therefore, the overhead increases, and thus, the average waiting time for the processes also becomes long. As a result, system performance is reduced as more and more CPU time is used up in context switching, instead of task execution. it may behave similarly to the First Come First Serve (FCFS) algorithm if the time quantum is excessively long, which leads to extended average waiting time. This paper proposes an improved Round Robin algorithm by incorporating machine learning, which optimally determines the time quantum dynamically. More precisely, the K-Nearest Neighbors algorithm will be used, with NumPy in charge of data processing, for the runtime prediction of an optimal time quantum considering characteristics of processes. The experimental results showed a considerable improvement in the parameters of average waiting, turnaround time, and the number of context switches with respect to the traditional Round Robin algorithm. Results indicated that machine learning efficiently modifies the predictable scheduling algorithms to make the scheduling process adaptive and efficient in operating systems. Key words: dynamic round robin, classical round robin, burst time, machine learning.
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Divya, M. O., and T. M. Prajesha. "INTELLIGENT ROUND ROBIN SCHEDULING ALGORITHM WITH DYNAMIC TIME QUANTUM." International Journal of Advances in Engineering & Scientific Research 2, no. 8 (2015): 05–09. https://doi.org/10.5281/zenodo.10726962.
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<strong>Abstract: </strong> <em>In this paper, we have studied various algorithms for scheduling of the processes in Operating System (OS). Amongst all the algorithms, Round Robin (RR) performs optimally in timeshared system because each process is given an equal amount of static time quantum. But the effectiveness of RR algorithm solely depends upon the choice of time quantum. We have made a comprehensive study and analysis of RR algorithm. We have proposed a new Improved-RR algorithm Intelligent RR (Intelligent Round Robin) by using Intelligent Time Slice. Our experimental analysis shows that Intelligent RR performs better than RR algorithm in terms of reducing the number of context switches, average waiting time and average turnaround time.</em> <strong><em>Keywords:</em></strong> Operating System, Scheduling Algorithm, Round Robin, Context switch, Waiting time, Turnaround time.
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Putra, Tri Dharma, and Rakhmat Purnomo. "Case Study: Improved Round Robin Algorithm." SinkrOn 7, no. 3 (2022): 950–56. http://dx.doi.org/10.33395/sinkron.v7i3.11530.
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In this journal, discussion is given to analyse the improved round robin algorithm more thoroughly. Round robin algorithm plays a significant role to be used in embedded systems. Round robin algorithm usually applied in real-time systems. Here, three case studies are given, and also the analysis of each case study. Comparisons are given about the average turn around time and average waiting time, also number of context switching between the three case studies. Improved round robin algorithm, is a modification from the generic round robin algorithm. In improved round robin algorithm if the remaining burst time is less than the time slice that is allocated, then the currently running process is continue to be executed. Then finish the currently running process from ready queue and execute the next ready queue. Three case studies are given with three different time quantum, which are 3, 4, and 5 ms. The result of this case study analysis is that, the efficiency of the quantum 5 ms is the most effective one. There is an increase of 50% context switching from quantum 3 to quantum 5. And for average turn around time we get 13.13% reduction in efficiency. While in average waiting time we get reduction 12.08% efficiency.
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Xu, Zhao Di, Xiao Yi Li, and Wan Xi Chou. "Algorithms of Determining any Perfect Matching Mi of Kv." Applied Mechanics and Materials 48-49 (February 2011): 170–73. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.170.
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A definition about edge-matrix is given. Two algorithms for solving perfect matching are obtained. Algorithms A is that perfect matching is determined by using edge coloring of edge-matrix ; Algorithm B is that perfect matching is determined by partitioning edge-matrix into sub matrix and also by solving perfect matching of a complete graph .The procedure of constructing round-robin tournament by using algorithm A and round-robin tournament by using algorithm B.
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Bagui, Sikha, and Evorell Fridge. "A Comparison of Fair Sharing Algorithms for Regulating Search as a Service API." Transactions on Networks and Communications 8, no. 6 (2021): 16–34. http://dx.doi.org/10.14738/tnc.86.9633.
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Providers of a Search as a Service (SaaS) environment must ensure that their users will not monopolize the service or use more than their fair share of resources. Fair sharing algorithms have long been used in computer networking to balance access to a router or switch, and some of these algorithms have also been applied to the control of queries submitted to search engine APIs. If a search query’s execution cost can be reliably estimated, fair sharing algorithms can be applied to the input of a SaaS API to ensure everyone has equitable access to the search engine.
 The novelty of this paper lies in presenting a Single-Server Max-Min Fair Deficit Round Robin algorithm, a modified version of the Multi-Server Max-Min Fair Deficit Round Robin algorithm. The Single-Server Max-Min Fair Deficit Round Robin algorithm is compared to three other fair sharing algorithms, token-bucket, Deficit Round Robin (DRR), and Peng and Plale’s [1] Modified Deficit Round Robin (MDRR) in terms of three different usage scenarios, balanced usage, unbalanced usage as well as an idle client usage, to determine which is the most suitable fair sharing algorithm for use in regulating traffic to a SaaS API. This research demonstrated that the Single-Server Max-Min Fair DRR algorithm provided the highest throughput of traffic to the search engine while also maintaining a fair balance of resources among clients by re-allocating unused throughput to clients with saturated queues so a max-min allocation was achieved.
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Putra, Tri Dharma, and Rakhmat Purnomo. "Simulation of Priority Round Robin Scheduling Algorithm." Sinkron 7, no. 4 (2022): 2170–81. http://dx.doi.org/10.33395/sinkron.v7i4.11665.
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In this journal, simulation of priority round robin scheduling algorithm is presented. To imitate the processes of operating system operation, simulation can be used. By simulation, model is used, namely models that represent the characteristics or behaviour of systems. Process scheduling is one important operation in operating system. OS-SIM can be used to model and simulate the operations of process scheduling. Some scheduling algorithms are available in modern operating systems, like First come First Serve (FCFS), Shortest Job First (SJF), Round Robin (RR), Priority Scheduling or combination of these algorithms. One important scheduling algorithm for real-time or embedded system is priority round robin scheduling algorithm. Priority round robin scheduling algorithm is a preemptive algorithm. Each process is given time quantum. Each process has a priority. Here time quantum 3 is given. The higher the time quantum, the more the context switching. By the use of OS-SIM, simulation can be understood easily and thoroughly. The statistics, will be calculated automatically by the system by the simulator, like the number of context switching, average waiting time, average turn around time, and average responds time. With one example, by using quantum=3. The average turn around time is 18.25 ms. The Average Waiting Time is 12 ms. The Average Responds time is 2.75 ms. The total burst time is 25 ms.
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Lenzini, Luciano, Enzo Mingozzi, and Giovanni Stea. "Performance analysis of Modified Deficit Round Robin schedulers." Journal of High Speed Networks 16, no. 4 (2007): 399–422. https://doi.org/10.3233/hsn-2007-325.
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Deficit Round Robin (DRR) is a scheduling algorithm which provides fair queuing at O(1) complexity. However, due to its round robin structure, its latency properties are not adequate for latency-critical applications, such as voice. For this reason, router manufacturers implement variants of the DRR algorithm which guarantee lower latencies to one (or a subset of) queue(s). In this paper we evaluate the performance of two such variants, both of which are known as Modified Deficit Round Robin, currently implemented in commercial routers. The comparison is carried out analytically, by deriving the latency and bandwidth guarantees of both algorithms, and by simulation.
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Nurcahya, Dimas, Siti Amatullah Karimah, and Satria Akbar Mugitama. "Performance Analysis of Scheduling Algorithms on Fog Computing using YAFS." Sinkron 8, no. 3 (2023): 1677–86. http://dx.doi.org/10.33395/sinkron.v8i3.12682.
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A smart device that has seen more development is the Internet of Things (IoT). An IoT system implementation requires a device that can accept and handle various sorts of data. Fog Computing is a solution to the issue since the IoT demands a device that can provide Real-Time. Certainly, load balancing involves scheduling the IoT devices and data used. Because Cloud and Fog Computing models enable data growth management and deployment planning, which necessitate a quicker response from platforms and applications, processing power scheduling is essential. The purpose of this study is to evaluate the performance of effective scheduling algorithms that adhere to these computing models platform requirements. The scheduling algorithm that can produce the lowest Processing Time and the resulting Time Efficiency is more efficient can be called the best scheduling algorithm. In this research, the author analyzes the performance of scheduling algorithms in the form of Round Robin and Priority Scheduling on Fog Computing. In this research, testing was carried out by creating a scenario of the effect of increasing the number of Fog Nodes and Devices used. The average result of scenario testing obtained for processing time for Round Robin is lower, and the highest Time Efficiency for Round Robin over Priority Scheduling is 11%. With these test results, the Round Robin scheduling algorithm has a simpler level of complexity. So, it can be concluded that Round Robin belongs to the category of the best scheduling algorithm in this case.
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Prasad, Vinay Kumar. "Optimized Load Balancing Using Adaptive Algorithm in Cloud Computing with Round Robin Technique." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 134–49. http://dx.doi.org/10.22214/ijraset.2022.45225.
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Abstract: Developments in the field of computer networks have been carried out by several groups. However, there are still a lot of wrong problems one is the server load. For this reason, a system will be implemented Load Balancing with the aim of overcoming the server load which is not in accordance with its capacity and to optimize server load before and after the implementation of the Round robin Algorithm Load Balancing system on the cloud servers. The method used is the comparative method, namely researches that compares and analyze two or more symptoms, compare least connection algorithm as the previous algorithm with Round robin algorithm. Load Balancing Testing with both algorithms using a software called Httperf. Httperf displays the value according to parameters. The parameters used are Throughput, Response Time, Error and CPU Utilization. The test results show that load balancing with the algorithm round robin is more effective to handle server load than algorithm.
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Alankar, Bhavya, Gaurav Sharma, Harleen Kaur, Raul Valverde, and Victor Chang. "Experimental Setup for Investigating the Efficient Load Balancing Algorithms on Virtual Cloud." Sensors 20, no. 24 (2020): 7342. http://dx.doi.org/10.3390/s20247342.
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Cloud computing has emerged as the primary choice for developers in developing applications that require high-performance computing. Virtualization technology has helped in the distribution of resources to multiple users. Increased use of cloud infrastructure has led to the challenge of developing a load balancing mechanism to provide optimized use of resources and better performance. Round robin and least connections load balancing algorithms have been developed to allocate user requests across a cluster of servers in the cloud in a time-bound manner. In this paper, we have applied the round robin and least connections approach of load balancing to HAProxy, virtual machine clusters and web servers. The experimental results are visualized and summarized using Apache Jmeter and a further comparative study of round robin and least connections is also depicted. Experimental setup and results show that the round robin algorithm performs better as compared to the least connections algorithm in all measuring parameters of load balancer in this paper.
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Al-Mekhlafi, Muneer Abdullah Saeed, and Nashwan Nagi Saleh Al-Marbe. "Lower and Upper Quartiles Enhanced Round Robin Algorithm for Scheduling of Outlier Tasks in Cloud Computing." Journal of Engineering and Technological Sciences - JOEATS 1, no. 1 (2023): 67–87. http://dx.doi.org/10.59421/joeats.v1i1.1420.
Full textAbstract:
Cloud computing is one of the top emerging technologies with
 huge market and enterprise potential as it provides on-demand, -based access
 to large-scale shared computing resources. Task scheduling is one of the most
 important issues in cloud computing in order to enhance performance and
 resource utilization while minimizing costs. Because of its simplicity and
 fairness, the round-robin algorithm is the ideal task scheduling algorithm,
 although it suffers from time complexity and cannot handle outlier tasks.
 Several modifications of Round Robin have been introduced to enhance time
 complexity. To ensure sufficient deal with time complexity and outlier tasks,
 this paper introduces a novel enhanced round-robin heuristic algorithm by
 utilizing the round-robin algorithm and updating its time quantum
 dynamically based on the lower and upper quartiles of the time quantum for
 all the tasks in the ready queue. The experimental results on four datasets
 showed that the proposed algorithm significantly outperformed baseline
 algorithms in terms of the average waiting time, turnaround time, and
 response time. The results show that, when compared to the baseline
 algorithm in cases 3 and 4, the proposed algorithm enhances the average
 waiting time's time complexity by 50% with datasets containing random and
 outlier tasks.
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Alhaidari, Fahd, and Taghreed Zayed Balharith. "Enhanced Round-Robin Algorithm in the Cloud Computing Environment for Optimal Task Scheduling." Computers 10, no. 5 (2021): 63. http://dx.doi.org/10.3390/computers10050063.
Full textAbstract:
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.
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Triangga, Hasta, Ilham Faisal, and Imran Lubis. "Analisis Perbandingan Algoritma Static Round-Robin dengan Least-Connection Terhadap Efisiensi Load Balancing pada Load Balancer Haproxy." InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) 4, no. 1 (2019): 70–75. http://dx.doi.org/10.30743/infotekjar.v4i1.1688.
Full textAbstract:
In IT networking, load balancing used to share the traffic between backend servers. The idea is to make effective and efficient load sharing. Load balancing uses scheduling algorithms in the process includes Static round-robin and Least-connection algorithm. Haproxy is a load balancer that can be used to perform the load balancing technique and run by Linux operating systems. In this research, Haproxy uses 4 Nginx web server as backend servers. Haproxy act as a reverse proxy which accessed by the client while the backend servers handle HTTP requests. The experiment involves 20 Client PCs that are used to perform HTTP requests simultaneously, using the Static round-robin algorithm and Least-connection on the haproxy load balancer alternately. When using Static round-robin algorithm, the results obtained average percentages of CPU usage successively for 1 minute; 5 minutes; and 15 minutes are; 0.1%; 0.25%; and 1.15% with average throughput produced is 14.74 kbps. Average total delay produced 64.3 kbps. The average total delay and jitter is 181.3 ms and 11.1 ms, respectively. As for the Least-connection algorithm average percentage obtained successively for 1 minute; 5 minutes; and 15 minutes are 0.1%; 0.3%; and 1.25% with the average throughput produced is 14.66 kbps. The average total delay and jitter is 350.3 ms and 24.5 ms, respectively. It means Static round-robin algorithm is more efficient than the algorithms Least-connection because it can produce a greater throughput with less CPU load and less total delay.
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Chhugani, Barkha, and Mahima Silvester. "Improving Round Robin Process Scheduling Algorithm." International Journal of Computer Applications 166, no. 6 (2017): 12–16. http://dx.doi.org/10.5120/ijca2017914034.
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., S. Jain, and H. Rohil. "Mode Based Round Robin Scheduling Algorithm." International Journal of Computer Sciences and Engineering 6, no. 6 (2018): 1399–403. http://dx.doi.org/10.26438/ijcse/v6i6.13991403.
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Sirohi, Abhishek, Aseem Pratap, and Mayank Aggarwal. "Improvised Round Robin (CPU) Scheduling Algorithm." International Journal of Computer Applications 99, no. 18 (2014): 40–43. http://dx.doi.org/10.5120/17475-8361.
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Alam. "FUZZY ROUND ROBIN CPU SCHEDULING ALGORITHM." Journal of Computer Science 9, no. 8 (2013): 1079–85. http://dx.doi.org/10.3844/jcssp.2013.1079.1085.
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Bhati, Roshi, Rahul Thambi, and Nikhil Nerurkar. "Various Variants of Round Robin Scheduling Algorithm." International Journal for Research in Applied Science and Engineering Technology 12, no. 7 (2024): 888–93. http://dx.doi.org/10.22214/ijraset.2024.63675.
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Abstract: In order to use the computer processor efficiently, different scheduling algorithms are used to manage the executionof multiple processes. One popular algorithm is called Round Robin (RR), where each process is given a short amount of time to run on the processor before switching to the next process inthe queue. The length of this time period, called a time quantum, is important in determining how efficient the scheduling is. If the time quantum is too long, it can increase the time it takes for a process to respond. If it is too short, it can increase the amount of time the processor spends switching between processes instead of actually executing them. In this paper, we explore different variants of the RR algorithm and compare their performancein terms of waiting time, turnaround time, and the number of times the processor switches between processes.
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He, Yong, Lei Gao, Gui Kai Liu, and Yu Zhen Liu. "A Dynamic Round-Robin Packet Scheduling Algorithm." Applied Mechanics and Materials 347-350 (August 2013): 2203–7. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2203.
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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.
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Kumar, Anil, Amit Kumar Gupta, Deepak Panwar, Sandeep Chaurasia, and Dinesh Goyal. "Operating system security with discrete mathematical structure for secure round robin scheduling method with intelligent time quantum." Journal of Discrete Mathematical Sciences and Cryptography 26, no. 5 (2023): 1519–33. http://dx.doi.org/10.47974/jdmsc-1816.
Full textAbstract:
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.
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Nafea, Omar Anwer, and Turkan Ahmed Khaleel. "An improved throttling algorithm for fog computing networks with an additional management layer." Al-Qadisiyah Journal for Engineering Sciences 17, no. 4 (2024): 390–99. https://doi.org/10.30772/qjes.2024.146104.1089.
Full textAbstract:
An emerging networking technique called fog computing extends cloud computing capabilities to the edge network's borders. It is employed to get around the limitations of cloud computing, like latency and bandwidth problems. Fog computing is suitable for IoT systems and applications that require real-time processing, reliable network access, low latency, and strong security. In this work, the objective is to design and implement a fog computing environment to simulate the behavior of a multi-user healthcare application, which represents the monitoring of elderly care homes in Mosul city. Several algorithms were employed to examine the effects of load balancing inside fog computing networks. These algorithms are Random, Round-Robin, and the modified Throttled algorithm, which is modified by adding an extra management layer to be more suitable for fog computing networks. The response time results obtained from implementing this modified method were superior to those of the random algorithm and closely resembled the response time results of the round-robin algorithm. In case QoS1 with 25 clients, the result was (0.246037794) second without the load balancing algorithm, (0.124323358) second in the Random algorithm, (0.115641477) second in the Round-Robin algorithm, and (0.114981575) second for the modified throttled algorithm. thus, making it applicable for fog computing networks and cloud computing networks.
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Iqbal, Mansoor, Zahid Ullah, Izaz Ahmad Khan, et al. "Optimizing Task Execution: The Impact of Dynamic Time Quantum and Priorities on Round Robin Scheduling." Future Internet 15, no. 3 (2023): 104. http://dx.doi.org/10.3390/fi15030104.
Full textAbstract:
Task scheduling algorithms are crucial for optimizing the utilization of computing resources. This work proposes a unique approach for improving task execution in real-time systems using an enhanced Round Robin scheduling algorithm variant incorporating dynamic time quantum and priority. The proposed algorithm adjusts the time slice allocated to each task based on execution time and priority, resulting in more efficient resource utilization. We also prioritize higher-priority tasks and execute them as soon as they arrive in the ready queue, ensuring the timely completion of critical tasks. We evaluate the performance of our algorithm using a set of real-world tasks and compare it with traditional Round Robin scheduling. The results show that our proposed approach significantly improves task execution time and resource utilization compared to conventional Round Robin scheduling. Our approach offers a promising solution for optimizing task execution in real-time systems. The combination of dynamic time quantum and priorities adds a unique element to the existing literature in this field.
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Biswas, Dipto, Md Samsuddoha, Md Rashid Al Asif, and Md Manjur Ahmed. "Optimized Round Robin Scheduling Algorithm Using Dynamic Time Quantum Approach in Cloud Computing Environment." International Journal of Intelligent Systems and Applications 15, no. 1 (2023): 22–34. http://dx.doi.org/10.5815/ijisa.2023.01.03.
Full textAbstract:
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.
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Gao, Chenhao, and Hengyang Wu. "An Improved Dynamic Smooth Weighted Round-robin Load-balancing Algorithm." Journal of Physics: Conference Series 2404, no. 1 (2022): 012047. http://dx.doi.org/10.1088/1742-6596/2404/1/012047.
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Abstract Load-balancing is a key component of highly available network infrastructure. Weighted round-robin is one of the important strategies to achieve load-balancing, which is a classic research subject. In recent years, the weighted round-robin algorithm has developed from static weight to dynamic. The Dynamic weighted round-robin algorithm needs further research in time-sensitive of dynamic weights and the rationality of results. Based on Nginx, this paper improves the dynamic weighting algorithm. Firstly, it proposes a method of dynamically calculating weights. The method determines the weight of the server in the cluster according to its theoretical performance and runtime state. Secondly, making the request allocation result more balanced and avoiding continuous centralized scheduling by an improved weighted algorithm. Experiments show that the algorithm proposed in this paper is effective and can improve system performance and load-balancing efficiency.
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ElDahshan, Kamal, Afaf Abd, and Nermeen Ghazy. "Achieving Stability in the Round Robin Algorithm." International Journal of Computer Applications 172, no. 6 (2017): 15–20. http://dx.doi.org/10.5120/ijca2017915161.
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Youm, Dong Hyun. "Load Balancing Strategy using Round Robin Algorithm." Asia-pacific Journal of Convergent Research Interchange 2, no. 3 (2016): 1–10. http://dx.doi.org/10.21742/apjcri.2016.09.01.
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Khatri, Jayanti. "An Enhanced Round Robin CPU Scheduling Algorithm." IOSR Journal of Computer Engineering 18, no. 04 (2016): 20–24. http://dx.doi.org/10.9790/0661-1804022024.
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Nawaz Tareen, Faheem, Ahmad Naseem Alvi, Badr Alsamani, Mohammed Alkhathami, Deafallah Alsadie, and Norah Alosaimi. "EOTE-FSC: An efficient offloaded task execution for fog enabled smart cities." PLOS ONE 19, no. 4 (2024): e0298363. http://dx.doi.org/10.1371/journal.pone.0298363.
Full textAbstract:
Smart cities provide ease in lifestyle to their community members with the help of Information and Communication Technology (ICT). It provides better water, waste and energy management, enhances the security and safety of its citizens and offers better health facilities. Most of these applications are based on IoT-based sensor networks, that are deployed in different areas of applications according to their demand. Due to limited processing capabilities, sensor nodes cannot process multiple tasks simultaneously and need to offload some of their tasks to remotely placed cloud servers, which may cause delays. To reduce the delay, computing nodes are placed in different vicinitys acting as fog-computing nodes are used, to execute the offloaded tasks. It has been observed that the offloaded tasks are not uniformly received by fog computing nodes and some fog nodes may receive more tasks as some may receive less number of tasks. This may cause an increase in overall task execution time. Furthermore, these tasks comprise different priority levels and must be executed before their deadline. In this work, an Efficient Offloaded Task Execution for Fog enabled Smart cities (EOTE − FSC) is proposed. EOTE − FSC proposes a load balancing mechanism by modifying the greedy algorithm to efficiently distribute the offloaded tasks to its attached fog nodes to reduce the overall task execution time. This results in the successful execution of most of the tasks within their deadline. In addition, EOTE − FSC modifies the task sequencing with a deadline algorithm for the fog node to optimally execute the offloaded tasks in such a way that most of the high-priority tasks are entertained. The load balancing results of EOTE − FSC are compared with state-of-the-art well-known Round Robin, Greedy, Round Robin with longest job first, and Round Robin with shortest job first algorithms. However, fog computing results of EOTE − FSC are compared with the First Come First Serve algorithm. The results show that the EOTE − FSC effectively offloaded the tasks on fog nodes and the maximum load on the fog computing nodes is reduced up to 29%, 27.3%, 23%, and 24.4% as compared to Round Robin, Greedy, Round Robin with LJF and Round Robin with SJF algorithms respectively. However, task execution in the proposed EOTE − FSC executes a maximum number of offloaded high-priority tasks as compared to the FCFS algorithm within the same computing capacity of fog nodes.
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A. Sheela, Mrs, and Mrs J. Ranjani. "An approach for dynamically load balanced flow scheduling(DLBS) in cloud." International Journal of Engineering & Technology 7, no. 3.3 (2018): 600. http://dx.doi.org/10.14419/ijet.v7i2.33.14844.
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The Paper based on load balanced flow scheduling algorithm. This algorithm is used in which huge amount of data send to multiple servers frequently without a few traffic, isolation in open flow network. In existing load balanced algorithm based on huge amount of data send to several server but it suffers from that that algorithm is not support to other open flow networks model and transmission pattern. In this proposed load balanced scheduled algorithm with Round Robin deals with maximizing the network throughput dynamically. The (Dynamically Load Balanced Flow Scheduling) DLBS problem is formulated , considerably a efficient heuristic scheduling algorithms was developed for the two typical Open Flow network model, they have data flow from time slot. The outcome represents load-balanced scheduling algorithms Round Robin and LOBUS with effective improvement in DLBS move toward will carry to the data centers. Plenty of researchers pay large number of attention on software-defined networking.
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Zohora, Most Fatematuz, Fahiba Farhin, and M. Shamim Kaiser. "An enhanced round robin using dynamic time quantum for real-time asymmetric burst length processes in cloud computing environment." PLOS ONE 19, no. 8 (2024): e0304517. http://dx.doi.org/10.1371/journal.pone.0304517.
Full textAbstract:
Cloud computing is a popular, flexible, scalable, and cost-effective technology in the modern world that provides on-demand services dynamically. The dynamic execution of user requests and resource-sharing facilities require proper task scheduling among the available virtual machines, which is a significant issue and plays a crucial role in developing an optimal cloud computing environment. Round Robin is a prevalent scheduling algorithm for fair distribution of resources with a balanced contribution in minimized response time and turnaround time. This paper introduced a new enhanced round-robin approach for task scheduling in cloud computing systems. The proposed algorithm generates and keeps updating a dynamic quantum time for process execution, considering the available number of process in the system and their burst length. Since our method dynamically runs processes, it is appropriate for a real-time environment like cloud computing. The notable part of this approach is the capability of scheduling tasks with asymmetric distribution of burst time, avoiding the convoy effect. The experimental result indicates that the proposed algorithm has outperformed the existing improved round-robin task scheduling approaches in terms of minimized average waiting time, average turnaround time, and number of context switches. Comparing the method against five other enhanced round robin approaches, it reduced average waiting times by 15.77% and context switching by 20.68% on average. After executing the experiment and comparative study, it can be concluded that the proposed enhanced round-robin scheduling algorithm is optimal, acceptable, and relatively better suited for cloud computing environments.
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Qazi, Farheen, Dur-e.-Shawar Agha, Muhammad Naseem, Shahnila Badar, and Fozia Hanif Khan. "Improving Round Robin Scheduling with Dynamic Time Quantum (IRRDQ)." Journal of Applied Engineering & Technology (JAET) 7, no. 2 (2023): 70–82. http://dx.doi.org/10.55447/jaet.07.02.115.
Full textAbstract:
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.
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Ghani, Rana Fareed, and Laith Al-Jobouri. "Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm." Electronics 12, no. 2 (2023): 462. http://dx.doi.org/10.3390/electronics12020462.
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Software-defined networks (SDNs) are computer networks where parameters and devices are configured by software. Recently, artificial intelligence aspects have been used for SDN programs for various applications, including packet classification and forwarding according to the quality of service (QoS) requirements. The main problem is that when packets from different applications pass through computer networks, they have different QoS criteria. To meet the requirements of packets, routers classify these packets, add them to multiple weighting queue systems, and forward them according to their priorities. Multiple queue systems in routers usually use a class-based weighted round-robin (CBWRR) scheduling algorithm with pre-configured fixed weights for each priority queue. The problem is that the intensity of traffic in general and of each packet class occasionally changes. Therefore, in this work, we suggest using the particle swarm optimization algorithm to find the optimal weights for the weighted fair round-robin algorithm (WFRR) by considering the variable densities of the traffic. This work presents a framework to simulate router operations by determining the weights and schedule packets and forwarding them. The proposed algorithm to optimize the weights is compared with the conventional WFRR algorithm, and the results show that the particle swarm optimization for the weighted round-robin algorithm is more efficient than WFRR, especially in high-intensity traffic. Moreover, the average packet-loss ratio does not exceed 7%, and the proposed algorithms are better than the conventional CBWRR algorithm and the related work results.
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Putra, Muhammad Aldi Aditia, Iskandar Fitri, and Agus Iskandar. "Implementasi High Availability Cluster Web Server Menggunakan Virtualisasi Container Docker." JURNAL MEDIA INFORMATIKA BUDIDARMA 4, no. 1 (2020): 9. http://dx.doi.org/10.30865/mib.v4i1.1729.
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The increasing demand for information on the internet causes the traffic load on the web server to increase. Therefore it can cause the workload on a web server service to be overloaded (request), so that the server is down (overloaded). Based on previous research the application of load balancing can reduce the burden of traffic on the web server. This research method uses load balancing on servers with round robin algorithm and least connections as well as a single server as a comparison. The parameters measured are throughput, responses time, requests per second, CPU utilization. From the test results obtained Haproxy load balancing system, the least connection algorithm is superior to the round robin algorithm. Generated per-second request value of 2607,141 req / s and throughput of 9.25 MB / s for the least connection, while 2807,171 req / s and 9.30 MB / s for round robin.
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N., Srilatha, Sravani M., and Divya Y. "Optimal Round Robin CPU Scheduling Algorithm using Manhattan Distance." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3664–68. https://doi.org/10.11591/ijece.v7i6.pp3664-3668.
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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. The performance of Round robin CPU scheduling algorithm is entirely dependent on the time quantum selected. 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 Manhattan distance has been proposed that decides a quantum value. The computation of the time quantum value is done by the distance or difference between the highest burst time and lowest burst time. The experimental analysis also shows that this algorithm performs better than RR algorithm and by reducing number of context switches, reducing average waiting time and also the average turna round time.