Robin Method Research Articles

A Proposed CPU Job-Scheduling Technique Based on Round Robin Method Using Dual Synchronized Time-Slices

A Proposed CPU Job-Scheduling Technique Based on Round Robin Method Using Dual Synchronized Time-Slices

Application of Round Robin in Scheduling in Web-Based Wedding Organizers

Wedding are cherished moments in the lives of couples. However, the complexity of wedding planning often poses challenges in arranging event schedules. To address this issue, this study aims to implement the Round Robin method for scheduling in a web-based Wedding Organizer. The Round Robin method is a scheduling algorithm that evenly allocates time for various necessary activities. In the context of a web-based Wedding Organizer, its implementation can optimize wedding activity scheduling by considering available time slots and avoiding scheduling conflicts among vendors. This research involves the development of a web-based application that employs the Round Robin method to organize the schedules of various vendors involved in weddings. The application offers convenience to couples-to-be and Wedding Organizers in viewing, organizing, and utilizing resources more effectively. With the application of the Round Robin method, it is anticipated that the operational efficiency of Wedding Organizers will improve, schedule conflicts will be mitigated, and the allocation of limited resources can be maximized. This study contributes to the advancement of a web-based Wedding Organizer scheduling.

Improved QoS with Fog computing based on Adaptive Load Balancing Algorithm

As the number of sensing devices rises, traffic on the cloud servers is boosting day by day. When a device connected to the IoTwants access to data, cloud computing encourages the pairing of fog & cloud nodes to provide that information. One of the key needs in a fog-based cloud system, is efficient job scheduling to decrease the data delay and improve the QoS (Quality of Service). The researchers have used a variety of strategies to maintain the QoS criteria. However, because of the increased service delay caused by the busty traffic, job scheduling is impacted which leads to the unbalanced load on the fog environment. The proposed work uses a novel model which curates the features and working style of Genetic algorithm and the optimization algorithm with the load balancing scheduling on the fog nodes. The performance of the proposed hybrid model is contrasted with the other well-known algorithms in contrast to the fundamental benchmark optimization test functions. The proposed work displays better results in sustaining the task scheduling process when compared to the existing algorithms, which include Round Robin (RR) method, Hybrid RR, Hybrid Threshold based and Hybrid Predictive Based models, which ensures the efficacy of the proposed load balancing model to improve the quality of service in fog environment.

Implementation of High Availability Message ISO 8583 using F5 Active-Passive Failover Method

In this research, the system was designed to solve problems related to High Availability on FDS (Fraud Detection System) servers that cannot be loaded balanced using the Round Robin method, resulting in changes to ISO 8583 messages. As a result, a method that can be used as High availability to maintain the Availability of the FDS Server without changing the message received is required. High availability will be achieved through the Active Passive Failover method, which will transfer data flows in the event of an operational failure on the FDS server. The transfer is based on CPU Load parameters and ISO 8583 messages, which are checked at each stage. The waterfall method was used in this research. The waterfall is a straightforward classic model with a linear system flow, with the output of each stage serving as the input for the next. The primary goals of this research are to ensure that data in ISO 8583 format can be streamed without changing messages, to measure the effectiveness of the Active Passive Failover method in performing High availability using ISO 8583 message parameters and CPU Load, and to increase the level of Availability and reliability of the FDS Server. This research's error rate decreased by 0.83%, and the SLA (Service Level Agreement) increased from 99.13% to 99.96%.

Achieving Consensus for Management of Hormone-Sensitive, Low-Volume Metastatic Prostate Cancer in Italy.

Metastatic hormone-sensitive prostate cancer (mHSPC) is usually categorized as high- or low-volume disease. This is relevant because low- and high-volume metastatic disease are associated with different outcomes, and thus management of the two forms should differ. Although some definitions have been reported, the concept of oligometastatic disease is not so clearly defined, giving rise to further variability in the choice of treatment, mainly between systemic agents and radiotherapy, especially in the era of metastasis-directed therapy. With the aim of providing clinicians with guidance on best practice, a group of medical and radiation oncologists, experts in prostate cancer, used the round robin method to generate a series of consensus statements on management of low-volume mHSPC. Consensus was obtained on three major areas of controversy: (1) with regard to clinical definitions of mHSPC, it was held that oligometastatic and low-volume disease refer to different concepts and should not be used interchangeably; (2) regarding therapy of de novo low-volume metastatic disease, androgen deprivation therapy alone can be considered undertreatment, and all patients should be evaluated for systemic treatment combinations; local therapy should not be denied in patients with mHSPC, regardless of the intensity of systemic therapy, and metastasis-directed therapy can be proposed in selected cases; (3) with regard to treatment of metachronous metastatic disease, patients should be evaluated for systemic treatment combinations. Metastasis-directed therapy can be proposed to delay systemic treatment in selected cases, especially if prostate-specific membrane antigen positron emission tomography staging has been performed and when indolent disease occurs. It is hoped that clinicians treating patients with mHSPC in daily practice will find this expert opinion of value.

Convergence study and regularizing property of a modified Robin–Robin method for the Cauchy problem in linear elasticity

In this paper, we are interested in solving a Cauchy inverse problem in linear elasticity. For this, we propose a new method based on Robin conditions on the inaccessible boundary, then we study the convergence and regularizing property of the proposed algorithm. We use the finite element method for the discretization of our problem. Further, we treat the spectrum analysis of the discrete problem in order to study the convergence behavior of the proposed method in the discrete case. Finally, we present numerical results which show the efficiency and stability of the proposed approach in the presence of perturbed data. The robustness of the proposed algorithm is also performed for the anisotropic and heterogeneous cases.

Convergence Analysis of the Nonoverlapping Robin--Robin Method for Nonlinear Elliptic Equations

We prove convergence for the nonoverlapping Robin--Robin method applied to nonlinear elliptic equations with a $p$-structure, including degenerate diffusion equations governed by the $p$-Laplacian. This nonoverlapping domain decomposition is commonly encountered when discretizing elliptic equations, as it enables the usage of parallel and distributed hardware. Convergence has been derived in various linear contexts, but little has been proven for nonlinear equations. Hence, we develop a new theory for nonlinear Steklov--Poincaré operators based on the $p$-structure and the $L^p$-generalization of the Lions--Magenes spaces. This framework allows the reformulation of the Robin--Robin method into a Peaceman--Rachford splitting on the interfaces of the subdomains, and the convergence analysis then follows by employing elements of the abstract theory for monotone operators. The analysis is performed on Lipschitz domains and without restrictive regularity assumptions on the solutions.

Dynamic Task Scheduling based on Burst Time Requirement for Cloud Environment

Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.

Scheduling Algorithms for CPU

The process scheduling, is one of the most important tasks of the operating system. We present in this paper some types of scheduling algorithms of CPU. One of the most common scheduling algorithms used by the most operating systems is the Round Robin method in which, the ready processes waiting in ready queue, seize the processor for a short period of time known as the quantum (or time slice) circularly. But the most important issue in RR algorithm, which highly affects its efficiency. It determines the amount of the time quantum. Assigning very small and very large values for this parameter, will lead to performance decrease due to increasing context switching overhead, and degradation of the RR method to FCFS algorithm consequently. We will suggest a solution of allocated time quantum.

Analysis Performance Of Conventional Algorithm And HMS Algorithm For Four-Way Intersection With Modified Round Robin

Traffic jam is currently one of the main problems for densely populated cities like Jakarta, Indonesia. One problem that causes traffic jams in Jakarta is that the traffic lights are too fast, which causes many cars to not be able to pass the traffic lights. There are already many algorithms to overcome this problem and get the right time for traffic lights based on how many vehicles are waiting in line, such as the HMS Algorithm and Conventional Algorithm. This research objective is to compare which algorithm has better performance to find the right amount of time for traffic lights to reduce traffic jams at four-way intersections with modified Round Robin method. And the result shown that the HMS algorithm is very suitable to be used in any condition for large or little vehicles, while conventional algorithms are only suitable to use for vehicles in the one little lane or the vehicles in one lane with other lane direction in the same place of lane

Pengaruh Metode Round Robin terhadap Hasil Belajar IPS Siswa Kelas VII

This study aims to determine the effect of Round Robin on student learning outcomes in social studies subject matter VII Class SMP Negeri 2 Situjoah District Limo Nagari. The quantitative method used in this study is an experimental approach, in which the research design is to use a control class as a comparison of the research class. Based on the research results from the analysis it was concluded that the cooperative learning technique of Round Robin d can improve students' social learning outcomes well. Class VII student learning outcomes in SMP N 02 Kec. Situjuah Limo Nagari was divided into two groups: the first was the experimental class where the mean score was 72.9 and the second was the control class where the average value was 60.3. Means the value of the experimental class is higher than the control value because the experimental class uses the Round Robin s method while the control class uses conventional. Conclusions, that by using the Round Robin method in social studies subjects can be said to have a significant effect on learning outcomes.
 Keywords: Round Robin Method, Learning Outcomes, Social Studies

Illustration of different modalities of Role-Play for Medical Communication Skills at Undergraduate Level

Role-play is commonly used as a learning method for teaching communication in medical institutions and there two types of role-play i.e. Round Robin and Relay`s methods. This study among our students and trainers to identify which role-play has better effect on students learning at college of Medicine, King Faisal University, Al Ahsa. All the first year students and trainers were included in the study. Students are divided into different groups and each group contains 9 – 11 students. Different scenarios are provided to the students with each physician and patient role. A pre-structured questionnaire was distributed among students and trainers to compare between the Role-play methods. The questionnaire included 15 statements related to the role-play methods based on Likert scale. Wilcoxon signed-rank test was applied to compare different items for both methods and to obtain p-value. The results showed that 221 students and 25 trainers filled the questionnaire. The Round Robin was found to have more influence on students` perception as compared to that for Relay`s except for item 4 i.e. role-play builds a team work where majority of participants agreed for Relay`s method. Similar results were found while checking perception of trainers. The results of statistical test for comparing both methods suggest that there is a significant difference in Round Robin and Relay`s method for most of the questions P- value < 0.05. We found that both methods of role-play used in communication skills sessions are helpful however, Round robin method has better outcome on learning as compared to Relay`s method

Aneffective cloud parcelling in a load balancing model

Load adjusting may be a standout amongst the vital issues for cloud registering. Since a large number for clients are gaining entrance to the cloud each moment, the idea of load adjusting need a critical sway on the execution about cloud registering. When nature will be thick, as substantial Furthermore complex, the divisions simplifies those load in the cloud. This paper executes two effective calculations for performing an exceptional load equalization model to the cloud surroundings in light of those cloud parceling particular idea for a switch component on decide diverse methodologies to diverse particular circumstances. Previously, load adjusting strategy, enhanced round robin method also diversion hypothesis strategy need aid connected with move forward those effectiveness done cloud.

Scheduling Optimization For Extract, Transform, Load (ETL) Process On Data Warehouse Using Round Robin Method (Case Study: University Of XYZ)

ETL scheduling is a challenging and exciting issue to solve. The ETL scheduling problem has many facets, one of which is the cost of time. If it is not handled correctly, it may take a very long time to execute and inconsistent data in very large data. In this study using Round-robin algorithm method that proved able to produce efficient results and in accordance with conventional methods. After doing the research, the difference between these two methods is about execution time. Through this experiment, the Round-robin scheduling method gives a more efficient execution time of up to 61% depending on the amount of data and the number of partitions used.

Rancang Bangun Mekanisme Load Sharing Pada Link Aggregation Menggunakan Software Defined Networking

Given the level of activity of Internet users is high on lately. Impact on the growing needs for server throughput can be treated with load sharing on link aggregation. However, it possess a problem for UDP protocol data packets which will experience jitter and packet received out of order high. Therefore, the author tries to create an algorithm to share the package which will be sent to the server with weighted round robin method that focuses UDP Protocol data packets. The author uses the Software Defined Networking (SDN) and OpenFlow protocol that is capable of directly reprogrammed network devices. Host connect by sending packets Internet Control Message Protocol (ICMP), Transport Control Protocol (TCP) and User Datagram Protocol (UDP) to the server, then do an analysis of the bandwidth, jitter, datagrams, and retry. The author has successfully implemented with the emulator Mininet and testing. The results indicate that the average jitter is able to be reduced to 50% and packets received out of order is reduced to 0 compared to standard link aggregation with weighted round robin load sharing method.
 Keywords— Software Defined Netwoking, Link Aggregation, Weighted Round Robin, UDP

AN IMPROVED LOAD SHEDDING SCHEDULING STRATEGY FOR SOLVING POWER SUPPLY DEFISIT

When high electricity demand growth not matched by the growth in generating capacity, energy deficit problem cannot be avoided. Power outages of up to 6 hours per day are part of the power crisis experienced by electricity consumers in Sumatra. The utility has applied load shedding approach to tackle the problem, however, there are weaknesses on the current load shedding program. It is discovered that most of the power outage occurs randomly without any prior notice and sometime lasted for many hours. Load shedding program is not properly scheduled and not fairly distributed among all consumers. A proper scheduling program must have a clear periodic schedule, fixed outage hours, fairly distributed and alternated among consumers and most importantly solve energy deficit problem. This paper presented an improved load shedding scheduling strategy based on Round Robin method. The method is then illustrated and applied on actual daily load profile of Sumatra electrical system.

A fair energy resource allocation strategy for micro grid

The design of smart grid systems have been proposed in several literature. However, the actual commercial feasibility of smart grids or micro grids still faces several problems including technical infrastructure related issues and market economy issues. One critical issue in the design of commercially feasible smart grids is how the electricity trading can be performed fairly among micro grids. In existing works, this issue has been mainly addressed by using some sort of priority scheme among buyers and sellers in electricity trading, which obviously does not guarantee a fair trading scheme. As a result, the commercial feasibility of existing works is at stake and will not work as proposed. This work tries to address this issue by proposing a Fair Energy Resource Allocation (FERA) method for smart grids. The proposed method has been implemented in a FIPA-compliant Multi-Agent System (MAS) based smart grid control system and evaluated against state-of-the-art round robin and priority based allocation methods. For trading among 30 micro grids, it is demonstrated that the proposed method results in a high fairness index of 96.22% even in the worst case, while the round robin scheme and the priority scheme result in a worst-case fairness index of only 57.8% and 11.29%, respectively. Thus, in the long term under different ratios of buyers and sellers, the proposed method is the only method that can achieve a very high fairness index in the worst case. Averaging over different ratios of buyers and sellers, the proposed method results in a fairness index of 99.57%, which is much higher that achieved by the round robin method (84.04%) and the priority scheme (63.56%). As far as cost saving is concerned, based on the cost saving opportunity (CSO) metric, in the long term (10,000 rounds of trading), the proposed method results in a CSO of 51.48%, which is much higher than that by the other two methods; round robin method results in 14.07% and priority-based method results in 34.44%.

Lifter assignment problem for inter-line transfers in semiconductor manufacturing facilities

As more advanced and diverse semiconductor products are demanded, each product requires more processing steps, and the product mix changes frequently. The production volume may exceed the capacity of one line at a semiconductor fabrication plant, and the equipment utilization becomes unbalanced. This situation leads to a combination of multiple lines, which requires the transfer of wafer lots from one line to another. Lifters are machines for inter-line transfers, and they can quickly become a critical bottleneck of semiconductor manufacturing. We introduce an online assignment problem between lifters and inter-line transfers, which is motivated in unified automated material handling systems. We propose several solution methods to improve assignment efficiency and resolve inter-line transfer delays in material handling systems. When compared to the round robin method used currently, the shortest expected arrival time (SEAT) rule decreases delivery time by 8.9 %.

Modification of Round Robin and Best CQI Scheduling Method for 3GPP LTE Downlink

In the downlink LTE, the scheduler is an important element that assigns resource block (RB) allocation for different users in a cell. RB is the smallest element that can be assigned by the scheduler. This paper proposed a new scheduler algorithm by considering the tradeoff balance between throughput and fairness among users. The benefits of both Best CQI and Round Robin schedulers have been combined in this proposed scheduler. The proposed scheduler has two main time slots that apply the combined algorithms. The primary time slot applies a Round Robin algorithm that has a continuous user sequence in the entire sub frame, and the second time slot then applies the Best CQI algorithm with a fairness enhancement. For 15dB SNR, the system has various throughput values in each scheduler, which is 61.2Mbps for the Best CQI scheduler, 32.3Mbps for the Round Robin scheduler, and 48Mbps for the proposed scheduler. For the results, in reference to Jain's fairness index, the proposed scheduler gains a fairness index of 0.97. Furthermore, for 20 users at 5MHz bandwidth, it is found that the average queuing delay is 5ms for the Round Robin scheduler, 29.38ms for the Best CQI scheduler, and 0.94ms for the proposed scheduler.

Dynamic Replication Algorithm for Data Replication to Improve System Availability: A Performance Engineering Approach

ABSTRACTInformation technology systems deployed by enterprises should not only fulfil their business functionalities but also cater to Quality of Service concerns such as Availability, Scalability, and Performance. To enhance the system performance, the system availability is an important factor and to improve the system availability, one of the strategies is replicating the frequently accessed data to multiple suitable locations which is a practical choice as the users can access the data from a nearby site. This is, however, not the case for replicas which must have a preset number of copies on several locations. How to decide a sensible number and right location for replicas have become an important issue in cloud computing. In this paper, we show a dynamic data replication strategy to enhance the performance of software system. To identify the suitable file to replicate and to decide respective number of replicas, we calculate popularity degree and replica factor. We use the fuzzy logic system to identify the system to place the replicas and we use the round robin method to place the replicas in the identified systems. We compare the performance of our technique with the existing technique.