First-come-first-served Research Articles

Fuzzy Reinforcement Learning for energy efficient task offloading in Vehicular Fog Computing

Vehicular Fog Computing (VFC) has been envisioned as a potential fog computing paradigm which aims to offload delay sensitive tasks to mobile fog vehicles instead of remote cloud in order to facilitate computational demands of smart villages close to rural highways. There exists challenges related to task offloading in VFC that need to be addressed. Most often, Road Side Units (RSUs) deployed along rural highways are energy constrained and they need to provide energy efficient scheduling services for the allocation of tasks to fog vehicles. On the other hand, energy consumption optimization is challenging, since scheduling decision of local processing of tasks incur computation cost while the allocation of tasks to fog vehicles incurs communication cost. Although the task offloading to VFC reduces response latency, it leads to higher RSU energy consumption contributed by the communication of task data to fog vehicles. Therefore, this paper presents an energy efficient vehicle scheduling problem for offloading of tasks to mobile fog nodes subject to satisfy constraints of task deadline and resource availability. To resolve high dimensionality issue caused by increased number of vehicles in RSU coverage, we propose an on-policy reinforcement leaning based scheduling algorithm combined with fuzzy logic based greedy heuristic, named as Fuzzy Reinforcement Learning (FRL). This greedy heuristic not only accelerates learning process, but also improves long term reward when compared to Q-learning algorithm. Extensive experiments have been performed to evaluate the proposed algorithm and the simulation results show that the proposed FRL algorithm outperforms other scheduling algorithms such as First Come First Serve (FCFS), Rate Monotonic Scheduling (RMS), Fuzzy and Distributed Task Allocation with Distributed Process (DTA_DP).

ANALISIS DAN PERANCANGAN SISTEM INFORMASI PADA BRASTAGI SUPERMARKET RANTAUPRAPAT DENGAN MENERAPKAN VIEWPOINT ORIENTED REQUIREMENT DEFINITION (VORD) BERBASIS WEB

Technological progress in the Millennial Era is very fast, especially in the business world, it has a very large effect. Information technology is currently growing in line with the needs of millennial children who want convenience. So every college wants to achieve a goal. So to achieve this goal, higher education institutions encourage to establish a Business Unit of the Faculty of Computer Science, Indonesian Methodist University (FIKOM UMI). Therefore we need a system that aims to improve the development of an entrepreneurial culture and improve the academic community. By overcoming these problems, a web-based millennial child accessories sales application was designed by applying the FCFS (First Come First Served) method. The millennial generation is currently a major player in the Indonesian economy. So in the business context, it is very important to understand the millennial character so that they can read product trends that are currently popular. One of the products that can show a person's character is accessories. The results obtained are intended to make it easier for customers to order and purchase a variety of accessories products and prioritize customers who are required to pay then the goods are sent and processed first. The system is built using the HTML and PHP programming languages, and the server uses Xampp and the database uses MySql.

PERANCANGAN APLIKASI PENJUALAN AKSESORIS ANAK MILENIAL BERBASIS WEB STUDI KASUS : UNIT BISNIS FIKOM UMI

Technological progress in the Millennial Era is very fast, especially in the business world, it has a very large effect. Information technology is currently growing in line with the needs of millennial children who want convenience. So every college wants to achieve a goal. So to achieve this goal, higher education institutions encourage to establish a Business Unit of the Faculty of Computer Science, Indonesian Methodist University (FIKOM UMI). Therefore we need a system that aims to improve the development of an entrepreneurial culture and improve the academic community. By overcoming these problems, a web-based millennial child accessories sales application was designed by applying the FCFS (First Come First Served) method. The millennial generation is currently a major player in the Indonesian economy. So in the business context, it is very important to understand the millennial character so that they can read product trends that are currently popular. One of the products that can show a person's character is accessories. The results obtained are intended to make it easier for customers to order and purchase a variety of accessories products and prioritize customers who are required to pay then the goods are sent and processed first. The system is built using the HTML and PHP programming languages, the server uses Xampp and the database uses MySQL.

PENERAPAN MODEL ANTREAN MULTI CHANNEL SINGLE PHASE PADA SISTEM PELAYANAN RESTORAN CEPAT SAJI

A queue will occur if the average number of arrivals exceeds the capacity of service facilities. Fast food restaurants are one of the places that usually have long queues at lunchtime and dinner time. KFC in Bali, located in the village of Sanur, is a fast food restaurant that is experiencing long queues. This is because this restaurant is located in a tourism area and the only KFC outlet on the Ngurah Rai Sanur bypass line and does not yet have a drive-thru service. The current condition at KFC Sanur is that there is more than one service facility, disciplined first come first service (FCFS) queues according to the multi channel single phase queuing model. After being analyzed with data taken before the pandemic period on November 18, 2019 to December 1, 2019 for 14 days during weekdays and weekends, it was found that the performance of the KFC Sanur queue system would have a smaller utility level if there were 3 active server. The total cost per customer if there are 2 active server is IDR 78,692.38 and if there are 3 server is IDR 75,788.45. Based on the results of this analysis, it can be concluded that it will be more optimal if there are 3 active server.

Fluid Models of Parallel Service Systems Under FCFS

In parallel service systems, customers of various types are served simultaneously by several servers that have some dierent and some overlapping skills or capacities. Examples include customer routing in call centers, scheduling of hospital operating rooms, and driver assignment in ride-hailing services. First come first served (FCFS) is a natural and widespread resource allocation policy, yet its performance both during the transient stage and in the long run is often difficult to analyze. In particular, matching rates, which indicate what fraction from all services are of a specific server customer type, are difficult to evaluate under FCFS. In Fluid Models of Parallel Service Systems under FCFS, Yuval Nov, Gideon Weiss, and Hanqin Zhang formulate a stochastic queueing model for such systems and study its fluid approximation. The paper demonstrates the usefulness and the limitations of exploring fluid performance in evaluating system behavior in terms of stability, responsiveness, and utilization.

An Evaluation of First-Come, First-Served Scheduling in a Geometrically-Constrained Wet Bulk Terminal

In 2022, a new sea lock at IJmuiden is expected to open, permitting an increase in marine traffic of larger ships from the sea to the port. In the interest of facilitating operations, we evaluate the impact of the current first-come, first-served (FCFS) admittance policy in the context of berth allocation for a wet bulk terminal in the port. Four model types are constructed: optimal FCFS; no FCFS with fixed arrival times; 48-h arrival time relaxation; and complete arrival time relaxation. Comparison of the model types is done by means of a rolling time window: of each day within the time frame, a schedule was created for the following 2 weeks, after which the objective value was calculated. When comparing the average of all objective values, it was found that the optimal FCFS model already shows an improvement compared to the historical situation. Between the FCFS and the no FCFS model, there are no considerable differences, because the vessels are constrained to be scheduled on/after their arrival time at the port. When relaxation is allowed, a considerable efficiency gain is possible, especially if larger ships arrive at the port.

Applying crisis standards of care to critically ill patients during the COVID-19 pandemic: Does race/ethnicity affect triage scoring?

ObjectiveGiven the variability in crisis standards of care (CSC) guidelines during the COVID‐19 pandemic, we investigated the racial and ethnic differences in prioritization between 3 different CSC triage policies (New York, Massachusetts, USA), as well as a first come, first served (FCFS) approach, using a single patient population.MethodsWe performed a retrospective cohort study of patients with intensive care unit (ICU) needs at a tertiary hospital on its peak COVID‐19 ICU census day. We used medical record data to calculate a CSC score under 3 criteria: New York, Massachusetts with full comorbidity list (Massachusetts1), and MA with a modified comorbidity list (Massachusetts2). The CSC scores, as well as FCFS, determined which patients were eligible to receive critical care under 2 scarcity scenarios: 50 versus 100 ICU bed capacity. We assessed the association between race/ethnicity and eligibility for critical care with logistic regression.ResultsOf 211 patients, 139 (66%) were male, 95 (45%) were Hispanic, 23 (11%) were non‐Hispanic Black, and 69 (33%) were non‐Hispanic White. Hispanic patients had the fewest comorbidities. Assuming a 50 ICU bed capacity, Hispanic patients had significantly higher odds of receiving critical care services across all CSC guidelines, except FCFS. However, assuming a 100 ICU bed capacity, Hispanic patients had greater odds of receiving critical care services under only the Massachusetts2 guidelines (odds ratio, 2.05; 95% CI, 1.09 to 3.85).ConclusionVarying CSC guidelines differentially affect racial and ethnic minority groups with regard to risk stratification. The equity implications of CSC guidelines require thorough investigation before CSC guidelines are implemented.

Nudge: Stochastically Improving upon FCFS

The First-Come First-Served (FCFS) scheduling policy is the most popular scheduling algorithm used in practice. Furthermore, its usage is theoretically validated: for light-tailed job size distributions, FCFS has weakly optimal asymptotic tail of response time. But what if we don't just care about the asymptotic tail? What if we also care about the 99th percentile of response time, or the fraction of jobs that complete in under one second? Is FCFS still best? Outside of the asymptotic regime, only loose bounds on the tail of FCFS are known, and optimality is completely open. In this paper, we introduce a new policy, Nudge, which is the first policy to provably stochastically improve upon FCFS. We prove that Nudge simultaneously improves upon FCFS at every point along the tail, for light-tailed job size distributions. As a result, Nudge outperforms FCFS for every moment and every percentile of response time. Moreover, Nudge provides a multiplicative improvement over FCFS in the asymptotic tail. This resolves a long-standing open problem by showing that, counter to previous conjecture, FCFS is not strongly asymptotically optimal. This paper represents an abridged version of [2].

A SURVEY OF VARIANTS OF ROUND ROBIN CPU SCHEDULING ALGORITHMS

Quite a number of scheduling algorithms have been implemented in the past, including First Come First Served (FCFS), Shortest Job First (SJF), Priority and Round Robin (RR). However, RR seems better than others because of its impartiality during the usage of its quantum time. Despite this, there is a big challenge with respect to the quantum time to use. This is because when the quantum time is too large, it leads to FCFS, and if the quantum time is too short, it increases the number of switches from the processes. As a result of this, this paper provides a descriptive review of various algorithms that have been implemented in the past 10 years, for various quantum time in order to optimize the performance of CPU utilization. This attempt will open more research areas for researchers, serve as a reference source and articulate various algorithms that have been used in the previous years – and as such, the paper will serve as a guide for future work. This research work further suggests novel hybridization and ensemble of two or more techniques so as to improve CPU performance by decreasing the number of context switch, turnaround time, waiting time and response time and in overall increasing the throughput and CPU utilization.

Nudge: Stochastically Improving upon FCFS

The First-Come First-Served (FCFS) scheduling policy is the most popular scheduling algorithm used in practice. Furthermore, its usage is theoretically validated: for light-tailed job size distributions, FCFS has weakly optimal asymptotic tail of response time. But what if we don't just care about the asymptotic tail? What if we also care about the 99th percentile of response time, or the fraction of jobs that complete in under one second? Is FCFS still best? Outside of the asymptotic regime, only loose bounds on the tail of FCFS are known, and optimality is completely open. In this paper, we introduce a new policy, Nudge, which is the first policy to provably stochastically improve upon FCFS. We prove that Nudge simultaneously improves upon FCFS at every point along the tail, for light-tailed job size distributions. As a result, Nudge outperforms FCFS for every moment and every percentile of response time. Moreover, Nudge provides a multiplicative improvement over FCFS in the asymptotic tail. This resolves a long-standing open problem by showing that, counter to previous conjecture, FCFS is not strongly asymptotically optimal.

Multi-Dependency and Time Based Resource Scheduling Algorithm for Scientific Applications in Cloud Computing

Workflow scheduling is one of the significant issues for scientific applications among virtual machine migration, database management, security, performance, fault tolerance, server consolidation, etc. In this paper, existing time-based scheduling algorithms, such as first come first serve (FCFS), min–min, max–min, and minimum completion time (MCT), along with dependency-based scheduling algorithm MaxChild have been considered. These time-based scheduling algorithms only compare the burst time of tasks. Based on the burst time, these schedulers, schedule the sub-tasks of the application on suitable virtual machines according to the scheduling criteria. During this process, not much attention was given to the proper utilization of the resources. A novel dependency and time-based scheduling algorithm is proposed that considers the parent to child (P2C) node dependencies, child to parent node dependencies, and the time of different tasks in the workflows. The proposed P2C algorithm emphasizes proper utilization of the resources and overcomes the limitations of these time-based schedulers. The scientific applications, such as CyberShake, Montage, Epigenomics, Inspiral, and SIPHT, are represented in terms of the workflow. The tasks can be represented as the nodes, and relationships between the tasks can be represented as the dependencies in the workflows. All the results have been validated by using the simulation-based environment created with the help of the WorkflowSim simulator for the cloud environment. It has been observed that the proposed approach outperforms the mentioned time and dependency-based scheduling algorithms in terms of the total execution time by efficiently utilizing the resources.

Stochastic Model on Three-Similar Units Three Phased Mission System with FCFS Repairs Pattern

The paper allocates a stochastic model on threesimilar units three-phased mission system. The developed system consists of units working in parallel, series and parallel configurations respectively. Initially, the three similar units are operational. Each component has only three states: good, degraded and failed. In this case, the single repair facility that repairs the units in first come first serve (FCFS)pattern has been thought of. Using Semi-Markov Process and regenerative point techniques, various measures of the system performance at each phase are obtained. The system has been analyzed graphically taking a particular case. Various conclusions are made regarding the reliability and cost consideration of the system at each phase as well as for the whole system(as combined Phase I, Phase II, Phase III).

Assigning Priorities (or Not) in Service Systems with Nonlinear Waiting Costs

For a queueing system with multiple customer types differing in service-time distributions and waiting costs, it is well known that the cµ-rule is optimal if costs for waiting are incurred linearly with time. In this paper, we seek to identify policies that minimize the long-run average cost under nonlinear waiting cost functions within the set of fixed priority policies that only use the type identities of customers independently of the system state. For a single-server queueing system with Poisson arrivals and two or more customer types, we first show that some form of the cµ-rule holds with the caveat that the indices are complex, depending on the arrival rate, higher moments of service time, and proportions of customer types. Under quadratic cost functions, we provide a set of conditions that determine whether to give priority to one type over the other or not to give priority but serve them according to first-come, first-served (FCFS). These conditions lead to useful insights into when strict (and fixed) priority policies should be preferred over FCFS and when they should be avoided. For example, we find that, when traffic is heavy, service times are highly variable, and the customer types are not heterogenous, so then prioritizing one type over the other (especially a proportionally dominant type) would be worse than not assigning any priority. By means of a numerical study, we generate further insights into more specific conditions under which fixed priority policies can be considered as an alternative to FCFS. This paper was accepted by Baris Ata, stochastic models and simulation.

Developing a detection model for a COVID-19 infected person based on a probabilistic dynamical system.

This paper presents a novel model to detect the COVID‐19 infected person from a Markovian feedback persons in a limited department capacity. The persons arrive one by one to the department and the balking and the retention of reneged person approaches are considered. There exists one server presents the service to these persons according to first‐come, first‐served (FCFS) discipline. An efficient and novel algorithm is presented to get the exact value of the probability of n persons in the department at any time interval. This algorithm depends on the Laplace transform to solve a probabilistic dynamical system of differential equations. By considering the exponential detection function and if the probability of the infected person in the department is equal to the probability of each one, then this algorithm is useful to obtain the detection probability of the infected one. Under steady state, the detection probability of the infected person is described. The usefulness of this model is illustrated for different capacities by using a numerical example to describe the behavior of probabilities of the persons in the department, the detection probabilities of the infected person as functions in time, and the mean time to detection.

A Comparative Analysis of Disk Scheduling Algorithms

In an operating system, disk scheduling is the process of managing the I/O request to the secondary storage devices such as hard disk. The speed of the processor and primary memory has increased in a rapid way than the secondary storage. Seek time is the important factor in an operating system to get the best access time. For the better performance, speedy servicing of I/O request for secondary memory is very important. The goal of the disk-scheduling algorithm is to minimize the response time and maximize throughput of the system.
 This work analyzed and compared various basic disk scheduling techniques like First Come First Serve (FCFS), Shortest Seek Time First (SSTF), SCAN, LOOK, Circular SCAN (C-SCAN) and Circular LOOK (C-LOOK) along with the corresponding seek time. From the comparative analysis, the result show that C-LOOK algorithm give the least head movement and seek time in different cases as compared to other algorithm. Therefore, it maximizes the throughput for the storage devices.

Analysis of Production Scheduling In “Abadi” Malang Rackets And Sport Equipment Company

Racket and Sports Equipment Company "Abadi" Malang is engaged in manufacturing. As a result of the covid-19, the company only produces midangan. The purpose of this research is to find out and find the optimal scheduling method so that it can overcome the problem of delays in order completion. The method used is the priority rule consisting of first come first serve (FCFS), shortest processing time (SPT), longest processing time (LPT), and earliest due date (EDD). The results of the study indicate that the SPT method is a method that has the most optimal measure of effectiveness compared to the FCFS, LPT, and EDD methods. The SPT method produces an average value of 21 days of completion, 31.74% utility, an average number of jobs in the system 3.15 jobs, and a delay of 12.5 days.

MANUFACTURING INDUSTRY JOB SHOP FLOOR DECISIONS THROUGH HYBRID GENETIC ALGORITHM

This article addresses flexible manufacturing system (FMS) Performance is likely to improve with employment of various resources efficiently. Initially simultaneous scheduling problems are solved by means of priority rules like first come first serve (FCFS), shortest processing time (SPT) and longest processing time (LPT) to find out the operational completion time for 120 problems. Later gene rearrangement genetic algorithm (HGA) is implemented for same set of problems with makespan as objective and the results are compared with the results of priority rules. The results are performed well by using HGA. The same HGA is used to find the finest optimal sequence that minimize the operational completion time.

Vessel scheduling with pilotage and tugging considerations

This paper considers vessel scheduling with pilotage and tugging constraints in berthing operations with channel restrictions at seaports. To our knowledge, pilotage and tugging requirements have not been simultaneously considered in the literature. This work proposes a mixed integer programming (MIP) formulation and an exact solution approach, based on constraint separation techniques, to solve the problem. The solution approach is initiated with a heuristic that runs in polynomial time. The approach then adds separation cuts to a relaxed version of the MIP formulation and updates the bounds until an optimal solution has been found. A real case and simulated realistic cases are used to compare the proposed model against the first-come first-serve (FCFS) policy that is traditionally used in vessel scheduling. The results show that significant improvements can be obtained, especially during congestion periods. Finally, a computational study demonstrates that the proposed solution approach is capable of solving real-size cases in a reasonable time.

Design of Visualization System for Horizontal Transportation Operation of Container Terminal

Aiming at the problem of resource allocation and planning of container trucks in container terminals, the visualization system for horizontal transportation operation of container terminals is designed based on virtual reality technology. The system mainly includes task allocation module, statistical analysis module and visualization module. Based on the real-time communication interface, the synchronous operation of physical scene and virtual scene is realized, which is convenient for remote and real-time control of field operation; based on the principle of the shortest total operation time, the vehicle transfer task is allocated to maximize the resource utilization; with the FCFS (first come first service), priority level and other scheduling strategies, the vehicle path planning is realized to avoid accidents such as collision; through statistics and analysis of data, workers can get real-time information such as vehicle status and total working hours. The scale-down experiment is designed to simulate the container transfer operation of the terminal, which verifies the function of the system. The overall solution of horizontal transportation operation for the container terminal is provided, which can promote the intelligent construction of the terminal.

Optimization of Pipe Production Scheduling in Line 18 Using First Come First Serve (Fcfs), Earlier Due Date (Edd), Short Process Time (Spt) Methods (Case Study: Pt Wtur)

For machine line 18, is intended to produce PVC pipe with a 5 ", 6" and 8 "with each contained item type AW and type D with a turn of the cycle a certain schedule. From the turn of this cycle, there are a couple of the impact is too long good finish duration of vacant stock in the Warehouse Production (GHP) pipe. The impact of the long duration of the good stock of empty finish unachieved impact on consumer demand (in this case the agent). By not reaching the consumer demand impact on service level SCM & Delivery. The purpose of this study to determine the optimal level of machine line 18 so that the products PVC size 5 ", 6" and 8 "are produced to meet the buffer stock storage. Thus, this research is expected to make a production schedule to meet the stock warehouse to the fullest, can meet the needs of consumers (agent) to the maximum but not over. From the data and data analysis using the First Come First Serve (FCFS), Earlier Due Date (EDD), Short Process Time (SPT), the SPT method is the most optimal method by having an average completion time of 4,10 days with 36,75% utility, then the average number of jobs 2,77 work, and delays the average occupation is 0,42 days.