First Come First Serve Algorithm Research Articles

The Role of Fog Device Density in IoT-Fog-Cloud Systems

Fog computing has emerged as an essential technology for enabling real-time, low-latency responses in cloud-based applications within Internet of Things (IoT) systems. This study explored the impact of the number of fog devices (NFDs) on the performance of IoT-fog-cloud systems. Through comparative analysis, two scheduling algorithms—First Come First Serve (FCFS) and Priority—were evaluated across different scales of system deployment. The results indicated that the FCFS algorithm was optimal for systems with fewer NFDs, whereas the Priority algorithm proved advantageous in larger settings. These findings not only establish guidelines for selecting appropriate scheduling strategies based on the scale of fog device deployment but also provide strategic insights for businesses on the optimal distribution of computational resources. This research aids companies in deciding whether to centralize resources in fewer branches with more employees or to decentralize into more branches with fewer employees, thereby optimizing operational efficiency and responsiveness.

Optimal CPU Jobs Scheduling Method Based on Simulated Annealing Algorithm

Task scheduling in an important element in a distributed system. It is vital how the jobs are correctly assigned for each computer’s processor to improve performance. The presented approaches attempt to reduce the expense of optimizing the use of the CPU. These techniques mostly lack planning and in need to be comprehensive. To address this fault, a hybrid optimization scheduling technique is proposed for the hybridization of both First-Come First-Served (FCFS), and Shortest Job First (SJF). In addition, we propose to apply Simulated Annealing (SA) algorithm as an optimization technique to find optimal job’s execution sequence considering both job’s entrance time and job’s execution time to balance them to reduce the job’s waiting time to be executed. As a result, this research proves that the proposed technique achieves an optimization efficiency with a percentage average 45.5 % according to the FCFS algorithm and 54.5% according to SJF method.

Practical Splitting Algorithm for Multi-Channel Slotted Random Access Systems

For slotted random access systems with a single channel, the slotted ALOHA (S-ALOHA) protocol shows 0.368 (packets/slot) as the maximum throughput, whereas some splitting (or tree) algorithms exhibit 0.487 (packets/slot). The S-ALOHA protocol has been widely adopted even for multi-channel systems such as Long-Term Evolution (LTE), as it is more practically implementable. However, the throughput of each channel in multi-channel S-ALOHA is limited to 0.368. In order to overcome this limit and some implementational drawbacks of the existing splitting algorithms, this paper proposes a novel splitting algorithm for multi-channel slotted systems which can also adapt to dynamic system situations through estimating the number of users who have packet to transmit. We analyze the throughput of our proposed algorithm and show that the proposed algorithm is more practical than the first-come first-serve (FCFS) algorithm and shows smaller access delay than the FCFS algorithm even for a single channel system. For M-channel systems, the proposed algorithm yields the maximum throughput of 0.487M. Extensive simulations validate our analytical results.

Untethering the Queue based on Multi Channel Access (MCA) Technology at Hospital Radiology Section

Background: Information technology is developing rapidly over time, but there are many companies do not make use of it to support their operational activities. One example is the queue system in the Radiology Section of Sanglah Hospital, which operates the conventional queue system.Objective: The problem occurs in this queue system is inefficient waiting time because the patients must come early and wait in line in the hospital waiting rooms. Many patients thereafter decide going home first or doing other activities. Another problem is it triggers double costs of transportation. The purpose of this study is to improve patients comfort while waiting in queue by applying untethering the queue. Untethering the queue is a service that allows people to be in a queue even though they are not in the waiting room.Methods: The system applies the FCFS (First Come First Serve) algorithm to manage patients’ queue and integrates this queue system with Telegram and SMS gateway. It makes patients easier to take queue numbers and receive notification of health service time from the Radiology Section of Sanglah Hospital.Result: As a result of this study is an untethering the queue application which is web-based queue system integrated to Telegram and SMS gateway. The daily queue services in the Radiology Section of Hospital can be improved through this application.Conclusion: Patients can only come to the hospital when the queue numbers obtained nearly the health service time so that it leads to time efficient and comfort while waiting in queue.Keywords:First Come First Serve, Multi Channel Access, SMS, Telegram, Untethering the Queue

Research on the Problem of Sorting Parallel Runway Aircraft in Terminal Area Based on Genetic Algorithm

Serious air traffic congestion often occurs in busy airports and terminal areas, which seriously interferes with the normal operation of flights, resulting in a large number of flight delays, causing huge economic losses to airlines, and also the affecting the safe operation of flights in the terminal area. This study takes the two-runway airport as the research object, establishes the parallel runway arrival flight sequencing model and designs the double-encoded genetic algorithm, uses a pair of chromosomes to determine the runway allocation and landing sequence number of the arriving flight, and arranges the flight landing sequence and the runway. The simulation experiments were carried out on 10 flights that were about to land at a certain time in the airport, the experimental results show that the algorithm achieves flight sorting and runway allocation optimization, compared with the current FCFS (First Come First Served) algorithm, it can effectively reduce flight delay time and improve the utilization efficiency of the airport terminal area.

Static Load Balancing Technique for Geographically Partitioned Public Cloud

Large number of users are shifting to the cloud system for their different kind of needs. Hence the number of applications on public cloud are increasing day by day. Handling public cloud is becoming unmanageable in comparison to other counterparts. Though fog technology has reduced the load on centralized cloud resources to a remarkable extent, still load handled at cloud end is significantly high. Geographic partitioning of public cloud can resolve these issues by adding manageability and efficiency in this situation. Dividing public cloud in smaller partitions opens ways to manage resources and requests in a better way. But, partitioned clouds introduce different ends for submission and operations of tasks and virtual machines. We have tried to handle all these complexities in this paper. Proposed work is focused upon load balancing in the partitioned public cloud by combining centralized and decentralized approaches, assuming the presence of fog layer. A load balancer entity is used for decentralized load balancing at partitions and a controller entity is used for centralized level to balance the overall load at various partitions. In the proposed approach, it is assumed that jobs are segregated first. All the jobs which can be handled locally by fog resources are not forwarded to the cloud layer directly. Those are processed locally by decentralized fog resources. Selection of an appropriate Virtual Machine (VM) for filtered set of job, which are forwarded to cloud environment, is done in three steps. Initially, selecting the partition with a maximum available capacity of resources. Then finding the appropriate node with maximum available resources, within a selected partition. And finally, the VM with minimum execution time for a task is chosen. Results are compared with the results produced in this work with First Come First Serve (FCFS) and Shortest Job First (SJF) algorithms, implemented in same setup i.e. partitioned cloud. This paper compares the Waiting Time, Finish Time and Actual Run Time of tasks using these algorithms. After initial experimentation, it is found that in most of the cases, while comparing above parameters, the proposed approach is producing better results than FCFS algorithm. But results produced by SJF algorithm produce better results. To reduce the number of unhandled jobs, a new load state is introduced which checks load beyond conventional load states. Major objective of this approach is to reduce the need of runtime virtual machine migration and to reduce the wastage of resources, which may be occurring due to predefined values of threshold. The implementation is done using CloudSim.

VANET Based p-RSA Scheduling Algorithm Using Dynamic Cloud Storage

Future intelligent transport systems would heavily rely on Vehicular Ad hoc Network which provides seamless services to the driver on national high-ways. This paper proposes priority based RSA algorithm (p-RSA). The proposed algorithm replaces road side unit with dynamic cloud to reduce the physical infrastructure from the network, provide larger scope of services maintain quality of service to the users. pRSA being on dynamic cloud gives information of the entire traffic to all the vehicles in the range and also the central controlling unit. During call for an emergency service, nearest Police Control Room van is sent a SOS (distress signal can be interpreted as Save our Soul) and at the same time nearest Police Picket and Medical services are alerted. Being on global positioning system and cloud even during misty or foggy conditions every vehicle would know where exactly it is heading and even if a target comes close to other vehicle a warning would flash on the screen with loud beep, the speed would be automatically cut-down to maintain the distance between the vehicles, not only ahead of it, but also behind the target vehicle. Scheduling of pRSA has been compared with first come first serve (FCFS), smallest data size first (SDF) and new method using Deadline and Size of Data (NDS) algorithms on the basis of skew, the priority factor increased by 93.75, 31.25 and 18.75% in comparison to FCFS, SDF and NDS algorithm respectively. Bandwidth consumption and energy utilization are 12.0 and 5.56% less than NDS.

Anonymity and Fairness in Packet Scheduling: A Quantitative Tradeoff

Fairness among multiple users sharing a common resource is an important criterion in the design and evaluation of scheduling algorithms in networks. Anonymous networking, where sources of transmitted packets are undecipherable to an eavesdropper, requires packets arriving at routers from multiple sources to be randomly reordered prior to transmission, which works against the notion of temporal fairness in packet scheduling. Consequently, it is important to understand the relationship between temporal fairness and achievable anonymity. In this paper, this relationship is investigated for three fair scheduling paradigms: First-Come--First-Serve (FCFS), Fair Queuing, and the Proportional Method. Using an information-theoretic metric for anonymity and a common temporal fairness index that measures the degree of out-of-order transmissions, the anonymity achievable under these scheduling paradigms is characterized and their anonymity-fairness tradeoffs are compared. The FCFS and Fair Queuing algorithms have little inherent anonymity, and a significant improvement in anonymity is achieved by relaxing their respective fairness paradigms. The analysis of the relaxed FCFS criterion, in particular, is accomplished by modeling the problem as a stochastic control system that is solved using dynamic programming. The proportional method of scheduling, while unpopular in networks today, is shown to outperform the other fair scheduling algorithms when trading temporal fairness for anonymity, and is also proven to be asymptotically optimal as the buffer size of the scheduler is increased.

Resource Allocation Algorithm Modeling in Queuing System Based on Quantization

The work relevance is determined by the urgent need to design and study queuing systems (QS). The selection and justification of resource management laws - the standby and service disciplines are very important here. The main aim of the study is to develop a QS simulation model with non-priority cyclic service RR (round robin) discipline, to compare the performance of the system under different control algorithm resources: RR and FCFS (first come-first served). To develop a simulation model the system of dynamic and event-driven modeling Matlab + Simulink and SimEvents libraries were used. 5 parallel processes were consistently allocated in RR time quantum algorithm. To imitate FCFS algorithm the round-robin size was set equal to 1. The testing of the developed QS model confirmed a correctness of its work. By varying the flow in the short and long (performance time) processes, it was shown that an advantage of RR algorithm over FCFS is observed, if a share of long processes is not more than 20 - 30%.

A Dynamic Packet Scheduling Scheme with Multilevel Priority for Wireless Sensor Network

Packet scheduling is one of the critical issues in wireless sensor networks. In WSNs most existing scheduling mechanisms use FCFS, non-preemptive or preemptive priority algorithms. However, most of these algorithms incur high processing overhead and high end-to-end transmission delay due to the FCFS concept and starvation of real time and nonreal time data packets in non-preemptive and preemptive priority scheduling algorithms. Also, these packet scheduling algorithms are predetermined and hence cannot change in application requirements of WSNs. Therefore, in this paper, we propose a dynamic multilevel priority (DMP) packet scheduling algorithm to overcome the short comes like starvation of real time data, end-to-end or data transmission delay, and to make the packet scheduling dynamic. It is well known that in DMP scheduling scheme, nodes are organized in hierarchical structure and each node (except those nodes which are located at last level of hierarchical structure) has three level of priority queues in which real time data packets go to highest priority queue and non-real time data packets go to other two queues based on certain threshold levels of their estimated processing time. The DMP scheme proposed in this work was implemented with network simulator (NS2) v.2.32. The results obtained (end-to-end delay, average waiting time, network lifetime, and energy consumption) indicate the proposed DMP scheme is superior to existing first come first serve (FCFS) packet scheduling scheme. General Terms Wireless Sensor Network, FCFS.

Research on Arrival/Departure Scheduling of Flights on Multirunways Based on Genetic Algorithm

Aiming at the phenomenon of a large number of flight delays in the terminal area makes a reasonable scheduling for the approach and departure flights, which will minimize flight delay losses and improve runway utilization. This paper considered factors such as operating conditions and safety interval of multi runways; the maximum throughput and minimum flight delay losses as well as robustness were taken as objective functions; the model of optimization scheduling of approach and departure flights was established. Finally, the genetic algorithm was introduced to solve the model. The results showed that, in the program whose advance is not counted as a loss, its runway throughput is improved by 18.4%, the delay losses are reduced by 85.8%, and the robustness is increased by 20% compared with the results of FCFS (first come first served) algorithm, while, compared with the program whose advance is counted as a loss, the runway throughput is improved by 15.16%, flight delay losses are decreased by 75.64%, and the robustness is also increased by 20%. The algorithm can improve the efficiency and reduce delay losses effectively and reduce the workload of controllers, thereby improving economic results.

Research on Mechanical Operation with Sequencing Optimization of Arrival Aircraft in Terminal Area

In order to ensure flight safety and efficiently sequence arrival aircrafts in terminal area, a sequencing model for scheduling the sequence of arrival aircrafts in the terminal area was discussed. Model's objective is minimizing the loss of delays due to meeting separation which is used to keep the safety of aircrafts before and afterwards. Then the model is transferred to pure integer nonlinear program model so that the model can be solved by some program software like Lingo. At last, a numerical example is used to illustrate the process of solving the model. The numerical example shows that the model proposed in this paper is extremely efficient in scheduling the sequence of arrival flights compared with the FCFS (first come first served) algorithm and model used for the aircraft sequencing in the terminal area is feasible.

Minimum CDT based Scheduling Algorithm versus FCFS in Grid Environment

To achieve the promising potentials of tremendous distributed resources, effective and efficient scheduling algorithms are fundamentally important. Unfortunately, scheduling algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, e.g. computer clusters, cannot work well in the new circumstances. In this research paper, MJ_CDTmin [1] (multiple jobs based on the minimum cumulative departure time) algorithm is compared with the already existing FCFS (First Come First Serve) algorithm in terms of the execution time (in secs).Since there were no results for minimizing the execution time in for existing algorithms. Hence the comparison is done only for the proposed algorithms. This is achieved with the experimental test bed by specifying deadline, while submitting the jobs. Simulation was carried out by different number of jobs varying from 1000 to 10,000. In the experimental testing heterogeneous machines were used and tested for different number of tasks/jobs. During the experiment, the comparison was carried out by considering the six different values for the Service time ( of the jobs. The main aim of proposed scheduling algorithm is to increase the system efficiency and to satisfy the job requirements from the available resources. The experimental results showed a significant improvement in terms of a smaller makespan time as compared to the already existing FCFS scheduling algorithm. Keyword

General packet induced queueing schemes for reducing packet delays in ADSL routers with peer-to-peer file sharing applications

This paper proposes a class of queueing schemes named general packet induced queueing schemes (GPIQS) in ADSL routers to reduce the queueing delays of non-P2P packets. The objective of the proposed queueing schemes is to send out the general packets first as well as P2P packets are able to be sent in a bounded queueing delay. The proposed queueing schemes use the general packet to induce the transmission of P2P packets which are from the same client and arrived at the ADSL router before the general packet. The outbound order of the packets transmitted from a specific client is not altered in the proposed schemes. Two queueing schemes named general packet induced queueing scheme with single P2P queue (GPIQS-SQ) and general packet induced queueing scheme with multiple P2P queues (GPIQS-MQ) are proposed. The two proposed queueing schemes differ in the number of P2P queues. In order to prevent the unlimited waiting time of P2P packets, we introduced a variable called the largest number of preempting packets to send out the P2P packets in a bounded time. Simulation results show that the proposed queueing schemes may send out the packets from ADSL router efficiently and the average queueing delay is smaller than the common used first-come first-served algorithm. Specifically, the GPIQS-MQ performs better than the GPIQS-SQ method in terms of average queueing delay of non-P2P packets. We also found that the increased average queueing delay of P2P packets is small. Finally, the values of the largest number of preempting packets are discussed.

Tasks Scheduling using Ant Colony Optimization

Problem statement: Efficient scheduling of the tasks to heterogeneous processors for any application is critical in order to achieve high pe rformance. Finding a feasible schedule for a given task set to a set of heterogeneous processors without ex ceeding the capacity of the processors, in general, is NP-Hard. Even if there are many conventional approaches available, people have been looking at unconventional approaches for solving this problem. This study uses a paradigm using Ant Colony Optimisation (ACO) for arriving at a schedule. Approach: An attempt is made to arrive at a feasible schedule of a task set on heterogeneous processors ensuring load balancing across the processors. The heterogeneity of the processors is modelled by assu ming different utilisation times for the same task on different processors. ACO, a bio-inspired computing paradigm, is used for generating the schedule. Results: For a given instance of the problem, ten runs are c onducted based on an ACO algorithm and the average wait time of all tasks is computed. Also th e average utilisation of each processor is calculat ed. For the same instance, the two parameters: average wait time of tasks and utilisation of processors ar e computed using the First Come First Served (FCFS). The results are tabulated and compared and it is found that ACO performs better than the FCFS with respect to the wait time. Although the processor utilisation is more for some processors using FCFS algorithm, it is found that the load is better bala nced among the processors in ACO. There is a marginal increase in the time for arriving at a schedule in AC O compared to FCFS algorithm. Conclusion: This approach to the tasks assignment problem using ACO performs better with respect to the two parameters used compared to the FCFS algorithm but the time taken to come up with the schedule using ACO is sli ghtly more than that of FCFS.

Calculus and Probability Determine the Performance of a Disk Drive

The performance of a disk drive depends on the disk scheduling algorithms employed. The mean response time for the scan algorithm and for the first-come first-served algorithm is derived using elementary calculus and probability techniques. The analysis shows that the scan algorithm performs better than the first-come first-served algorithm except at low rates of request for disk access.