Priority Queuing and Scheduling Algorithms Analysis Using Opnet Modeler

This work investigates which algorithm of scheduling algorithm will provide the best QoS for which type of application in addition to how stationary nodes and mobile nodes affect the network in terms of mobility and time. We used variable scheduling algorithms Weighted Fair Queuing (WFQ), Priority Queuing (PQ),First In First Out (FIFO) for different applications including real-time and non-real-time, in the context of mobility and stationery to investigate which algorithm of scheduling will provide the best quality of service with presenting a HetNet based LTE-A architecture including macrocell, picocells and femtocells.

The paper considers both the basic mechanisms of queue management on the router and the principle of their operation. A comparative analysis of the following queuing mechanisms: FIFO (First-In First-Out), CQ (Custom Queuing), PQ (Priority Queuing), WFQ (Weighted Fair Queuing), CBWFQ (Class Based Weighted Fair Queuing) and LLQ (Low Latency Queuing) based on a number of parameters such as traffic volume, traffic type, service of mixed traffic, enable on router and number of queues was made. The results of analysis showed that each of the queuing mechanisms has its advantages when dealing with certain types of traffic. Whereas in the process of load balancing several interfaces of the router are involved simultaneously the choice of queuing mechanism on each of them will depend on QoS for real-time traffic. Thus in this work the effect of various queue management mechanisms (such as FIFO, PQ, CQ, WFQ, LLQ) to QoS for real-time traffic in the process of load balancing on the router in an IP network was also investigated. The simulation results showed that most of queuing mechanisms (except FIFO and CQ) in the process of load balancing allowed to provide high QoS for real time traffic by reducing the values of delays and jitter and a significant reduction of lost packets for such traffic flows. At the same time the results showed that in the load balancing process, the most efficient queues servicing mechanism is LLQ, which provides the lowest delay for VoIP and the end to-end delay commensurable with the PQ mechanism for video traffic.

his paper studies under what conditions congestion control schemes can be both efficient, so that capacity is not wasted, and incentive compatible, so that each participant can maximize its utility by following the prescribed protocol. We show that both conditions can be achieved if routers run strict priority queueing (SPQ) or weighted fair queueing (WFQ) and end-hosts run any of a family of protocols which we call Probing Increase Educated Decrease (PIED). A natural question is whether incentive compatibility and efficiency are possible while avoiding the per-flow processing of WFQ. We partially address that question in the negative by showing that any policy satisfying a certain "locality" condition cannot guarantee both properties. Our results also have implication for convergence to some steady-state throughput for the flows. Even when senders transmit at a fixed rate (as in a UDP flow which does not react to congestion), feedback effects among the routers can result in complex dynamics which do not appear in the simple topologies studied in past work.

Fair and Delay Adaptive Scheduler (FDAS) is a scheduling mechanism that dynamically adapts to the incoming traffic flows' requirements in term of bandwidth allocation, delay bounds and packet loss restrictions. It performs this utilizing both virtual finish time fluid scheduling along with schedulability and delay sensitive scheduling. The former ensures that the flows receive a fair share of the available output throughput while the later ensures that time critical flows that are about to expire will receive preferential treatment when needed to avoid getting garbled and dropped when possible. FDAS tries to maximize the satisfaction as perceived by incoming traffic flows through balancing between bandwidth fairness and delay bound accommodation. FDAS acts as a hybrid scheduler that tries to overcome fairness allocation problems due to preferential treatment for the soon-to-expire packets which happens in Earliest Deadline First (EDF) schedulers. Meanwhile, it tries to minimize the number of packets that violate their deadlines for transmission and get garbled accordingly that happens on Weighted Fair Queuing (WFQ) and its derivatives. In this paper, we try to answer the question of how many of the flows and how much of their traffic can be accommodated in terms of delay bound and throughput requirements given the incoming mixture of traffic with diverse QoS requirements. FDAS preliminary modeling and optimization is discussed in this paper to answer the above question in a manner that maximizes the overall performance satisfaction as perceived by incoming flows taking into consideration traffic priorities, if any.

본 논문에서는 WDRR(Weighted Deficit Round Robin) 기법을 토대로 군사 위성통신망의 QoS를 향상시키기 위한 스케줄링 기법을 제안한다. 제안된 동적 WDRR기법은 통신망 대기열의 패킷의 크기가 커지는 경우 지수이동평균을 이용, 적절한 추가 퀀텀을 부여하여 대기열의 패킷을 효율적으로 전송하는 방법이다. 제안된 알고리즘의 효용성을 증명하기 위해 OPNET Modeler를 이용하여 모의실험환경을 구축하고, 제안된 알고리즘의 신뢰성 및 실시간성을 분석하였다. 이를 통하여, 기존 군사용 위성통신망 스케줄링 기법에 사용되는 WRR(Weighted Round Robin), DRR(Deficit Round Robin), WDRR(Weighted Deficit Round Robin) 등을 비교 분석한 모의실험 결과를 통해 통신망 지연시간과 패킷 손실율에 관한 성능 향상을 보였다.

The Poisson distribution is a fundamental concept in probability theory and statistics. It is widely used to model the occurrence of rare events across diverse fields, including physics, biology, finance, and medicine. It offers a way to calculate the likelihood of a certain number of events occurring within a specified time period, assuming the events happen independently of one another. The Poisson distribution is commonly used to predict the outcome of random, independent events. In heavy ion-induced nuclear reactions where compound nuclei are formed under conditions of high spin and moderate excitation energy, the investigation of one or multiple neutron emissions is of particular interest. When heavy-ion reactions occur, a random number of neutrons may be released as the target becomes excited by partial or complete absorption of projectile energy, leading to the formation of a highly excited composite system. These neutrons are statistically evaporated to de-excite the compound nucleus (CN). The Poisson distribution function can thus be applied to describe the decay probability of an excited nucleus, particularly for predicting the emission of a specific number of neutrons. In this process, the excess of excitation energy over the binding energy of the released neutrons acts as the continuous variable, and the number of released neutrons serves as the discrete variable. This framework helps us quantify the likelihood of observing a given number of neutrons emitted from an excited nucleus formed in a typical nuclear reaction. In this work, the measured cross-section data for multiple neutron evaporation channels in systems such as [Formula: see text]Ho, [Formula: see text]Tm, [Formula: see text]Te, [Formula: see text]Nd, [Formula: see text]Tm, [Formula: see text]Yb and [Formula: see text]Lu reactions have been analyzed using the Poisson distribution. This approach allows all open channels to be treated simultaneously, offering a simplified yet physically meaningful alternative to more elaborate statistical models.

Although weighted fair queueing (WFQ) has been regarded as an ideal scheduling algorithm in terms of its combined delay bound and proportional fairness properties, its asymptotic time complexity increases linearly with the number of sessions serviced by the scheduler, thus limiting its use in high-speed networks. An algorithm that combines the delay and fairness bounds of WFQ with O(1) timestamp computations had remained elusive so far. In this paper we present two novel scheduling algorithms that have O(1) complexity for timestamp computations and provide the same bounds on end-to-end delay and buffer requirements as those of WFQ. The first algorithm, frame-based fair queueing (FFQ), uses a framing mechanism to periodically recalibrate a global variable tracking the progress of work in the system, limiting any short-term unfairness to within a frame period. The second algorithm, starting potential based fair queueing (SPFQ), performs the recalibration at packet boundaries, resulting in improved fairness while still maintaining the O(1) timestamp computations. Both algorithms are based on the general framework of rate-proportional servers (RPSs) introduced by Stiliadis and Varma (see ibid., vol.6, no.2, p.164-74, 1998). The algorithms may be used in both general packet networks with variable packet sizes and in asynchronous transfer mode (ATM) networks.

A bi-objective truck scheduling problem in a cross-docking center with probability of breakdown for trucks

This paper focuses on the capacity of wireless ad hoc networks and analyzes the effect of key factors viz. network size, traffic patterns and detailed local radio interactions on the capacity of such networks. The capacity is evaluated with several different network layouts and traffic patterns through simulations. To demonstrate the impact of these factors, the capacity evaluation starts with a simple case of a chain of evenly spaced nodes in a network environment and progresses to a network with random traffic and randomly spaced nodes. Initially, capacity of static nodes is evaluated for various network layouts and traffic patterns. Since, in most scenarios, nodes do not travel significant distances during packet transmissions. As an enhancement, mobility of nodes is introduced into the network scenario and the performance is again evaluated. The simulations are carried out using OPNET modeler and the results obtained are presented in this report. The results are analyzed to understand the impact of these factors on the capacity and consequently suggest measures to increase the same. This work shows that the achievable capacity of ad hoc network depends on network size, traffic pattern and mobility. In a single cell topology, it is found that there is a 50% reduction in network throughput, if the node size increases from 2 to 10 nodes, whereas there is a 74% reduction in the throughput for chain topology for the same increase in node size. In a lattice topology with horizontal traffic, there is a 46 % reduction in network throughput when the lattice size increases from 4X4 to 5x5.The same percentage of reduction is observed when both horizontal and network traffic is introduced. In a random network topology with random traffic, there is an 80 % reduction in network throughput when the node size increases from 150 to 750 nodes. However, for the same scenario with the introduction of mobility to the nodes, a slight improvement is achieved with an overall 75% reduction in network throughput.

Low cost broadband services used widely in the recent years increased the demand for multimedia applications. Many of these applications require different quality of service (QoS) in terms of throughput and delay. In the current resource constrained wireless networks, resource management plays a vital role. In order to handle the resources effectively and to increase the QoS, proper packet scheduling algorithms need to be developed. Low latency queuing (LLQ) is a packet scheduling algorithm which combines strict priority queuing (SPQ) to class-based weighted fair queuing (CBWFQ). In this paper, an enhanced low latency queuing (ELLQ) algorithm is proposed in which an additional SPQ is introduced along with the existing SPQ. Further, the QoS is improved by integrating congestion avoidance algorithm with ELLQ. Simulation results using the OPNET modeller show that the proposed algorithm outperforms the existing algorithm in terms of throughput and delay for the multimedia applications.

This paper is concerned with a discrete-time $ Geo/G/1$ retrial queueing system with non-preemptive priority, working vacations and vacation interruption where the service times and retrial times are arbitrarily distributed. If an arriving customer finds the server free, his service commences immediately. Otherwise, he either joins the priority queue with probability $ α$, or leaves the service area and enters the retrial group (orbit) with probability $ \mathit{\bar{\alpha }}\left( = 1-\alpha \right)$. Customers in the priority queue have non-preemptive priority over those in the orbit. Whenever the system becomes empty, the server takes working vacation during which the server can serve customers at a lower service rate. If there are customers in the system at the epoch of a service completion, the server resumes the normal working level whether the working vacation ends or not (i.e., working vacation interruption occurs). Otherwise, the server proceeds with the vacation. Employing supplementary variable method and generating function technique, we analyze the underlying Markov chain of the considered queueing model, and obtain the stationary distribution of the Markov chain, the generating functions for the number of customers in the priority queue, in the orbit and in the system, as well as some crucial performance measures in steady state. Furthermore, the relation between our discrete-time queue and its continuous-time counterpart is investigated. Finally, some numerical examples are provided to explore the effect of various system parameters on the queueing characteristics.

This work discusses the development of information technology service management using cloud computing approach to improve the performance of administration system and online learning at STMIK IBBI Medan, Indonesia. The network topology is modeled and simulated for system administration and online learning. The same network topology is developed in cloud computing using Amazon AWS architecture. The model is designed and modeled using Riverbed Academic Edition Modeler to obtain values of the parameters: delay, load, CPU utilization, and throughput. The simu- lation results are the following. For network topology 1, without cloud computing, the average delay is 54 ms, load 110 000 bits/s, CPU utilization 1.1%, and throughput 440 bits/s. With cloud computing, the average delay is 45 ms, load 2 800 bits/s, CPU utilization 0.03%, and throughput 540 bits/s. For network topology 2, without cloud computing, the average delay is 39 ms, load 3 500 bits/s, CPU utilization 0.02%, and throughput database server 1 400 bits/s. With cloud computing, the average delay is 26 ms, load 5 400 bits/s, CPU utilization email server 0.0001%, FTP server 0.001%, HTTP server 0.0002%, throughput email server 85 bits/s, FTP server 100 bits/sec, and HTTP server 95 bits/s. Thus, the delay, the load, and the CPU utilization decrease; but, the throughput increases. Information technology service management with cloud computing approach has better performance.

IEEE 802.16 standard supports real time and non-real time services at each node. However, it has flexibility to develop customized scheduling algorithms according to different priority-based traffic's quality of service (QoS) requirements. Hence, it is imperative to obtain optimum scheduling schemes for different kinds of traffic (i.e., services). Earliest due date (EDD) is one of the highly referred scheduling algorithms for real time communication. In this presentation, our study shows that the proposed hybrid algorithms (EDD along with weighted fair queue (WFQ)) in a node gives better performance for real time services instead of EDD only. Moreover, the results reveal that, scheduling schemes from base station (BS) to subscriber station (SS) like grant per SS (GPSS) impacts less delay than grant per connection (GPC)

Input queuing has become dominant and popular building blocks for high speed crossbar switches with many ports and fast line rates because they require minimum speed-up of memory bandwidth. Input Queued switches with finite Virtual Output Queues guarantees QoS performance in terms of throughput and average delay. A switch performs two functions Queuing and Scheduling. Queue Management algorithm manages the size of the queues and drops packets when necessary or appropriate. Scheduling algorithms determine next packet to transfer and solves conflicts with the switching fabric. Fairness and Starvation are another two properties of IQ switches and it is analyzed in finite VOQ in this works. Fairness performs fair allocation of bandwidth among flows and prevents flows from misbehaving flows. Starvation of VOQ prevents serving High priority queue. The motivation behind this study is to schedule the HoL packets queued in finite VOQs by Framing with Low Latency Queuing (LLQ) and Weighted Fair Queueing (WFQ). This queueing technique of VOQ is measured in terms of throughput and average delay by fair allocation of bandwidth with WFQ and Starvation-free queue with LLQ.

In this paper, a hybrid spatial and temporal scheduling algorithm for wireless networked control system, which takes the distance between robot and task region as well as the deadline of a task into consideration is proposed. In our method, we quantify spatial and temporal factors for eventually getting the priority queue. Based on the priority queue, the robot is able to execute the tasks sequentially. At last, extensive simulations are conducted to show the advantages of our spatial and temporal scheduling algorithm. Simulation results show that, on the premise of ensuring high successful scheduling rate, compared with previous method, our scheme show merits in terms of task requesting throughput, successful task solving ratio, average responding delay.