Abstract: Effective patient queue management to minimize patient wait delays and patient overcrowding is one of the major challenges faced by hospitals. Unnecessary and annoying waits for long periods result in substantial human resource and time wastage and increase the frustration endured by patients. For each patient in the queue, the total treatment time of all the patients before him is the time that he must wait. It would be convenient and preferable if the patients could receive the most efficient treatment plan and know the predicted waiting time through a mobile application that updates in real time. Therefore, we propose a Patient Treatment Time Prediction (PTTP) algorithm to predict the waiting time for each treatment task for a patient. We use realistic patient data from various hospitals to obtain a patient treatment time model for each task. Based on this large-scale, realistic dataset, the treatment time for each patient in the current queue of each task is predicted. Based on the predicted waiting time, a Hospital Queuing-Recommendation (HQR) system is developed. HQR calculates and predicts an efficient and convenient treatment plan recommended for the patient. Because of the large-scale, realistic dataset and the requirement for real-time response, the PTTP algorithm and HQR system mandate efficiency and low-latency response. We use an Apache Spark-based cloud implementation at the National Supercomputing Center in Changsha to achieve the aforementioned goals. Extensive experimentation and simulation results demonstrate the effectiveness and applicability of our proposed model to recommend an effective treatment plan for patients to minimize their wait times in hospitals.

Abstract: We study Compound TCP (C-TCP), the default TCP in the Windows operating system, with Random Exponential Marking (REM) and the widely used Drop-Tail queue policy. The performance metrics we consider are stability of the queue size, queuing delay, link utilization, and packet loss. We analyze the following models: 1) a nonlinear model for C-TCP with Drop-Tail and small buffers; 2) a stochastic variant of REM along with C-TCP; and 3) the original REM proposal as a continuous-time nonlinear model with delayed feedback. We derive conditions to ensure local stability and show that variations in system parameters can induce a Hopf bifurcation, which would lead to the emergence of limit cycles. With Drop-Tail and small buffers, the Compound parameters and the buffer size both play a key role in ensuring stability. In the stochastic variant of REM, larger thresholds for marking/dropping packets can destabilize the system. With the original REM proposal, using Poincare normal forms and the center manifold analysis, we also characterize the type of the Hopf bifurcation. This enables us to analytically verify the stability of the bifurcating limit cycles. Packet-level simulations corroborate some of the analysis. Some design guidelines to ensure stability and low latency are outlined.

Abstract: FISCHER'21 has shown that in the standard first-come-first-served queuing system Ek/M/1, the average stationary waiting time (in queue) of an arriving customer decreases monotonically in k for fixed arrival and service rates. The analogous result for the queuing system M/G/1 is a simple consequence of the Pollaczek-Khintchine formula. These results easily follow from more general theorems in references 4-6 and 9. This paper gives a short survey of results concerning the comparison of the stationary waiting time for GI/G/1 queues. We shall use the concept of a semi-ordering relation in the set of distribution functions (d.f. 's). (1)

Abstract: Queue management systems allow a long queue/line of people to be held in a relatively small area. However, if there is no queue/line the system may frustrate users. The invention provides in one aspect a queue management gate 110 comprising an attachment device 150 for attaching the queue management gate to a stanchion 30 of the type used in queue management systems which include flexible tapes extending between stanchions to form lanes, the gate further comprising a relatively rigid movable barrier 60, movable in a substantially horizontal plane, the gate for allowing access between adjacent lanes formed by the queue management system such that users may avoid walking through the empty lanes formed by the queue management system.

Abstract: We consider a two-queue polling model in which customers upon arrival join the shorter of two queues. Customers arrive according to a Poisson process and the service times in both queues are independent and identically distributed random variables having the exponential distribution. The two-dimensional process of the numbers of customers at the queue where the server is and at the other queue is a two-dimensional Markov process. We derive its equilibrium distribution using two methodologies: the compensation approach and a reduction to a boundary value problem.

Abstract: We present the development and evaluation of a situated crowdsourcing mechanism that estimates queue length in real time. The system relies on public interactive kiosks to collect human estimations about their queue waiting time. The system has been designed as a standalone tool that can be retrospectively embedded in a variety of locations without interfacing with billing or customer systems. An initial study was conducted in order to determine whether people who just joined the queue would differ in their estimates from people who were at the front of the queue. We then present our system's evaluation in four different restaurants over 19 weekdays. Our analysis shows how our system is perceived by users, and we develop 2 ways to optimise the waiting time estimation: by correcting the estimations based on the position of the input mechanism, and by changing the sliding window considered inputs to provide better prediction. Our analysis shows that approximately 7% of restaurant customers provided estimations, but even so our system can provide predictions with up to 2 minute mean absolute error.

Abstract: In CPU scheduling various algorithms exist like FCFS (First come first serve), SJF (Shortest job first), SRTF (Shortest remaining time first), Priority Scheduling, Round Robin (RR), MLQ (Multilevel queue), MLFQ (Multilevel feedback queue) scheduling. Multilevel Feedback Queue (MLFQ) algorithm allows the switching of processes between queues depending on their burst time. The processes switch to the next queue when burst time is greater than time quantum. Each queue can define its own scheduling policy. In this paper we have implemented MLFQ technique using small burst time for the first queue thus making it analogous to RR scheduling and using SJF prior to RR from second queue onwards gives better CPU utilization. Dynamic time quantum is also used which further improves the efficiency of the scheduling. Here the dynamic time quantum of the queues is calculated based on the burst time of the processes. Time quantum of the second queue is the burst time of the (2n/3)th process (where n is the number of processes remaining after the execution in the first queue) and time quantum of the third queue is burst time of the largest remaining process. Thus 66% of the processes get executed in the second queue and remaining processes in the last queue thus preventing the problem of starvation of huge burst time processes.

Abstract: Nowadays people spend a substantial amount of time waiting in different places such as supermarkets and amusement parks. Detecting the status of queuing may benefit both users and business. In this paper, we present QueueSense, a queuing recognition system to assist in a queue management system. QueueSense consists of clients on smartphones that provide automatic, energy-efficient, and accurate queuing recognition, and a server in the cloud that collects data, identifies multi-queue lines, and provides waiting time estimation. In order to be useful, QueueSense should be able to recognize queuing behavior in various queuing scenarios without greatly decreasing the battery life of mobile phones. We present features of queuing and build the classifier on smartphones to automatically recognize queue classifier without human input. We investigate the complicated nature of energy consumption for queue recognition on phones and design an effective algorithm to maximize energy savings while guaranteeing accuracy of queue recognition. We evaluate QueueSense performance using the data set from real world queuing scenarios collected over a three-month period. Empirical results show that QueueSense is adaptive to various queuing scenarios with both high recognition accuracy and energy efficiency. We further implemented a prototype of QueueSense, the first queue detection system using smartphones. We conducted real-world experiments in a dining hall and a supermarket near a university campus. Through implementation and evaluation, we demonstrate that QueueSense is capable of detecting waiting lines that occur in our daily lives.

Abstract: Processor sharing (PS) queuing systems and particularly their well-known class of egalitarian processor (EPS) sharing are widely investigated by research community and applied for the analysis of wire and wireless communication systems and networks. The same can be said for queuing systems in random environment, with unreliable servers, interruptions, pre-emption mechanisms. Nevertheless, only few works focus on queues with both PS discipline and unreliable servers. In the paper, compared with the previous results we analyse a finite capacity PS queuing system with unreliable server and an upper limit of the number of customers it serves simultaneously. For calculating the mean sojourn time, unlike a popular but computational complex technique of inverse Laplace transform we use an effective method based on embedded Markov chains. The paper also includes a practical numerical example of web browsing in a wireless network when the corresponding low priority traffic can be interrupted by more priority applications.

Abstract: Many network-wide traffic management strategies based on the Macroscopic or Network Fundamental Diagram (NFD) have been developed in recent years. In this paper we investigate one of these strategies, namely feedback NFD-based perimeter control, which limits the rate at which vehicles are allowed to enter an urban region. The inflow limitation is imposed at selected main entry links (gated links) and results in queuing of vehicles at the boundaries of the network. Most of the works on this subject neglected the effect of the queued vehicles on the traffic conditions upstream of the gated links. In this paper we analyze in microsimulation the queuing at the gated links and its effect on network performance for a realistic network model. Moreover, a queue management strategy based on a continuous quadratic knapsack problem aiming at balancing relative queues at the gated links is proposed. Simulation results suggest that queues under perimeter control are shorter in space and time than with no perimeter control. Additionally, managing the queues at the gated links not only improves the overall network performance but also reduces the possibility of queue propagation to the upstream junctions. This improves traffic flow outside the protected network.

Abstract: Congestion management for transmission control protocol is of utmost importance to prevent packet loss within a network. This necessitates strategies for active queue management. The most applied active queue management strategies have their inherent disadvantages which lead to suboptimal performance and even instability in the case of large round trip time and/or external disturbance. This paper presents an internal model control robust queue management scheme with two degrees of freedom in order to restrict the undesired effects of large and small round trip time and parameter variations in the queue management. Conventional approaches such as proportional integral and random early detection procedures lead to unstable behaviour due to large delay. Moreover, internal model control–Smith scheme suffers from large oscillations due to the large round trip time. On the other hand, other schemes such as internal model control–proportional integral and derivative show excessive sluggish performance for small round trip time values. To overcome these shortcomings, we introduce a system entailing two individual controllers for queue management and disturbance rejection, simultaneously. Simulation results based on Matlab/Simulink and also Network Simulator 2 NS2 demonstrate the effectiveness of the procedure and verify the analytical approach.

Abstract: Queue Information & Prediction System (QIPS) uses the probability of queue existing in a given venue to assess the queue time. The instantaneous queue time for a location may be determined using Bluetooth, Wi-Fi, or other wireless networks. QIPS uses the distances from signal strengths along with venue characteristics to determine an estimated queue time. Using queue probability for a venue and the instantaneous queue time for the same area QIPS may generate a Queue Decision Window (QDW). The QDW is a period of time leading up to a transaction or a consumption of a service. QIPS sorts through information surrounding a venue where crowds as well as queues may exists to determine queue time. Knowing the approximate queue time for transactions and consumption of services is helpful for consumers to manage their time.

Abstract: In this paper, we propose a reference architecture for Delay-Tolerant Networking (DTN) routing protocols and a thorough quantitative evaluation of many protocols proposed in the literature. We categorize DTN protocols according to their use of the three techniques that are the key elements of our reference architecture: queue management, forwarding and replication. Queue management orders and manages the messages in the node’s buffer; forwarding selects the messages to be delivered when there is a contact; and finally, replication bounds the number of replicas in the network. Contrary to most previous papers, where either only qualitative comparisons have been presented or only a single category of protocols has been analyzed, in our work, we discuss the results of our experimental activity on many of the DTN protocols in the literature. Our results, which have been obtained both using synthetic and real mobility traces, show that an effective combination of the proposed techniques can significantly improve the performance of the protocols in terms of delivery ratio, overhead and delay.

Abstract: Ferry service plays an important role in several cities with waterfront areas. Transportation authorities often need to forecast volumes of vehicular traffic in queues waiting to board ships at ferry terminals to ensure sufficient capacity and establish schedules that meet demand. Several previous studies have developed models for long-term vehicle queue length prediction at ferry terminals using terminal operation data. Few studies, however, have been undertaken for short-term vehicular queue length prediction. In this study, machine learning methods including the artificial neural network (ANN) and support vector machine (SVM) are applied to predict vehicle waiting queue lengths at ferry terminals. Through time series analysis, the existence of a periodic queue-length pattern is established. Hence, methodologies used in this study take into account periodic features of vehicle queue data at terminals for prediction. To further consider the cyclical characteristics of vehicle queue data at ferry terminals, a prediction approach is proposed to decompose vehicle waiting queue length into two components: a periodic part and a dynamic part. A trigonometric regression function is introduced to capture the periodic component, and the dynamic part is modeled by SVM and ANN models. Moreover, an assembly technique for combining SVM and ANN models is proposed to aggregate multiple prediction models and in turn achieve better results than could be attained from a lone predictive method. The prediction results suggest that for multi-step ahead vehicle queue length prediction at ferry terminals, the ensemble model outperforms the separate prediction models and the hybrid models, especially as prediction step size increases. This research has important practical significance to both traffic service management interests and the travelers in cities along waterfront areas.

Abstract: Delay-tolerant networks (DTNs) have attracted increasing attention from governments, academia and industries in recent years. They are designed to provide a communication channel that exploits the inherent mobility of trams, buses and cars. However, the resulting highly dynamic network suffers from frequent disconnections, thereby making node-to-node communications extremely challenging. Researchers have thus proposed many routing/forwarding strategies in order to achieve high delivery ratios and/or low latencies and/or low overheads. Their main idea is to have nodes store and carry information bundles until a forwarding opportunity arises. This, however, creates the following problems. Nodes may have short contacts and/or insufficient buffer space. Consequently, nodes need to determine (i) the delivery order of bundles at each forwarding opportunity and (ii) the bundles that should be dropped when their buffer is full. To this end, we propose an efficient scheduling and drop policy for use under quota-based protocols. In particular, we make use of the encounter rate of nodes and context information such as time to live, number of available replicas and maximum number of forwarded bundle replicas to derive a bundle’s priority. Simulation results, over a service quality metric comprising of delivery, delay and overhead, show that the proposed policy achieves up to 80 % improvement when nodes have an infinite buffer and up to 35 % when nodes have a finite buffer over six popular queuing policies: Drop Oldest (DO), Last Input First Output (LIFO), First Input First Output (FIFO), Most FOrwarded first (MOFO), LEast PRobable first (LEPR) and drop bundles with the greatest hop-count (HOP-COUNT).

Abstract: In this paper, we consider a cognitive scenario where an energy harvesting secondary user shares the spectrum with a primary user. The secondary source helps the primary source in delivering its undelivered packets during periods of silence of the primary source. The primary source has a queue for storing its data packets, whereas the secondary source has two data queues: a queue for storing its own packets and the other for storing the fraction of the undelivered primary packets accepted for relaying. The secondary source is assumed to be a battery-based node, which harvests energy packets from the environment. In addition to its data queues, the secondary user has an energy queue to store the harvested energy packets. The secondary energy packets are used for primary packets decoding and data packets transmission. More specifically, if the secondary energy queue is empty, the secondary source can neither help the primary source nor transmit a packet from the data queues. The energy queue is modeled as a discrete-time queue with Markov arrival and service processes. Because of the interaction of the queues, we provide inner and outer bounds on the stability region of the proposed system. We investigate the impact of the energy arrival rate on the stability region. Numerical results show the significant gain of cooperation.Copyright © 2014 John Wiley & Sons, Ltd.

Abstract: On a highway setup, a vehicle will most probably use a tollgate server that has the shortest queue thinking that it is the fastest exit. In this paper, an intelligent highway tollgate queue selector using fuzzy logic is proposed and simulated in Matlab SimEvents. Its aim is to automatically select the most appropriate tollgate server for a vehicle to ensure the shortest waiting time while trying to balance the server's utilization. Two policies are considered in this study, namely: (1) Shortest Queue (SQ) and (2) Fuzzy Logic-Controlled Queue (FLCQ). Results indicate that the FLCQ policies reduce the average waiting time and queue length by approximately 50% of those obtained from the SQ policy while guaranteeing an equal utilization among available servers. These findings are valid for light and heavy, homogeneous and nonhomogeneous vehicle arrivals. To further improve the decision making of the fuzzy logic controller, traffic flow information collected by remote road-side units can be exploited to allow the control of various system parameters (e.g., service time) in advance.

Abstract: Approaches are disclosed for distributing messages across multiple data centers where the data centers do not store messages using a same message queue protocol. In some embodiment, a network element translates messages from a message queue protocol (e.g., Kestrel, RABBITMQ, APACHE Kafka, and ACTIVEMQ) to an application layer messaging protocol (e.g., XMPP, MQTT, WebSocket protocol, or other application layer messaging protocols). In other embodiments, a network element translates messages from an application layer messaging protocol to a message queue protocol. Using the new approaches disclosed herein, data centers communicate using, at least in part, application layer messaging protocols to disconnect the message queue protocols used by the data centers and enable sharing messages between messages queues in the data centers. Consequently, the data centers can share messages regardless of whether the underlying message queue protocols used by the data centers (and the network devices therein) are compatible with one another.

Abstract: Waiting lines or queues are a common phenomenon in life, especially in the province of organizations that are for profit making. Queues are common in such places as petrol or filling stations, supermarkets stores, clinics, hospitals, motor parks, manufacturing firms, to mention a but a few. An interesting aspect of queuing process resides in the measures of its system's performance, especially in terms of average service rate, systems, utilization and the costs implied for a given capacity level. This paper explains the analysis of Queuing systems for the empirical data of supermarket checkout service unit using queuing theory. One of the expected gains from studying queuing systems is to review the efficiency of the models in terms of utilization and waiting length, hence increasing the number of queues so customers will not have to wait longer when servers are too busy. In other words, trying to estimate the waiting time and length of queue(s), is the aim of this study. Queuing simulation is used to obtain a sample performance result and estimated solutions for multiple queuing models are also interested. This study requires an empirical data which may include the variables like, arrival time in the queue of checkout operating unit (server), departure time, service time, etc. A questionnaire is developed to collect the data for such variables and the reaction of the Supermarket from the customers separately. This model is developed for a sales checkout operation in the supermarket. The model designed for this research is multiple queues multiple-server model. The model contains five servers which are checkout sales counters; attached to each server is a queue. In any service system, a queue forms whenever current demand exceeds the existing capacity to serve. This occurs when the checkout operation unit is too busy to serve the arriving costumers, immediately.

Abstract: Production parallel systems are space-shared, and resource allocation on such systems is usually performed using a batch queue scheduler. Jobs submitted to the batch queue experience a variable delay before the requested resources are granted. Predicting this delay can assist users in planning experiment time-frames and choosing sites with less turnaround times and can also help meta-schedulers make scheduling decisions. In this paper, we present an integrated adaptive framework, Qespera, for prediction of queue waiting times on parallel systems. We propose a novel algorithm based on spatial clustering for predictions using history of job submissions and executions. The framework uses adaptive set of strategies for choosing either distributions or summary of features to represent the system state and to compare with history jobs, varying the weights associated with the features for each job prediction, and selecting a particular algorithm dynamically for performing the prediction depending on the characteristics of the target and history jobs. Our experiments with real workload traces from different production systems demonstrate up to 22% reduction in average absolute error and up to 56% reduction in percentage prediction error over existing techniques. We also report prediction errors of less than 1i¾?h for a majority of the jobs. Copyright © 2015 John Wiley & Sons, Ltd.

Abstract: This paper considers a repairable M/G/1 retrial queue with Bernoulli schedule and a general retrial policy, which is motivated by a contention problem in the downlink direction of wireless base stations in cognitive radio networks. Arriving Customers (called primary arrivals) who cannot receive service upon arrival either join the infinite waiting space in front of the server (called as the normal queue) with probability $$q$$ , or enter the orbit with probability $$1-q$$ according to the FCFS discipline. If the server breaks down in the process of the service of a customer, the customer in service either joins the orbit queue or leaves the system forever. First, we study the ergodicity of two related embedded Markov chains and derive stationary distributions. Second, we find the steady-state joint generating function of the number of customers in both queues. Some important performance measures of the system are obtained. Third, the reliability analysis of the system is also given. Finally, numerical examples are given to illustrate the impact of system parameters on the system performance measures.

Abstract: A system and method for scheduling tasks associated with controlling access to databases. The system and method relate to scheduling tasks for data requesting systems that satisfy particular conditions. For example, data requesting systems that satisfy the conditions may have associated tasks stored in a queue during a first processing phase. Data requesting systems that do not satisfy the conditions may have associated tasks inhibited from being stored in the queue during the first processing phase, but these tasks may be stored in the queue during a later second processing phase. Tasks stored in the queue during the first processing phase may be processed before tasks stored in the queue during the second processing phase. For example, the tasks may correspond to accessing a database for querying data representing access rights to a resource.

Abstract: The problem of QoS characteristics definition for self-similar traffic for queuing system of the type W/M/1 using the Weibull distribution is considered. To solve this problem, a transformation of Laplace-Stieltjes is applied. The values of service quality characteristics for self-similar traffic QS W/M/1 such as: the average time of packets delay, the average number of requirements in QS and the length of the packet queue are obtained.

Abstract: Managing network-related resources involves sophisticated trade-off between flexibility, high performance standards, latency demands which adhere to service level agreements (SLAs) and cost constraints. Network functioning virtualization (NFV) opens new challenges to the remote network management which combines activation and control of virtual machines (VMs) according to variable demand. Currently, this functionality is being handled by harnessing the traditional orchestration algorithms using suboptimal heuristics. We model the problem of virtual network function (VNF) allocation by queuing system with flexible number of queues, which captures variety of constraints including queue deployment and displacement, delay cost, holding cost, scheduling reward and fine. Next, we model the system by Markov decision process (MDP) and numerically solve it to find the optimal policy. We show analytically and by simulations that the optimal policy possesses decision thresholds which depend on several parameters.1

Abstract: Apparatus and methods implementing a hardware queue management device for reducing inter-core data transfer overhead by offloading request management and data coherency tasks from the CPU cores. The apparatus include multi-core processors, a shared L3 or last-level cache (“LLC”), and a hardware queue management device to receive, store, and process inter-core data transfer requests. The hardware queue management device further comprises a resource management system to control the rate in which the cores may submit requests to reduce core stalls and dropped requests. Additionally, software instructions are introduced to optimize communication between the cores and the queue management device.

Abstract: This paper presents a proposed alternative system for queuing management that could reduce inconvenience to the public. The motivation of this system is depicted from an observation on the people queuing for services in the hospitals and the government offices without committing to the estimated time for their demand. Waiting for the service is counterproductive which consumes an unacceptable amount of productive time for the patients. We develop the system to manage the queue without physically lining up and allow people to monitor their queue status by their wireless handheld devices. The project accomplishes its objective as a tool to manage the hospital queue online where customers, patients and stakeholder can access theirs queues remotely over the Internet through a web application. The results benefit to both stakeholder to manage their time for other desire activities and hospitals in utilizing its spacious area for other business proposes.