Physical Queue Research Articles

Scheduling Time-Critical Traffic With Virtual Queues in Software-Defined Time-Sensitive Networking

The emerging applications in vertical industries generate diverse time-critical traffic flows with bounded delay requirements. Time-Sensitive Networking (TSN) enhances the traditional Ethernet by using Time-Aware Shaper (TAS), providing delay guarantees for traffic flow transmission. However, the fixed scheduling granularity of physical queues in TAS can bring an obstacle for the flow isolation in per-flow scheduling, such as the complex computing and configuration. This paper proposes a method of Virtual Queues-based Time-Aware Traffic Scheduling (VQ-TATS) in Software-Defined Time-Sensitive Networking (SD-TSN). SD-TSN is a networking architecture that integrates the determinism guarantees of TSN and flexible network resource allocation of Software-Defined Networking (SDN). Through the capability of SD-TSN, the physical queues resource is virtualized for VQ-TATS. VQ-TATS includes the VQ clustering and VQ mapping stages. VQ clustering aggerates virtual queues to adapt to the scheduling granularity of TAS. VQ mapping builds the relationship between virtual and physical queues and generates the gate control list of TAS. The clustering and mapping algorithms are also designed to perform VQ-TATS. The evaluation in an industrial control use case shows the effectiveness of the proposed method in schedulability and runtime.

Evaluasi Kepuasan Pengguna Aplikasi Kai Access Menggunakan Model End User Computing Satisfaction (EUCS)

In the rapidly advancing era of globalization, technology plays a pivotal role in various facets of life, offering manifold benefits. Serving as a vital component in daily tasks and responsibilities, technology has become indispensable. PT. Kereta Api Indonesia has harnessed technological advancements through the KAI Access application, providing customers the convenience of booking train tickets and accessing railway services without the need for physical queues. Despite these advantages, the KAI Access application has garnered low ratings on the Play Store. To enhance user experience and align it with expectations, it is imperative to gauge user satisfaction. This thesis seeks to ascertain the satisfaction level of KAI Access application users by employing Doll & Turkzadeh's End User Computing Satisfaction (EUCS) model, incorporating variables such as Content, Accuracy, Format, Ease of Use, and Timeliness. A sample comprising 400 respondents, specifically those who have previously utilized the KAI Access application, underwent SEM-PLS evaluation utilizing SmartPLS software. The assessment revealed that Content, Format, and Timeliness exert a significant influence on user satisfaction, whereas Accuracy and Ease of Use lack a substantial impact.

Multiclass dynamic system optimum solution for mixed traffic of human-driven and automated vehicles considering physical queues

Dynamic traffic assignment (DTA) is an important method in the long term transportation planning and management processes. However, in most existing system optimum dynamic traffic assignment (SO-DTA), no side constraints are used to describe the dynamic link capacities in a network which is shared by multiple vehicle types. Our motivation is based on the possibility for dynamic system optimum (DSO) to have multiple solutions, which differ in where queues are formed and dissipated in the network. To this end, this paper proposes a novel DSO formulation for the multi-class DTA problem containing both human driven and automated vehicles in single origin-destination networks. The proposed method uses the concept of link based approach to develop a multi-class DTA model that equally distributes the total physical queues over the links while considering explicitly the variations in capacity and backward wave speeds due to class proportions. In the model, the DSO is formulated as an optimization problem considering linear vehicle composition constraints representing the dynamics of the link capacities. Numerical examples are set up to provide some insights into the effects of automated vehicles on the queue distribution as well as the total system travel times.

How Observed Queue Length and Service Times Drive Queue Behavior in the Lab

Join and renege decisions from a single server, observable, first come first served queue are studied via controlled laboratory experiments. The role observed queue length and encountered service time experience plays on these decisions is explored. Reneging behavior by customers influences the performance of many service systems where waiting occurs. An understanding of the drivers of renege behavior is essential to queue design endeavors. Analysis of experiment data shows that, controlling for the total waiting time, the survival time in a queue is affected by the physical queue length as well as experienced service times. Not all subjects are affected by the physical queue length in the same way. Furthermore, this effect is partly mitigated when additional information on waiting time is provided. The experiment design that enables a comparison to a deterministic service time benchmark allows to separate the average pace (speed) set by the expected service time from a relative pace capturing the difference between realized service times and expectations. A fast relative pace is found to have a significant effect on patience which can be reduced by creating a setting that diminishes the motivation for in-queue observation.

Steady-state link travel time methods: Formulation, derivation, classification, and unification

Travel times are one of the most important outputs of transport planning models, especially in a strategic context. It is therefore paramount that the methods that underpin the construction of travel times are well understood. A plethora of methods exists to extract and/or construct travel times given some underlying network loading procedure, also known as the traffic flow propagation model. However, the relation between these different travel time methods and the consistency between such methods has received relatively little attention in the literature. This might in part be due to the many different traffic flow propagation models in existence, ranging from vehicle based (microscopic), to flow based (macroscopic), and models that explicitly account for the time varying nature of traffic flows (dynamic) to models that do not (static). In this work, we limit ourselves to flow based, i.e. macroscopic, traffic flow models. Within this modelling paradigm we consider dynamic, semi-dynamic, and static traffic flow propagation formulations used to construct link travel times. The semi-dynamic and static approaches are considered as more aggregate versions of the dynamic formulation. Within this context we formulate a unified (link) travel time formulation that is consistent across these three modelling paradigms under the assumption of steady-state flow conditions. The dynamic link travel time formulation is based on a recent state-of-the-art continuous time macroscopic dynamic network loading model. In the dynamic model we assume steady-state conditions to remain consistent with steady-state semi-dynamic and static approaches. This allows us to derive semi-dynamic link travel time formulations from our dynamic model, while the static formulation is derived from its semi-dynamic counterpart. Throughout this work we explore link travel times from three different perspectives; an experienced perspective, which actively tracks the tail of a physical queue, and two functional perspectives, both of which do not require explicit queue tracking. Based on the existing literature and proposed formulations, a classification framework is proposed allowing one to compare existing (and future) methods in the literature in an objective fashion. We provide a number of explicit derivations of existing model formulations that can be considered special cases of our unified approach. A numerical example across the different perspectives is included and a significant number of representative existing methods in the literature has been classified based on our proposed framework for the reader's convenience.

Computing Dynamic User Equilibria on Large-Scale Networks with Software Implementation

Dynamic user equilibrium (DUE) is the most widely studied form of dynamic traffic assignment (DTA), in which road travelers engage in a non-cooperative Nash-like game with departure time and route choices. DUE models describe and predict the time-varying traffic flows on a network consistent with traffic flow theory and travel behavior. This paper documents theoretical and numerical advances in synthesizing traffic flow theory and DUE modeling, by presenting a holistic computational theory of DUE, which is numerically implemented in a MATLAB package. In particular, the dynamic network loading (DNL) sub-problem is formulated as a system of differential algebraic equations based on the Lighthill-Whitham-Richards fluid dynamic model, which captures the formation, propagation and dissipation of physical queues as well as vehicle spillback on networks. Then, the fixed-point algorithm is employed to solve the DUE problems with simultaneous route and departure time choices on several large-scale networks. We make openly available the MATLAB package, which can be used to solve DUE problems on user-defined networks, aiming to not only facilitate benchmarking a wide range of DUE algorithms and solutions, but also offer researchers a platform to further develop their own models and applications. The MATLAB package and computational examples are available at https://github.com/DrKeHan/DTA.

Reward maximization in general dynamic matching systems

We consider a matching system with random arrivals of items of different types. The items wait in queues—one per item type—until they are “matched.” Each matching requires certain quantities of items of different types; after a matching is activated, the associated items leave the system. There exists a finite set of possible matchings, each producing a certain amount of “reward.” This model has a broad range of important applications, including assemble-to-order systems, Internet advertising, and matching web portals. We propose an optimal matching scheme in the sense that it asymptotically maximizes the long-term average matching reward, while keeping the queues stable. The scheme makes matching decisions in a specially constructed virtual system, which in turn controls decisions in the physical system. The key feature of the virtual system is that, unlike the physical one, it allows the queues to become negative. The matchings in the virtual system are controlled by an extended version of the greedy primal–dual (GPD) algorithm, which we prove to be asymptotically optimal—this in turn implies the asymptotic optimality of the entire scheme. The scheme is real time; at any time, it uses simple rules based on the current state of the virtual and physical queues. It is very robust in that it does not require any knowledge of the item arrival rates and automatically adapts to changing rates. The extended GPD algorithm and its asymptotic optimality apply to a quite general queueing network framework, not limited to matching problems, and therefore are of independent interest.

Dynamic traffic assignment in degradable networks: paradoxes and formulations with stochastic link transmission model

ABSTRACTThis paper proposes a simultaneous route and departure time choice (SRDTC) problem with fixed demand in a degradable transport network. In this network, travelers face with stochastic travel times. Their selection of routes and departure times follows the UE principle in terms of the mean generalized route cost, which is defined as the probabilistic dynamic user optimal (PDUO) principle. The proposed PDUO-SRDTC problem is formulated as a variational inequality (VI) problem. As a special case of PDUO-SRDTC problem, the PDUO route choice (PDUO-RC) problem is also proposed and formulated as a VI problem. Network degradation is defined on the degradation of the outflow capacity of each link. A Monte Carlo-based stochastic link transmission model (MC-SLTM) is developed to capture the effect of physical queues and the random evolution of traffic states during flow propagation to estimate mean generalized route costs. Both the extragradient algorithm and the route-swapping method with a variable sample size scheme are developed to solve the proposed VI problems. Numerical examples are developed to illustrate the paradoxical phenomena of the problems and the effectiveness of the solution methods. Numerical results show that constructing a new road, enhancing link outflow capacity, or reducing outflow capacity degradation can lead to poor network performance and it is important to consider both network degradation and queue spillback when making transportation policies aimed at improving network performance. The results also demonstrate that the variable sample size scheme can give a quicker and better solution than the traditional fixed sample size scheme.

Waves in a Spatial Queue

Envisaging a physical queue of humans, we model a long queue by a continuous-space model in which, when a customer moves forward, they stop a random distance behind the previous customer, but do not move at all if their distance behind the previous customer is below a threshold. The latter assumption leads to “waves” of motion in which only some random number W of customers move. We prove that ℙ(W > k) decreases as order k− 1/2; in other words, for large k the k’th customer moves on average only once every order k1/2 service times. A more refined analysis relies on a non-obvious asymptotic relation to the coalescing Brownian motion process; we give a careful outline of such an analysis without attending to all the technical details.

Multi-class dynamic network traffic flow propagation model with physical queues

Multi-class dynamic network traffic flow propagation model with physical queues

PHYSICAL AND MATHEMATICAL QUEUES IN THE APPLIED QUEUING THEORY

The problem of various types of queues arising in queuing systems is considered in the paper. The concept of a physical queue is introduced; universal mathematical formulas of the first and second moments of main discrete and continuous random variables characterizing behavior of physical queues for various models of mixed type queuing systems are obtained.

Multi-class dynamic traffic assignment with physical queues: intersection-movement-based formulation and paradox

ABSTRACTThis paper proposes an intersection-movement-based variational inequality formulation for the multi-class dynamic traffic assignment (DTA) problem involving physical queues using the concept of approach proportion. An extragradient method that requires only pseudomonotonicity and Lipschitz continuity for convergence is developed to solve the problem. We also present a car–truck interaction paradox, which states that allowing trucks to travel or increasing the truck flow in a network can improve network performance for cars in terms of the total car travel time. Numerical examples are set up to illustrate the importance of considering multiple vehicle types and their interactions in a DTA model, the effects of various parameters on the occurrence of the paradox, and the performance of the solution algorithm.

Virtual queue dropping for robust real-time video over IEEE 802.11aa wireless LANs

Stream classification service (SCS) is a novel concept proposed in the newly released IEEE 802.11aa standard for robust audio and video streaming, particularly for graceful degradation of streaming quality during network congestions. Based on intra-access category prioritisation (IACP), SCS is equipped with a pair of access category (AC) queues to differentiate real-time and non-real-time video streams, namely (AC_VI, AAC_VI), and thus introduces the need for an efficient scheduler design; similarly for audio. In this study, we propose a novel cross-layer design called virtual queue dropping (VQD) for packet scheduling between AC_VI and AAC_VI. Driven by a real-time video-packet-importance scheme, VQD adopts conditional priority weighting to enhance the priority of I-packets from AAC_VI so that they can fairly compete with P-packets from AC_VI. Moreover, to achieve graceful degradation during network congestions, VQD (i.e. based on priority coupling among different component queue lengths within the same physical AC queue) is adopted so that the dropping probabilities of lower-priority video packets are not only larger but also affected-and-increased by those of higher-priority ones. Different limits of priority retires of I- and P-packets can avoid unexpected long delays, and an optimal set of retry limits has been found to minimise the performance impact due to real-time constraints. Our results show that VQD outperforms PWD and SCS-CR in various performance metrics, and achieves a win-win game for the dilemma in maintaining priority for AC_VI and fairness for AAC_VI simultaneously.

A cell-based multiple vehicle type dynamic user equilibrium model with physical queues

This paper proposes a cell-based multiple vehicle type dynamic user equilibrium model with physical queues. A single-type traffic flow model is extended to a general case with multiple vehicle types that can be partly solved by the time-space discretization method. Then, a network version of the multiple vehicle type cell transmission model is given. An integrated variational inequality (VI) formulation is presented to capture the complex traveler choice behaviors such as route and departure time choices. Furthermore, a genetic algorithm with a flow-swapping method is adopted to solve the VI problem. Two examples are used to evaluate the properties of this formulation. The results show that the model can reflect dynamic phenomena, such as multiple vehicle type speed consistent under congested conditions, queue formation and dissipation and so on. Moreover, the solutions can approximately follow the multiple vehicle type dynamic route and departure time user equilibrium conditions.

Comparisons of Perceptions and Behavior in Ticket Queues and Physical Queues

Ticket queues are systems that issue tickets to customers upon their arrival. Although ticket queues are preferred by many service providers, there is limited research on ticket queues, especially on customer perceptions of, preferences for, and behavior in these systems. We conducted a series of surveys to understand customer preferences and patience in a ticket queue and a physical queue (stand-in-line system) and to investigate whether the assumptions used in analytical queuing models for customer abandonment behavior are realistic. Study results indicate that subjects generally prefer ticket queues over physical queues and have greater patience in ticket queues than they do in physical queues. In addition, we observe that subjects are willing to wait longer than they initially were, assuming that they already have spent some time waiting in line. Using the survey results, we ran a series of simulation models by adjusting the traditional queuing assumptions and showed the impact of customer behavior on system performance measures in ticket and physical queues. Our results can assist managers, in determining the type of queue to implement under various service settings, and researchers, in modeling more realistic queuing systems.

An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance

Different from traditional methods, this paper formulates the logit-based stochastic dynamic user optimal (SDUO) route choice problem as a fixed point (FP) problem in terms of intersection movement choice probabilities, which contain travelers’ route information so that the realistic effects of physical queues can be captured in the formulation when a physical-queue traffic flow model is adopted, and that route enumeration and column generation heuristics can be avoided in the solution procedure when efficient path sets are used. The choice probability can be either destination specific or origin–destination specific, resulting into two formulations. To capture the effect of physical queues in these FP formulations, the link transmission model is modified for the network loading and travel time determination. The self-regulated averaging method (SRAM) was adopted to solve the FP formulations. Numerical examples were developed to illustrate the properties of the problem and the effectiveness of the solution method. The proposed models were further used to evaluate the effect of information quality and road network improvement on the network performance in terms of total system travel time (TSTT) and the cost of total vehicle emissions (CTVE). Numerical results show that providing better information quality, enhancing link outflow capacity, or constructing a new road can lead to poor network performance.

Lifetime Enrichment of Wireless Sensor Networks using DEMN Algorithm

Wireless Sensor networks are mainly used for sensing the parameters such as, temperature, dampness, demands, blustery weather direction and pace, illumination concentration, tremor intensity, noise power, power-line electrical energy, chemical attention, impurity levels and essential body functions. WSN has limited battery size. Lifetime enrichment is a significant one, because replacement of batteries is not possible in WSN. These works concentrate on techniques which are used to increase the lifetime of Wireless Sensor Networks (WSN). Many factors are taken into account for this enrichment of life time of wireless sensor networks, such as minimizing the power consumption, low cost operation, optimal routing algorithms. This work proposes an algorithm namely DEMN, which enriches the lifetime of WSN. By using DEMN algorithm, the physical queue is created and the results of real traffic volume are defined. The simulation result shows that the comparison of Distributed algorithm and DEMN algorithm.

Submission to the DTA2012 Special Issue: A Case for Higher-Order Traffic Flow Models in DTA

An accurate Dynamic Traffic Assignment (DTA) model should capture real world traffic flow dynamics and predict ‘dynamic’ travel times. Traditional DTA models used simple traffic flow functions such as exit flow functions, delay functions, point queues, and deterministic physical queue models. Recently, simulation based models apply well accepted traffic flow theoretic models to simulate traffic flow. However, a significant number of papers over the last decade have adopted an approximation of LWR traffic flow model, the cell transmission model, for simulating traffic flow in a DTA model. This paper compares three models, namely, LWR, Payne and Aw-Rascle, models, for their suitability to be embedded in a DTA model. Model calibration and flow simulation is performed separately using two different speed–density relationships. Results showed the importance of choice of speed-density relationship in traffic flow simulation. Models were used to simulate traffic state at different discretization levels and it was observed that as discretization becomes finer, the models' accuracy increases. Finally, the models were applied to a two node, two link network to analyze their performance in a DTA framework. The higher-order models captured congestion dissipation better than LWR model which consistently underestimates congestion and travel time.

Stackelberg Routing on Parallel Networks With Horizontal Queues

This paper presents a game theoretic framework for studying Stackelberg routing games on parallel networks with horizontal queues, such as transportation networks. First, we introduce a new class of latency functions that models congestion due to the formation of physical queues. For this new class, some results from the classical congestion games literature (in which latency is assumed to be a non-decreasing function of the flow) do not hold. In particular, we find that there may exist multiple Nash equilibria that have different total costs. We provide a simple polynomial-time algorithm for computing the best Nash equilibrium, i.e., the one which achieves minimal total cost. Then we study the Stackelberg routing game: assuming a central authority has control over a fraction of the flow on the network (compliant flow), and that the remaining flow (non-compliant) responds selfishly, what is the best way to route the compliant flow in order to minimize the total cost? We propose a simple Stackelberg strategy, the Non-Compliant First (NCF) strategy, that can be computed in polynomial time. We show that it is optimal for this new class of latency on parallel networks. This work is applied to modeling and simulating congestion relief on transportation networks, in which a coordinator (traffic management agency) can choose to route a fraction of compliant drivers, while the rest of the drivers choose their routes selfishly.

A Model for Continuous Dynamic Network Loading Problem with Different Overtaking Class Users

This article presents a model for solving the continuous loading network problem when different class users interact in the traffic network so that overtaking among different class users is permitted but the FIFO rule is satisfied for the same class users. The model calculates the link travel time functions at a basic finite set of equally spaced times, which are used to interpolate a monotone spline for all other times in order to preserve monotonicity and guarantee that the FIFO rule is satisfied at all points for the same class users. The model assumes nonlinear link travel time functions of the link volumes including those ahead of the link a being considered, takes into account that different class functions must be asymptotically coincident for high congestions, and considers link physical queues. The path origin demands are reproduced as linear combinations of density functions and the conservation laws are used to determine the path flow wave evolution throughout the network. Different path flow waves are mixed together and a congestion equation is used to determine the link travel times. Finally, all information is combined to make it compatible in times and locations using an iterative method until convergence. The method is illustrated by some examples of illustrative and real networks. The results seem to reproduce the observed trends closely. The resulting required CPU times are reasonable so that the method seems to be applicable to real networks.