Congestion Model Research Articles

Analytical modelling of congestion for 6LoWPAN networks

The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT ‘things’. In 6LoWPAN networks, heavy network traffic causes congestion which significantly affects the overall performance and the quality of service metrics. In this paper, a new analytical model of congestion for 6LoWPAN networks is proposed using Markov chain and queuing theory. The derived model calculates the buffer loss probability and the channel loss probability as well as the number of received packets at the final destination in the presence of congestion. Also, we calculate the actual wireless channel capacity of IEEE 802.15.4 with and without collisions based on Contiki OS implementation. The validation of the proposed model is performed with different scenarios through simulation by using Contiki OS and Cooja simulator. Simulation results show that the analytical modelling of congestion has an accurate agreement with simulation.

Stochastic Model of Ships Traffic Capacity and Congestion — Validation by Real Ships Traffic Data on Świnoujście — Szczecin Waterway

AbstractPaper presents validation of previously created stochastic ships traffic stream model by the real data of ships delays on Świnoujście — Szczecin waterway. The model is mostly based on Monte Carlo methodology. The model is microscopic which means that each ship’s model is treated as separate object possessing given attributes. As the main parameter of presented validation total waiting (delay) time of ships have been applied. The time of ships delays was possessed from Szczecin VTS centre and compared with the model output.

Vickrey Meets Alonso: Commute Scheduling and Congestion in a Monocentric City

This paper studies the interaction between dynamic traffic congestion and urban spatial equilibrium, using a model that is a straight unification of the Vickrey (1969) bottleneck congestion model and the Alonso (1964) monocentric city model. In a monocentric city with a bottleneck at the entrance to the CBD, residents choose their commute departure time jointly with residential location and housing consumption. Commuters arrive at the bottleneck in sequence sorted by residential location, so that more distant residents arrive later. The socially optimal toll makes central residents commute earlier in the morning than they would without the toll, which in turn induces a city that is less dense in the center and more dense further out. This is the opposite effect of what is found in models with static congestion.

Assessment of renal perfusion impairment in a rat model of acute renal congestion using contrast-enhanced ultrasonography

Renal congestion is caused by elevated central venous pressure (CVP), and decreases glomerular filtration in patients with congestive heart failure. Since real-time contrast-enhanced ultrasonography (CEUS) using microbubble-based contrast agents can visualize the perfused microvascular bed, we sought to evaluate the impairment of renal perfusion during acute renal congestion with CEUS. In Wister rats, CEUS of kidney was performed with the direct monitoring of CVP and intra-renal pressure (IRP). When CVP was elevated to 10 and 15mmHg after the bolus injection of normal saline via the femoral vein, peak intensity (PI, dB) and time to PI (TTP) in the renal cortex and medulla were compared with control rats. There was a strong correlation between IRP and CVP (r=0.95, p<0.0001). In the congestion model, more time was required for enhancement of the parenchyma, especially in the medulla compared to control; TTP of the medulla and cortex at 15mmHg CVP (CVP15) was significantly prolonged compared with controls (medulla, 4351±98 vs. 1415±267ms, p=0.003; cortex, 3219±106 vs. 1335±264ms, p=0.005). In addition, medullary PI at CVP15 decreased, but not significantly, compared to those of controls and at 10mmHg CVP (20.1±0.9, 22.8±1.6, 21.6±0.2dB). In contrast, cortical PIs at CVP15 were significantly lower than that of control (24.6±1.0 vs. 31.4±1.0dB, p=0.007). CEUS revealed that impaired renal parenchymal flow in an acute congestion model is accompanied with increased renal interstitial pressure.

Congestion v Content Provision in Net Neutrality: The Case of Amazon's Twitch.tv

This paper studies the efficient use of prioritization in Amazon’s Twitch.tv, taking into account the trade-off between entry and congestion. I specify and estimate supply and demand models for live video, and a congestion model. Using technological shocks, I identify congestion costs for content providers and their consumers. Using shocks in prioritization, I identify its benefits. With estimated preferences and technological parameters, I construct counterfactuals. Without congestion, demand potentially doubles. A supply-side Pigouvian tax is preferred to a demand-side one. Without prioritization, consumer welfare drops up to 10%. I consider a rent-extractive platform, and discuss parallels with net-neutrality policy.

Congestion-aware route selection in automatic evacuation guiding based on cooperation between evacuees and their mobile nodes

When a large-scale disaster occurs, evacuees have to evacuate to safe places quickly. For this purpose, an automatic evacuation guiding scheme based on cooperation between evacuees and their mobile nodes has been proposed. The previous work adopts shortest-distance based route selection and does not consider the impact of traffic congestion caused by evacuation guiding. In this paper, we propose congestion-aware route selection in the automatic evacuation guiding. We first adopt a traffic congestion model where each evacuee’s moving speed on a road is determined by the population density of the road and his/her order among evacuees traveling in the same direction. Based on this congestion model, each evacuee’s mobile node estimates the cost, i.e., traveling time, of each road in the area. Each mobile node collects information about blocked road segments and positions of other evacuees through communication infrastructures or other mobile nodes. Based on the obtained information, it calculates and selects the smallest-cost route. Through simulation experiments, we show that the congestion-aware route selection can reduce both average and maximum evacuation times compared to the shortest-distance-based route selection, especially under highly congested situations. Furthermore, we show that the congestion-aware route selection can work well even under highly damaged situations where only direct wireless communication among mobile nodes is available.

Effect model of urban traffic congestion on driver’s lane-changing behavior

Road traffic congestion has become a normal state and caused many problems in large cities of China, and lane-changing model has attracted increased attention in recent years. This study is aimed t...

Dynamic equilibrium at a congestible facility under market power

This paper studies equilibrium and optimum at a congested facility when firms have market power; e.g., when a few airlines jointly use a congested airport. Unlike most of the previous literature, we characterize the equilibrium in terms of timing of arrivals in a continuous-time congestion model when firms simultaneously schedule services. Using the Henderson-Chu dynamic model of flow congestion in a multiple-firm setting, we find that a stable and unique Nash equilibrium in pure strategies always exists. Importantly, it also exists in cases where it fails to exist under bottleneck congestion (notably when the value of schedule late exceeds the value of travel delays). We find that symmetric firms schedule arrivals inefficiently, and strongly concentrated around the desired arrival time so that the peak is shorter and delays are higher than socially optimal. We show that when firms are asymmetric in terms of output, all firms schedule vehicles in the peak center, around the desired arrival time, with arrival windows increasing with firm size such that a smaller firm's window is always fully contained in a larger firm's window and only the largest firm operates in the early and late shoulders. Furthermore, for any pair of asymmetric firms, the larger firm has a higher instantaneous arrival rate at any moment where both firms schedule arrivals. Our results also show that even though self-internalization can be substantial, there is scope for decentralizing the first-best outcome through time-varying tolls.

P6186Quantitative computer tomographic derived measurements of extravascular lung water and left ventricular filling pressure in a porcine model of pulmonary congestion

P6186Quantitative computer tomographic derived measurements of extravascular lung water and left ventricular filling pressure in a porcine model of pulmonary congestion

Modeling the dynamics of congestion in large urban networks using the macroscopic fundamental diagram: User equilibrium, system optimum, and pricing strategies

The macroscopic fundamental diagram (MFD) is introduced in recent studies to present the relationship between the flow and the density of the network in large urban regions (neighborhoods). The MFD can be also rescaled to approximate network outflow as a function of the vehicular accumulation of the system in the morning commute problem. In this research, we develop a bathtub model (macro-scale traffic congestion model) by combining Vickrey's (1969) model of dynamic congestion with the MFD to formulate the user equilibrium over the peak as an ordinary differential equation (ODE). This problem can be solved numerically to estimate the exact solution of the morning commute problem. Alternatively, the morning commute problem can be solved analytically by approximating the solution of the ODE using a well-behaved function. Here, we present a quadratic and also a linear approximation of the equilibrium solution for a semi-quadratic MFD, considering that the declining part of the MFD is shown to be well estimated by a quadratic function. To optimize the system, we present pricing strategies for network users (dynamic tolling) and employers inside the region (dynamic taxing) that can minimize the generalized cost of the system by keeping the outflow maximized over the peak. Finally, we compare the exact and the approximate solutions of the problem, and also the proposed pricing strategies of the region in a numerical example.

Distributed construction of purely additive spanners

This paper studies the complexity of distributed construction of purely additive spanners in the CONGEST model. We describe algorithms for building such spanners in several cases. Because of the need to simultaneously make decisions at far apart locations, the algorithms use additional mechanisms compared to their sequential counterparts. We complement our algorithms with a lower bound on the number of rounds required for computing pairwise spanners. The standard reductions from set-disjointness and equality seem unsuitable for this task because no specific edge needs to be removed from the graph. Instead, to obtain our lower bound, we define a new communication complexity problem that reduces to computing a sparse spanner, and prove a lower bound on its communication complexity. This technique significantly extends the current toolbox used for obtaining lower bounds for the CONGEST model, and we believe it may find additional applications.

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

A general framework for modeling shared autonomous vehicles with dynamic network-loading and dynamic ride-sharing application

Shared autonomous vehicles (SAVs) could provide low-cost service to travelers and possibly replace the need for personal vehicles. Previous studies found that each SAV could service multiple travelers, but many used unrealistic congestion models, networks, and/or travel demands. The purpose of this paper is to provide a method for future research to use realistic flow models to obtain more accurate predictions about SAV benefits. This paper presents an event-based framework for implementing SAV behavior in existing traffic simulation models. We demonstrate this framework in a cell transmission model-based dynamic network loading simulator. We also study a heuristic approach for dynamic ride-sharing. We compared personal vehicles and SAV scenarios on the downtown Austin city network. Without dynamic ride-sharing, the additional empty repositioning trips made by SAVs increased congestion and travel times. However, dynamic ride-sharing resulted in travel times comparable to those of personal vehicles because ride-sharing reduced vehicular demand. Overall, the results show that using realistic traffic flow models greatly affects the predictions of how SAVs will affect traffic congestion and travel patterns. Future work should use a framework such as the one in this paper to integrate SAVs with established traffic flow simulators.

Scheduling for a processor sharing system with linear slowdown

We consider the problem of scheduling arrivals to a congestion system with a finite number of users having identical deterministic demand sizes. The congestion is of the processor sharing type in the sense that all users in the system at any given time are served simultaneously. However, in contrast to classical processor sharing congestion models, the processing slowdown is proportional to the number of users in the system at any time. That is, the rate of service experienced by all users is linearly decreasing with the number of users. For each user there is an ideal departure time (due date). A centralized scheduling goal is then to select arrival times so as to minimize the total penalty due to deviations from ideal times weighted with sojourn times. Each deviation is assumed quadratic, or more generally convex. But due to the dynamics of the system, the scheduling objective function is non-convex. Specifically, the system objective function is a non-smooth piecewise convex function. Nevertheless, we are able to leverage the structure of the problem to derive an algorithm that finds the global optimum in a (large but) finite number of steps, each involving the solution of a constrained convex program. Further, we put forward several heuristics. The first is the traversal of neighbouring constrained convex programming problems, that is guaranteed to reach a local minimum of the centralized problem. This is a form of a "local search", where we use the problem structure in a novel manner. The second is a one-coordinate "global search", used in coordinate pivot iteration. We then merge these two heuristics into a unified "local-global" heuristic, and numerically illustrate the effectiveness of this heuristic.

Inside the Queue: Hypercongestion and Road Pricing in a Continuous Time - Continuous Place Model of Traffic Congestion

This paper develops a continuous-time - continuous-place economic model of road traffic congestion with a bottleneck, based on car-following theory. The model integrates two archetype congestion technologies used in the economics literature: 'static flow congestion', originating in the works of Pigou, and 'dynamic bottleneck congestion', pioneered by Vickrey. Because a closed-form analytical solution of the formal model does not exist, its behaviour is explored using a simulation model. In a setting with endogenous departure time choice and with a bottleneck along the route, it is shown that 'hypercongestion' can arise as a dynamic - transitional and local - equilibrium phenomenon. Also dynamic toll schedules are explored. It is found that a toll rule based on an intuitive dynamic and space-varying generalization of the standard Pigouvian tax rule can hardly be improved upon. A naive application of a toll schedule based on Vickrey's bottleneck model, in contrast, appears to perform much worse and actually even reduces welfare in the numerical model.

Step by Step: Revisiting Step Tolling in the Bottleneck Model

In most dynamic traffic congestion models, congestion tolls must vary continuously over time to achieve the full optimum. This is also the case in Vickrey's (1969) 'bottleneck model'. To date, the closest approximations of this ideal in practice have so-called 'step tolls', in which the toll takes on different values over discrete time intervals, but is constant within each interval. Given the prevalence of step tolling schemes they have received surprisingly little attention in the literature. This paper compares two step-toll schemes that have been studied using the bottleneck model by Arnott, de Palma and Lindsey (1990) and Laih (1994). It also proposes a third scheme in which late in the rush hour drivers slow down or stop just before reaching a tolling point, and wait until the toll is lowered from one step to the next step. Such behaviour has indeed been observed in reality. Analytical derivations and numerical modelling show that the three tolling schemes have different optimal toll schedules and reduce total social costs by different percentages. These differences persist even in the limit as the number of steps approaches infinity. Braking lowers the welfare gain from tolling by 14% to 21% in the numerical example. Therefore, preventing or limiting braking seems important in designing step-toll systems.

A commuting model for the analysis of the impacts of a tramway project: application to the Lens area

ABSTRACTRoad congestion is not only an issue for major European urban agglomerations, but also for smaller ones. It is also the case of the Lens urban area, where car use is much higher than the average for medium-sized urban agglomerations in France. Local authorities put forward tramway projects to deal with the strongly negative externalities of congestion: travel time losses and pollution. To analyse its medium-term impact, we have developed a commuting with congestion model, inspired by the four-step traditional model, but with data made available from an origin–destination matrix. The results are encouraging but insufficient, and it is necessary to adopt supplementary measures in order to retrieve and justify the sizeable investments needed. Some measures prove to be very efficient, such as parking fees and urban tolls. Other measures, such as the subsidization of public transport, are partially efficient since they have an impact mainly on intra-urban commutes.

Towards a model of emergency department congestion

The purpose of this paper is to examine the flow of patients through the emergency department of a large suburban acute general hospital and the factors that influence overcrowding and congestion. The paper broadly draws on the input-process-output systems paradigm as a basis for examining emergency department patient throughput. A data set of all attendances at the emergency department of a large suburban acute general hospital during the course of a full calendar year was examined using statistical tools. The analysis found that the major influencers of length of stay were patient-related factors such as age, severity of ailment (triage category), and whether or not the patient was admitted into the main hospital. Patients admitted into the hospital had significantly longer length of stay in emergency than those who were not admitted. The main influencers of patient arrivals were temporal factors such as time of day and day of arrival. These influencing factors are formed into a tentative model of emergency department congestion.

Towards a model of emergency department congestion

The purpose of this paper is to examine the flow of patients through the emergency department of a large suburban acute general hospital and the factors that influence overcrowding and congestion. The paper broadly draws on the input-process-output systems paradigm as a basis for examining emergency department patient throughput. A dataset of all attendances at the emergency department of a large suburban acute general hospital during the course of a full calendar year was examined using statistical tools. The analysis found that the major influencers of length of stay were patient-related factors such as age, severity of ailment (triage category) and whether or not the patient was admitted into the main hospital. Patients admitted into the hospital had significantly longer length of stay in emergency than those who were not admitted. The main influencers of patient arrivals were temporal factors such as time of day and day of arrival. These influencing factors are formed into a tentative model of emergency department congestion.