Abstract

This study uses regression analysis to evaluate long-run traffic management system performance. Three important traffic management systems in the Twin Cities metro area - Ramp Metering, Variable Message Signs (VMS), and Freeway Service Patrol (the Highway Helper Program) were evaluated with multiple regression models to predict link speed and incident rate. We find that ramp meters increase freeway link speed and reduce incident rate. Freeway Service Patrols increase link speed when incidents are present. The results for variable message signs are ambiguous. Document type: Part of book or chapter of book

Abstract

Traffic engineering tools are applied to design a set of paths, e.g., using MPLS, in the network in order to achieve global network utilization. Usually, paths are guaranteed long-term traffic rates, while the short-term rates of bursty traffic are not guaranteed. The resource allocation scheme, suggested in this paper, handles bursts based on maximal traffic volume allocation (termed TVAfB) instead of a single maximal or sustained rate allocation. This translates to better SLAs to the network customers, namely SLAs with higher traffic peaks, that guarantees burst non-dropping. Given a set of paths and bandwidth allocation along them, the suggested algorithm finds a special collection of bottleneck links, which we term the first cut, as the optimal buffering location for bursts. In these locations, the buffers act as an additional resource to improve the network short-term behavior, allowing traffic to take advantage of the under-used resources at the links that precede and follow the bottleneck links. The algorithm was implemented in MATLAB. The resulted provisioning parameters were simulated using NS-2 to demonstrate the effectiveness of the proposed scheme. Document type: Part of book or chapter of book

Abstract

International audience Due to the varying and dynamic characteristics of network traffic, the analysis of traffic flows is of paramount importance for net- work security, accounting and traffic engineering. The problem of ex- tracting knowledge from the traffic flows is known as the heavy-hitter issue. In this context, the main challenge consists in mining the traffic flows with high accuracy and limited memory consumption. In the aim of improving the accuracy of heavy-hitters identification while having a reasonable memory usage, we introduce a novel algorithm called ACL- Stream. The latter mines the approximate closed frequent patterns over a stream of packets. Carried out experiments showed that our proposed algorithm presents better performances compared to those of the pioneer known algorithms for heavy-hitters extraction over real network traffic traces. Document type: Part of book or chapter of book

Abstract

A TCP flow is congestion responsive because it reduces its send window upon the appearance of congestion. An aggregate of nonpersistent TCP flows, however, may not be congestion responsive, depending on whether the flow (or session) arrival process reacts to congestion or not. In this paper, we describe a methodology for the passive estimation of traffic congestion responsiveness. The methodology aims to classify every TCP session as either "open-loop" or "closed-loop". In the closed-loop model, the arrival of a session depends on the completion of the previous session from the same user. When the network is congested, the arrival of a new session from that user is delayed. On the other hand, in the openloop model, TCP sessions arrive independently of previous sessions from the same user. The aggregate traffic that the open-loop model generates is not congestion responsive, despite the fact that each individual flow in the aggregate is congestion responsive. Our measurements at a dozen of access and core links show that more than 60-80% of the traffic that we could analyze (mostly HTTP traffic) follows the closed-loop model. Document type: Part of book or chapter of book

Abstract

When non-recurrent road traffic congestion happens, the operator of the traffic control centre has to select the most appropriate traffic control measure or combination of measures in a short time to manage the traffic network. This is a complex task, which requires expert knowledge, much experience and fast reaction. There are a large number of factors related to a traffic state as well as a large number of possible control measures that need to be considered during the decision making process. The identification of suitable control measures for a given non-recurrent traffic congestion can be tough even for experienced operators. Therefore, simulation models are used in many cases. However, simulating different traffic scenarios for a number of control measures in a complicated situation is very time-consuming. In this paper we propose an intelligent traffic control decision support system (ITC-DSS) to assist the human operator of the traffic control centre to manage online the current traffic state. The proposed system combines three soft-computing approaches, namely fuzzy logic, neural network, and genetic algorithm. These approaches form a fuzzy-neural network tool with self-organization algorithm for initializing the membership functions, a GA algorithm for identifying fuzzy rules, and the back-propagation neural network algorithm for fine tuning the system parameters. The proposed system has been tested for a case-study of a small section of the ring-road around Riyadh city. The results obtained for the case study are promising and show that the proposed approach can provide an effective support for online traffic control. Document type: Part of book or chapter of book

Abstract

International audience; The annual number of flights in Western Europe has increased from about 2.6 million in 1982 to about 4.5 million in 1992, an increase of 73%. Acute congestion of the Air Traffic Control system has been the result. One way to reduce this congestion is to modify the flight plans (slot of departure and route) in order to adapt the demand to the available capacity. This paper addresses the general time-route assignment problem. A state of the art of the existing methods shows that this problem is usually partially treated and the whole problem remains unsolved due to the complexity induced. We perform our research on the application of stochastic methods on real traffic data, and without using the flow network concept, but by simulating the flight of each aircraft. The first results shows that our Genetic Algorithms based method is able to reduce congestion of the french airspace by a factor 2. Special coding techniques and operators are used to improve the quality of the genetic search. Document type: Part of book or chapter of book

Abstract

In this paper we present an intelligent multi-topology IGP (MT-IGP) based intra-domain traffic engineering (TE) scheme that is able to handle unexpected traffic fluctuations with near-optimal network performance. First of all, the network is dimensioned through offline link weight optimization using Multi-Topology IGPs for achieving maximum path diversity across multiple routing topologies. Based on this optimized MT-IGP configuration, an adaptive traffic engineering algorithm performs dynamic traffic splitting adjustment for balancing the load across multiple routing topologies in reaction to the monitored traffic dynamics. Such an approach is able to efficiently minimize the occurrence of network congestion without the necessity of frequently changing IGP link weights that may cause transient forwarding loops and routing instability. Our experiments based on real network topologies and traffic matrices show that our approach has a high chance of achieving near-optimal network performance with only a small number of routing topologies. Document type: Part of book or chapter of book

Abstract

Part 3: Resource Allocation; International audience; There has long been a need for a robust and reliable system which distributes traffic across multiple paths. In particular such a system must rarely reorder packets, must not require per-flow state, must cope with different paths having different bandwidths and must be self-tuning in a variety of network contexts. PREFLEX, proposed herein, uses estimates of loss rate to balance congestion. This paper describes a method of automatically adjusting how PREFLEX will split traffic in order to balance loss across multiple paths in a variety of network conditions.Equations are derived for the automatic tuning of the time scale and traffic split at a decision point. The algorithms described allow the load balancer to self-tune to network conditions. The calculations are simple and do not place a large burden on a router which would implement the algorithm. The algorithm is evaluated by simulation using ns-3 and is shown to perform well under a variety of circumstances. The resulting adaptive, end-to-end traffic balancing architecture provides the necessary framework to meet the increasing demands of users while simultaneously offering edge networks more fine-grained control at far shorter timescales. Document type: Part of book or chapter of book

Abstract

The transformation of the Internet into an important and ubiquitous commercial infrastructure has not only created rapidly rising bandwidth demands but also significantly changed consumer expectations in terms of performance, security and services. Consequentially as service providers attempt to encourage business and leisure applications on to the Internet, there has been a requirement for them to develop an improved IP network infrastructure in terms of reliability and performance [1]. Interest in congestion control through traffic engineering has arisen from the knowledge that although sensible provisioning of the network infrastructure is needed together with sufficient underlying capacity, these are not sufficient to deliver the QoS required [2]. This is due to dynamic variations in load. In operational IP networks, it has been difficult to incorporate effective traffic engineering due to the limited capabilities of the IP technology. In principle, Multiprotocol Label Switching (MPLS), a connection-oriented label swapping technology, offers new possibilities in addressing the limitations by allowing the operator to use sophisticated traffic control mechanisms.\r \r However, as yet, the traffic engineering capabilities offered by MPLS have not been fully exploited. Once label switched paths (LSPs) have been provisioned through the service providers' network, there are currently no management facilities for dynamic re-optimisation of traffic flows. The service level agreements (SLAs) between the network operator and the customer are agreed in advance of the commencement of traffic flow, and these are mapped to particular paths throughout the provider's domain and may be maintained for the duration of the contract. During transient periods, the efficiency of resource allocation could be increased by routing traffic away from congested resources to relatively under-utilised links. Some means of restoring the LSPs to their original routes once the transient congestion has subsided is also desirable. Document type: Part of book or chapter of book

Abstract

Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of congestion, can turn even the biggest highways into a parking lot. Several congestion mitigation strategies are being studied, many focusing on micro-simulation of traffic to determine how modifying road structures will affect the flow of traffic and the networking perspective of vehicle-to-vehicle communication. Vehicle routing on a network of roads and intersections can be modeled as a distributed constraint optimization problem and solved using a range of centralized to decentralized techniques. In this paper, we present a constraint optimization model of a traffic routing problem. We produce congestion data using a sinusoidal wave pattern and vary its amplitude (saturation) and frequency (vehicle waves through a given intersection). Through empirical evaluation, we show how a centralized and decentralized solution each react to unknown congestion information that occurs after the initial route planning period. Document type: Part of book or chapter of book