A meta-model for multiobjective routing in MPLS networks

MPLS (Multiprotocol Label Switching) enables the utilisation of explicit routes and other advanced routing mechanisms in multiservice packet networks, capable of dealing with multiple and heterogeneous QoS (Quality of Service) parameters. Firstly the paper presents a discussion of conceptual and methodological issues raised by multiobjective routing optimisation models for MPLS networks. The major contribution is the proposal of a multiobjective routing optimisation framework for MPLS networks. The major features of this modelling framework are: the formulation of a three-level hierarchical routing optimisation problem including network and service performance objectives, the inclusion of fairness objectives in the different levels of optimisation and a two-level stochastic representation of the traffic in the network (traffic flow and packet stream levels). A variant of the general model for two classes of traffic flows, QoS traffic and Best Effort traffic, is also presented. Finally a stochastic teletraffic modelling approach, underlying the optimisation model, is fully described. Work partially supported by programme POSI of the III EC programme cosponsored by FEDER and national funds.     

Graceful reassignment of excessively long communications paths in networks

Modern broadband telecommunications networks transport diverse classes of traffic through flexible end-to-end communications paths. For instance, Internet Protocol (IP) networks with Multi-Protocol Label Switching (MPLS) carry traffic through label switched paths. These flexible paths are often changed in real, or near-real, time in response to congestion and failures detected in the network. As a result, over time, some of these communications paths become excessively long (referred to as out-of-kilter), leading to poor service performance and waste of network resources. An effective reassignment scheme may require reassignment of communications paths with acceptable length (referred to as in-kilter) in order to generate spare capacity on certain links for the out-of-kilter paths. A graceful reassignment solution provides an ordered sequence of reassignments that satisfies the following: (i) the total number of reassigned communications paths does not exceed a specified limit, (ii) no temporary capacity violations are incurred on any network link during the execution of the sequence of reassignments (reassignments are executed sequentially, one at a time), (iii) a communications path is reassigned only as a unit without being split among multiple alternate routes (iv) all reassigned communications paths will be in-kilter, (v) none of the reassignments of communications paths that were originally in-kilter can be excluded from the specified solution without resulting in some capacity violation, and (vi) the sequence of reassignments approximately optimizes a predefined objective, such as maximizing the number of reassigned out-of-kilter communications paths or maximizing the total load reassigned from out-of-kilter communications paths. The resulting problem is formulated as a multi-period, multi-commodity network flow problem with integer variables. We present a search heuristic that takes advantage of certain problem properties to find subsequences of reassignments that become part of the solution, without performing an exhaustive search. Each subsequence reassigns at least one out-of-kilter communication path.     

A Method for Finding the Shortest Route Through a Road Network

When a new road is being planned it is necessary to assess how much traffic will be diverted to it from various parts of the existing road network. This allocation of traffic has usually been based on a comparison of journey times or journey costs on alternative routes, and has depended on the selection, by trial and error, of the cheapest route through the network.A method is described which determines the shortest or cheapest routes between points on the network and which can readily be extended to show how traffic between the points is distributed and to assess the total cost of vehicle operation on the network.The procedure is quite systematic and independent of the manner in which journey costs are derived, and it could be carried out on an electronic computer with considerable saving in time. It can be applied to any transportation or communication problem that involves finding the most economical routes through a network.     

Car path tracking in traffic flow networks with bounded buffers at junctions

This article deals with the modeling for an individual car path through a road network, where the dynamics is driven by a coupled system of ordinary and partial differential equations. The network is characterized by bounded buffers at junctions that allow for the interpretation of roundabouts or on-ramps while the traffic dynamics is based on first-order macroscopic equations of Lighthill-Whitham-Richards (LWR) type. Trajectories for single drivers are then influenced by the surrounding traffic and can be tracked by appropriate numerical algorithms. The computational experiments show how the modeling framework can be used as navigation device.     

Day-to-day evolution of the traffic network with Advanced Traveler Information System

Since the notion of user equilibrium (UE) was proposed by Wardrop [13], it has become a cornerstone for traffic assignment analysis. But, it is not sufficient to only ask whether equilibrium exists or not; it is equally important to ask whether and how the system can achieve equilibrium. Meanwhile, stability is an important performance in the sense that if equilibrium is unsustainable, both the equilibrium and the trajectory are sensitive to disturbances, even a small perturbation will result in the system evolution away from the equilibrium point. These incentive a growing interest in day-to-day dynamics. In this paper, we develop a dynamical system with Advanced Traveler Information System (ATIS) and study the stability of the network with ATIS. A simple network is used to simulate the model, and the results show that there exist periodic attractors in the traffic network in some cases (for example, the market penetration level of ATIS is 0.25 and traffic demand is 2 unit). It is found that the logit parameter of the dynamical model and the traffic demand can also affect the stability of the traffic network. More periodic attractors appear in the system when the traffic demand is large and the low logit parameter can delay the appearance of periodic attractors. By simulation, it can be concluded that if the range of the periodic attractors’ domain of the simple network is known, the road pricing based on the range of the attraction domain is effective to alleviate the instability of the system.     

An Efficient Approach to Real-Time Traffic Routeing for Telephone Network Management

When contingencies occur in the telephone network the proper traffic control actions for rearranging the traffic flow must be promptly taken in a short period of time, otherwise, the congestion will soon spread to other parts of the network. In this paper, a multicommodity maximal flow model is proposed to formulate the problem, and an efficient approach is proposed to find the solution within a short time period. The node pairs are first sorted by the traffic demand into decreasing order and the capacity of links is allocated to the node pair with largest demand. The traffic allocation is then iteratively reallocated on those routes which share the same links to find a better solution, until that solution is obtained. The advantages of this approach are: (1) a feasible solution can be obtained within a short time period; (2) the affected traffic can be rerouted on paths with more than two links; (3) an acceptable solution can be found once the period has expired.     

结点有约束的交通网络最短路径模型

结点有约束的网络是一类特殊的网络，如具有禁止通行限制信息的交通路网等，由于最短路径的求解是有后效性的，经典的Dijkstra算法等不能直接用来求解该问题，本文提出了一种结点有约束的交通网络最短路径建模方法，该方法所建模型为一般网络模型，可用任一传统高效的算法求其最短路径，从根本上降低了问题的复杂性，为很好地解决交通、通信等领域中的此类问题提供了有益的方法。     

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.     

A network traffic flow model for motorway and urban highways

The research reported in this paper develops a network-level traffic flow model (NTFM) that is applicable for both motorways and urban roads. It forecasts the traffic flow rates, queue propagation at the junctions and travel delays through the network. NTFM uses sub-models associated with all road and junction types that comprise the highway. The flow at any one part of the network is obviously very dependent on the flows at all other parts of the network. To predict the two-way traffic flow in NTFM, an iterative simulation method is executed to generate the evolution of dependent traffic flows and queues. To demonstrate the capability of the model, it is applied to a small case study network and a local Loughborough–Nottingham highway network. The results indicate that NTFM is capable of identifying the relationship between traffic flows and capturing traffic phenomena such as queue dynamics. By introducing a reduced flow rate on links of the network, the effects of strategies used to carry out roadworks can be mimicked.     

Heavy-traffic analysis of the sojourn time in a three node Jackson network with overtaking

We consider a Jackson network consisting of three first-in-first-out (FIFO)M/M/1 queues. When customers leave the first queue they can be routed to either the second or third queue. Thus, a customer that traverses the network by going from the first to the second to the third queue, can be overtaken by another customer that is routed from the first queue directly to the third. We study the distribution of the sojourn time of a customer through the three node network, in the heavy traffic limit. A three term heavy traffic asymptotic approximation to the sojourn time density is derived. The leading term shows that the nodes decouple in the heavy traffic limit. The next two terms, however, do show the dependence of the sojourn times at the individual nodes and give quantitative measures of the effects of overtaking.     

Spatial distribution complexities of traffic congestion and bottlenecks in different network topologies

Recently, urban traffic congestion has become a popular social problem. The generation and the propagation of congestion has close relation with the network topology, the traffic flow, etc. In this study, based on the traffic flow propagation method, we investigate the time and space distribution characteristics of the traffic congestion and bottlenecks in different network topologies (e.g., small world, random and regular network). The simulation results show that the random network is an optimal traffic structure, in which the traffic congestion is smaller than others. Moreover, the regular network is the worst topology which is prone to be congested. Additionally, we also prove the effects of network with community structure on the traffic system and congestion bottlenecks including its generation, propagation and time–space complexities. Results indicate that the strong community structure can improve the network performance and is effective to resist the propagation of the traffic congestion.     

公路隧道围岩稳定性评价的改进人工神经网络方法

本文运用改进的人工神经网络方法 ,研究了公路隧道围岩稳定性的评价定级问题 .首先讨论了模型建立和算法选择与分析 ,并对实际的工程问题进行了计算和模拟 .所得的评价定级结果接近于实际 ,计算方法可靠 ,计算时间适中 ,方法稳定性良好 .本文的研究结果表明 ,利用人工神经网络方法评价隧道围岩的稳定性具有广阔应用前景 .     

Multipolar routing: where dynamic and static routing meet

Assuming that the traffic matrix belongs to a polytope, we describe a new routing paradigm where each traffic matrix is routed a combination of a number of extreme routings. This combination depends on the current traffic matrix. Multipolar routing can be seen as a generalization of both routing and robust static routing. Moreover, the time complexity of multipolar routing is under control since it depends on the number of poles (i.e. the number of extreme routings) which can be defined by the network planner     

Motorway traffic parameter estimation from mobile phone counts

In this paper a new method for real time estimation of vehicular flows and densities on motorways is proposed. This method is based on fusing traffic counts with mobile phone counts. The procedure used for the estimation of traffic flow parameters is based on the hypothesis that “instrumented” vehicles can be counted on specific motorway sections and traffic flow can be measured on entrance and exit ramps. The motorway is subdivided into cells, assuming that mobile phones entering and exiting every cell can be counted during the observation period. An estimate of “instrumented” vehicle concentration is obtained and propagated on the network in time and space. This allows one to estimate traffic flow parameters by sampling “instrumented” traffic flow parameters using a “concentration” (the ratio of the densities of instrumented vehicles to the density of overall traffic) propagation mechanism.     

Routing and location on a network with hazardous threats

The aim of this paper is to minimise the impact of hazards located on or near a network. Two situations are considered: (1) where a hazard is located on a network and affects off network sites and (2) an off-network hazard which can affect traffic on the network. Eight models aimed at optimising different objectives are developed and solved, including finding a route between two nodes on a network which minimises the hazard along it and finding a location on a network where the hazard is minimised.     

A framework for user equilibrium dynamic traffic assignment

Several analytic approaches have been developed to describe or predict traffic flows on networks with time-varying (dynamic) travel demands, flows and travel times. A key component of these models lies in modelling the flows and/or travel times on the individual links, but as this is made more realistic or accurate it tends to make the overall model less computationally tractable. To help overcome this, and for other reasons, we develop a bi-level user equilibrium (UE) framework that separates the assignment or loading of flows on the time–space network from the modelling of flows and trip times within individual links. We show that this model or framework satisfies appropriate definitions of UE satisfies a first-in-first-out (FIFO) property of road traffic, and has other desirable properties. The model can be solved by iterating between (a) a linear network-loading model that takes the lengths of time–space links as fixed (within narrow ranges), and (b) a set of link flow sub-models which update the link trip times to construct a new time–space network. This allows links to be processed sequentially or in parallel and avoids having to enumerate paths and compute path flows or travel times. We test and demonstrate the model and algorithms using example networks and find that the algorithm converges quickly and the solutions behave as expected. We show how to extend the model to handle elastic demands, multiple destinations and multiple traffic types, and traffic spillback within links and from link to link.     

Applying a recurrence plot scheme to analyze non-stationary transition patterns of IP-network traffic

This paper describes a recurrence plot (RP) approach to the analysis of non-stationary transition patterns of IP-network traffic. To get a quantitative measure of dynamical transition patterns of IP-network traffic, we used the values of determinism (DET) defined by the recurrence quantification analysis (RQA). Also, when evaluating the fractal-based properties of IP-network traffic, we focused on two parameters: (i) the long-range dependence (LRD)-related scaling parameter α derived from the detrended fluctuation analysis (DFA) and (ii) the range of the generalized fractal dimension. In applying this method to traffic analysis, we performed two kinds of traffic measurement in Tokyo, Japan, and derived the values of DET and fractal-based parameters of IP-network traffic over time. In checking the measured network traffic, we found that the characteristic with respect to DET and self-similarity seen in the measured network traffic fluctuated over time, with different time-variation patterns for two measurement locations. Results also confirmed that a larger value of DET or accumulated DET reflected increases in the degree of LRD of IP-network traffic and that the accumulated DET reflected the decreases in the degree of multi-fractality of IP-network traffic. As a result, we confirmed that RP-based measures can be effective for evaluating the non-stationary transition patterns of IP-network traffic in terms of quantitative fractal-based properties.     

Sensitivity Analysis Based Method for Optimal Road Network Pricing

Road pricing is an important economic measure for optimal management of transportation networks. The optimization objectives can be the total travel time or total cost incurred by all the travelers, or some other environmental objective such as minimum emission of dioxide, an so on. Suppose a certain toll is posed on some link on the network, this will give an impact on flows over the whole network and brings about a new equilibrium state. An equilibrium state is a state of traffic network at which no traveler could decrease the perceived travel cost by unilaterally changing the route. The aim of the toll setting is to achieve such an equilibrium state that a certain objective function is optimized. The problem can be formulated as a mathematical program with equilibrium constraints (MPEC). A key step for solving such a MPEC problem is the sensitivity analysis of traffic flows with respect to the change of link characteristics such as the toll prices. In this paper a sensitivity analysis based method is proposed for solving optimal road pricing problems.     

Discrete-time dynamic traffic assignment models with periodic planning horizon: system optimum

This paper proposes a system optimal dynamic traffic assignment model that does not require the network to be empty at the beginning or at the end of the planning horizon. The model assumes that link travel times depend on traffic densities and uses a discretized planning horizon. The resulting formulation is a nonlinear program with binary variables and a time-expanded network structure. Under a relatively mild condition, the nonlinear program has a feasible solution. When necessary, constraints can be added to ensure that the solution satisfies the First-In-First-Out condition. Also included are approximation schemes based on linear integer programs that can provide solutions arbitrarily close to that of the original nonlinear problem.     

Multiscale Analysis and Data Networks

The empirical finding of self-similarity in data network traffic over many time scales motivates the need for analysis tools that are particularly well adapted for identifying structures in network traffic. These structures span a range of time scales or are scale-dependent. Wavelet-based scaling analysis methods are especially successful, both collecting summary statistics from scale to scale and probing the local structure of packet traces. They include both spectral density estimation to identify large time-scale features and multifractal estimation for small time-scale bursts. While these methods are primarily statistical in nature, we may also adapt them to visualize the “burstiness” or the instantaneous scaling features of network traffic. This expository paper discusses the theoretical and implementation issues of wavelet-based scaling analysis for network traffic. Because data network traffic research does not consist solely of analysis, we show how these wavelet-based methods may be used to monitor and infer network properties (in conjunction with on-line algorithms and careful network experimentation). More importantly, we address what types of networking questions we can and cannot investigate with such tools.