Routing Behavior Research Articles

A sensitivity-based approach for adaptive decomposition of anticipatory network traffic control

Anticipatory optimal network control is defined as the problem of determining the set of control actions that minimizes a network-wide objective function. This not only takes into account local consequences on the propagation of flows, but also the global network-wide routing behavior of the users. Such an objective function is, in general, defined in a centralized setting, as knowledge regarding the whole network is needed to correctly compute it. Reaching a level of centralization sufficient to attain network-wide control objectives is however rarely realistic in practice. Multiple authorities are influencing different portions the network, separated either hierarchically or geographically. The distributed nature of networks and traffic directly influences the complexity of the anticipatory control problem.This is our motivation for this work, in which we introduce a decomposition mechanism for the global anticipatory network traffic control problem, based on dynamic clustering of traffic controllers. Rather than solving the full centralized problem, or blindly performing a full controller-wise decomposition, this technique allows recognizing when and which controllers should be grouped in clusters, and when, instead, these can be optimized separately.The practical relevance with respect to our motivation is that our approach allows identification of those network traffic conditions in which multiple actors need to actively coordinate their actions, or when unilateral action suffices for still approximating global optimality.This clustering procedure is based on well-known algebraic and statistical tools that exploit the network’s sensitivity to control and its structure to deduce coupling behavior. We devise several case studies in order to assess our newly introduced procedure’s performances, in comparison with fully decomposed and fully centralized anticipatory optimal network control, and show that our approach is able to outperform both centralized and decomposed procedures.

Building Nemo, a system to monitor IP routing and traffic paths in real time

Efficiently operating and quickly troubleshooting Internet backbones require timely and accurate information about the routing system, their traffic demands, and how they are routed. Unfortunately, the dynamism and complexity of routing protocols, their lack of monitoring features and intricate interaction, together with the volume of routing state make their monitoring network-wide (e.g. across an AS or ISP) hard; while the narrow scope of traffic data provided by existent measurement tools and scalability issues make it difficult to infer the spatial distribution of the traffic. We present the design of a Network Monitoring tool (Nemo) conceived to offer two critical functions: first, monitoring nodes’ routing and forwarding state in nearly real time; second, the ability to derive forwarding paths, which can permit obtaining spatial representations of the traffic when combined with traffic measurement data. We discuss the hardest challenges to overcome to support these functions, how we addressed them, and show preliminary results obtained in two operational networks to illustrate the feasibility and utility of the tool. Nemo was conceived to work with legacy equipment, relying only on standard, widely-supported functions. Nevertheless, we identify downsides of recent monitoring features and suggest simple modifications to router behavior that could greatly ease monitoring the routing system.

Network modelling and prediction of retrograde gas behaviour in natural gas pipeline systems

As retrograde gases are transported through pipeline systems, retrograde condensation may occur. The presence of this additional liquid phase is responsible for additional pressure losses in natural gas surface production systems. Gases and liquids have markedly different routing behaviour when moving concurrently through a network system and the determination of their distribution within the network is of vital importance for retrograde gas surface transportation operations. This study is aimed at developing and testing an analytical tool that predicts phase behaviour of retrograde gas in natural gas pipeline systems. This tool will allow operators to make better decisions regarding liquid phase removal from the network, pressure loss mitigation, design and location of surface production and separation equipment with an accurate map of the pressure, phase distribution and phase property inside the network. The proposed network model for retrograde gas is able to handle realistic field situations and allows the user to effectively track liquid and gas preferential routing within the network and provide guidance for improving the performance of the entire gas pipeline system.

Electric vehicles: A review of network modelling and future research needs

Electric vehicles are believed to be an effective solution for reducing greenhouse gas emissions. Despite extensive study on the attributes and characteristics of electric vehicles and their charging infrastructure design, the development and network modelling of electric vehicles are still evolving and limited. This article provides a comprehensive review of electric vehicle studies and identifies existing research gaps in the aspects of theories, modelling approaches, solution algorithms and applications. This article first describes the electric vehicles’ concepts, market share, characteristics and charging infrastructures. Then, the studies on traffic assignment problem with electric vehicles in the network and limited charging facilities are particularly discussed. We conclude that it is of great importance to take into account electric vehicles’ special characteristics (e.g. range limit) in predicting their routing behaviour and charging infrastructure design networks.

Exploratory Analysis of Signal Coordination Impacts on Macroscopic Fundamental Diagram

The macroscopic fundamental diagram (MFD) of urban traffic is a recently developed tool to describe traffic on large-scale urban networks. A network’s MFD can be significantly affected by various properties, including signal settings, block lengths, travel speeds, and routing behaviors. However, current understanding of the impact of signal offsets (i.e., signal coordination) on the MFD is limited to idealized one-dimensional networks, and little is known about how signal coordination affects the MFDs of more realistic two-dimensional networks. To overcome this gap, the present study examined the impacts of signal coordination on the MFD of an idealized two-dimensional grid network using both an analytical method and a microscopic traffic simulator (Aimsun). Seven coordination strategies were considered, including the simultaneous, alternating, double-alternating, one-dimensional green-wave, two-dimensional green-wave, MAXBAND, and random strategies. In general, the impacts of coordination were highly sensitive to the signal cycle length chosen. The results also revealed that poor coordination can significantly decrease the network capacity and the free-flow travel speed. However, good coordination offers little advantage over simultaneous offsets, even with directional travel demands moving in the prioritized directions. The reason is that the benefits provided to vehicles in the prioritized directions are negated by the disadvantages to vehicles traveling in the nonprioritized directions. These results suggest that the insights from other idealized simulations with simultaneous offsets may be generalizable to more realistic situations with more realistic coordination strategies.

Mitigating routing behavior in mobile wireless network with various types of routing attacks

Mitigating routing behavior in mobile wireless network with various types of routing attacks

X-Hamiltonian Surface Broadcast Algorithm

Broadcast is one of the most important approach in distributed memory parallel computers that is used to find a routing approach from one source to all nodes in the mesh. Broadcasting is a data communication task in which corresponds to one-to-all communication. Routing schema is the approach used to determine the road that is used to send a message from a source node to destination nodes. In this paper, we propose an efficient algorithm for broadcasting on an all-port wormhole-routed 3D mesh with arbitrary size. Wormhole routing is a fundamental routing mechanism in modern parallel computers which is characterized with low communication latency. We show how to apply this approach to 3-D meshes. In wormhole, routing large network packets are broken into small pieces called FLITs (flow control digits). The destination address is kept in the first flit which is called the header flit and sets up the routing behavior for all subsequent flits associated with the packet. In this paper, we introduce an efficient algorithm, X-Hamiltonian Surface Broadcast (X-HSB) which uses broadcast communication facility with deadlock-free wormhole routing in general three dimensional networks. In this paper, the behaviors of this algorithm are compared to the previous results using simulation; our paradigm reduces broadcast latency and is simpler. The results presented in this paper indicate the advantage of our proposed algorithm.

基于绕行路径的聚类分析与异常检测

本文对BGP路由中的绕行路径作了定义，通过观察路由表的AS_PATH属性，总结归纳了绕行路径的六种表现形式，即连续重复AS、环路、绕邻居AS、绕国、绕境、绕跨国企业。同时，对绕行路径的表现形式进行了聚类分析，并提出了基于绕行路径的连续重复AS、路由环路、国内流量外泄、路径伪造、路径篡改等异常路由检测方法。实验表明，本文所提方法能够有效检测异常路由行为，同时揭示了绕行路径的存在是使得网络流量传递平均最短路径变长的主要原因之一。 In this paper, the detour path is defined firstly. Through the observation of AS_PATH property of the routing table, we sum up the six forms of the detour path, i.e., continuously repeated AS, loop, around the neighbor AS, around the country, around the border and around the multinational company. Moreover, we did the clustering analysis of the manifestation of detour path and put forward the routing anomaly detection method based on the detour path. The method can detect the continuous repeated AS, routing loop, domestic traffic leaked, forged path, garbled path with such anomalies. Experiments show that the proposed method can effectively detect abnormal routing behavior and also suggest that one of the main reasons for the average shortest path of Internet traffic which becomes longer is the existence of the detour paths.

Towards eco-friendly home networking

Home networking is becoming increasingly sophisticated as users connect ever more networked devices. In the past, home networks typically consisted of a simple router and maybe a few computers. Now, high speed wireless networks are commonplace in homes with a large number of devices: TVs, game consoles, home theater systems, and even home automation systems. This is in addition to standard computing devices such as desktops, laptops, tablets, smart phones and network-attached storage. Smart homes with many wireless sensors to improve quality of life are also emerging. However, home network devices such as routers and broadband modems have been designed for maximum performance with limited consideration of energy optimization when the devices are idle or serving low bandwidth traffic. The goal of this paper is to analyze network activity of wireless home routers, investigate opportunities for energy saving, and present mechanisms for improving the energy efficiency of wireless home routers. We analyzed five week-long traces of home network traffic and identified a number of energy saving opportunities. Through detailed trace-based simulation and implementation measurements we are able to reduce the wireless energy consumption of the home router by 12–59% while incurring only minor delay of the initial packet delivery after leaving the low energy state. Modification of an actual router's behavior shows that the proposed energy optimizations are feasible with existing clients.

Freight data collection using GPS and web-based surveys: Insights from US truck drivers’ survey and perspectives for urban freight

This paper reports on tools, methods and experimental designs that have been developed to study the routing behavior and movement of trucks. The application of these capabilities is demonstrated with a case study on the route choices of North American intercity truck drivers’, with a focus on the choice between tolled and free roads. An extension to the urban freight context, currently ongoing in Singapore, is briefly discussed, highlighting the challenges and main differences compared to the intercity case.

A Fast Prototyping Framework for Analog Layout Migration With Planar Preservation

Analog layout generation in the advanced CMOS design is challenging by its increasing layout constraints and performance requirements. This situation becomes more intricate by the growing parasitic variability and manufacturing reliability. To facilitate the feasibility of template-based layout migration, this paper first introduces a layout preservation, which extracts placement and routing behaviors from an existing layout into a crossing graph via constrained Delaunay triangulation. And later this crossing graph can be migrated into multiple layouts with placement and routing reconnection. The proposed approach also provides a refinement for wire to optimize the performance metrics. This approach is applied to a variable-gain amplifier, a folded-cascode operational amplifier, and a low dropout regulator. The experimental results demonstrate more possibility on layout migration, such that averagely more than 75% routing of migrated layout is generated by our approach. Additionally, it exhibits the productivity with qualified performance on different designs.

An extended coordinate descent method for distributed anticipatory network traffic control

Anticipatory optimal network control can be defined as the practice of determining the set of control actions that minimizes a network-wide objective function, so that the consequences of this action are taken in consideration not only locally, on the propagation of flows, but globally, taking into account the user’s routing behavior. Such an objective function is, in general, defined and optimized in a centralized setting, as knowledge regarding the whole network is needed in order to correctly compute it. This is a strong theoretical framework but, in practice, reaching a level of centralization sufficient to achieve said optimality is very challenging. Furthermore, even if centralization was possible, it would exhibit several shortcomings, with concerns such as computational speed (centralized optimization of a huge control set with a highly nonlinear objective function), reliability and communication overhead arising.The main aim of this work is to develop a decomposed heuristic descent algorithm that, demanding the different control entities to share the same information set, attains network-wide optimality through separate control actions.

Estimating Urban Traffic Patterns through Probabilistic Interconnectivity of Road Network Junctions.

The emergence of large, fine-grained mobility datasets offers significant opportunities for the development and application of new methodologies for transportation analysis. In this paper, the link between routing behaviour and traffic patterns in urban areas is examined, introducing a method to derive estimates of traffic patterns from a large collection of fine-grained routing data. Using this dataset, the interconnectivity between road network junctions is extracted in the form of a Markov chain. This representation encodes the probability of the successive usage of adjacent road junctions, encoding routes as flows between decision points rather than flows along road segments. This network of functional interactions is then integrated within a modified Markov chain Monte Carlo (MCMC) framework, adapted for the estimation of urban traffic patterns. As part of this approach, the data-derived links between major junctions influence the movement of directed random walks executed across the network to model origin-destination journeys. The simulation process yields estimates of traffic distribution across the road network. The paper presents an implementation of the modified MCMC approach for London, United Kingdom, building an MCMC model based on a dataset of nearly 700000 minicab routes. Validation of the approach clarifies how each element of the MCMC framework contributes to junction prediction performance, and finds promising results in relation to the estimation of junction choice and minicab traffic distribution. The paper concludes by summarising the potential for the development and extension of this approach to the wider urban modelling domain.

Orbital angular momentum (OAM) modes routing in a ring fiber based directional coupler

Optical modes carrying orbital angular momentum (OAM) are becoming a hot topic, for that it promises a greatly improved information transmission capacity for fiber-optic communication systems. In this paper, we report our study on the coupling characteristics (coupling length and power transfer behavior) of OAM modes routing in a ring fiber based directional coupler. We decomposed an OAM mode propagating along a ring fiber coupler into its corresponding HE even and odd modes using beam propagation method. We found a general description of OAM modes in a ring fiber based coupler, which provides useful information for further study of fiber components using OAM modes.

Asymmetric Three‐Way Plasmonic Color Routers

Coupling plasmonic silver nanocubes with a thin titania film allows three-way tunable asymmetric color routing, in which different scattering, reflection, and transmission colors are exhibited. The color routing behavior, which is due to Fano resonances and high refractive index of titania, is changed by switching between the front and back incidence and tuning the nanocube size and titania thickness.

A Reinforcement Routing Algorithm with Access Selection in the Multi–Hop Multi–Interface Networks

Abstract In this paper, a routing algorithm is proposed for access selection in a network to find the optimal paths among intermediate nodes with multiple interfaces. Markov Decision Process is applied in each node to find optimal policy and select proper paths to the best access point in a dynamic environment. A reward function is defined as environment feedback to optimize and adapt routing behavior of nodes based on the local information. Selection metrics in each node are interface load, link quality and destination condition. It is shown, by using the proposed algorithm, there are better management in the node which decreases interference and collision and selects links with better quality toward the best possible destination. The performance of the method is exemplified and it is shown how the throughput and average delay of the network with more interface in its nodes, improved while packet loss degrades. As an example a two-interface and a one-interface network are studied. It is shown when network load is increased, interface management will improve the throughput, in the network with two-interface nodes. Also, by considering the link quality factor in the reward function, packet dropping becomes less but average delay increases.

Evolutionary Game-Theoretic Solution for Virtual Routers with Padding Misbehavior in Cloud Computing

With the development of cloud computing and virtualization, a physical router can be multiplexed as a large number of virtual routers. TCP-based interactive applications have an incentive to improve their performance by padding “junk packets” into the network among real communication packets. This padding misbehavior will upgrade short TCP flows from “mice” to “elephants” and consequently lead to network congestion and breakdown. This paper presents a detailed solution and analysis for describing the normal behavior and padding misbehavior of virtual routers. In particular, a system model for analyzing behavior of virtual routers is based on evolutionary game model, and, through analyzing the stability of the equilibrium points, the stable point is the solution to the problem. The clear evolutionary path of network applications with the normal behavior and padding misbehavior is analyzed by the corresponding graph. Then this paper gives the behavior control suggestions to effectively restrain the padding misbehavior and maintain stable high-throughputs of the router. The simulation results demonstrate that our solution can effectively restrain the padding misbehavior and maintain stable high-throughputs of the router simultaneously compared with the classical queue management.

Design of energy efficient optical networks with software enabled integrated control plane

The growing energy consumption has posed new challenges for the future development of networks. Some earlier work has proposed solutions to improve energy consumption based on the existing control plane, for example, node/links sleeping. This study presents a new possibility to reduce network energy consumption by proposing a new integrated control plane structure utilising Software Defined Networking technologies. The integrated control plane increases the efficiencies of exchanging control information across different network domains, while introducing new possibilities to the routing methods and the control over quality of service (QoS). The structure is defined as an overlay generalised multi-protocol label switching (GMPLS) control model. With the defined structure, the integrated control plane is able to gather information from different domains (i.e. optical core network and the access networks), and enable energy efficiency networking over a wider area. In the case presented, the integrated control plane collects the network energy related information and the QoS requirements of different types of traffic. This information is used to define the specific group of traffic's (flow's) routing behaviours. With the flexibility of the routing structure, results show that the energy efficiency of the network can be improved without compromising the QoS for delay/blocking sensitive services.

Social-Insect-Inspired Networking for Autonomous Load Optimisation

The now established paradigm of System on Chip advances towards high-density many-core systems by employing Networks on Chip (NoCs) to connect a large number of processing elements. This brings many new challenges to embedded system design, but also opens up opportunities for new approaches that can leverage and exploit the many-core fabric in ways that traditional system architectures could not. This paper describes a new approach of adopting behavioural aspects of social insects as an inspiration towards autonomous, self-repairing systems. Each node in the NoC is considered as a member of a distributed colony and a simple adaptive controller is responsible for determining the behaviour of each node (member of the colony), relying only on a set of sensory inputs local to each node and small amounts of information shared between neighbours. Three adaptive routing schemes are presented that demonstrate how a sense-act-model applied at node level can lead to the emergence of novel routing behaviours that provide runtime self-optimisation of network load balancing without any prior analysis of the NoC topology. It is also discussed how these emergent behaviours of systems inspired by social insect colonies can be exploited to exhibit other novel autonomous and adaptive behaviours including fault tolerance and dynamic task allocation.

Rotor-routing on Galton-Watson trees

A rotor-router walk on a graph is a deterministic process, in which each vertex is endowed with a rotor that points to one of the neighbors. A particle located at some vertex first rotates the rotor in a prescribed order, and then it is routed to the neighbor the rotor is now pointing at. In the current work we make a step toward in understanding the behavior of rotor router walks on random trees. More precisely, we consider random i.i.d. initial configurations of rotors on Galton-Watson trees T, i.e. on a family tree arising from a Galton-Watson process, and give a classification in recurrence and transience for rotor-router walks on these trees.