基于状态反馈的网络分布式拥塞管理方案

提出了一种新型的面向区分服务网络的分布式拥塞管理方案。其基本思想是利用拥塞状态反馈信息在边缘节点或主机上实施拥塞管理，该方案主要包括三个组成部分；拥塞状态控制分组，早期拥塞检测和流量控制算法，实验结果表明，与标准的区分服务网络相比，该方案能在TCP和UDP聚集之间公平地分配带宽并能显著地降低分组丢失率。     

Management of traffic congestion in adaptive traffic signals using a novel classification-based approach

Traffic congestion is a critical problem which makes roads busy. Traffic congestion challenges traffic flow in urban areas. A growing urban area creates complex traffic problems in daily life. Congestion phenomena cannot be resolved only by applying physical constructs such as building bridges and motorways and increasing road capacity. It is necessary to build technological systems for transportation management to control the traffic phenomenon. In this article, a new idea is proposed to tackle traffic congestion with the aid of machine learning approaches. A new strategy based on a tree-like configuration (i.e. a decision-making model) is suggested to handle traffic congestion at intersections using adaptive traffic signals. Different traffic networks with different sizes, varying from nine to 400 intersections, are examined. Numerical results and discussion are presented to prove the efficiency and application of the proposed strategy to alleviate traffic congestion.     

TCP-friendly congestion control for streaming real-time applications over wireless networks

Congestion control for streaming real-time applications, which need smoothness of the transmission rate, should be transmission control protocol (TCP)-friendly. Moreover, in wireless networks, TCP-friendly congestion control should be based on differentiation of packet losses due to congestion and wireless link error to improve network utilisation. The authors propose a TCP-friendly congestion control algorithm based on explicit congestion notification over the wireless networks. The simulation results show that the proposed algorithm utilises the link bandwidth efficiently, providing smoothness of the transmission rate.     

An OpenFlow-Based Load Balancing Strategy in SDN

In today’s datacenter network, the quantity growth and complexity increment of traffic is unprecedented, which brings not only the booming of network development, but also the problem of network performance degradation, such as more chance of network congestion and serious load imbalance. Due to the dynamically changing traffic patterns, the state-of the-art approaches that do this all require forklift changes to data center networking gear. The root of problem is lack of distinct strategies for elephant and mice flows. Under this condition, it is essential to enforce accurate elephant flow detection and come up with a novel load balancing solution to alleviate the network congestion and achieve high bandwidth utilization. This paper proposed an OpenFlow-based load balancing strategy for datacenter networks that accurately detect elephant flows and enforce distinct routing schemes with different flow types so as to achieve high usage of network capacity. The prototype implemented in Mininet testbed with POX controller and verify the feasibility of our load-balancing strategy when dealing with flow confliction and network degradation. The results show the proposed strategy can adequately generate flow rules and significantly enhance the performance of the bandwidth usage compared against other solutions from the literature in terms of load balancing.     

Exploring Collective Dynamics in Communication Networks

A communication network, such as the Internet, comprises a complex system where cooperative phenomena may emerge from interactions among various traffic flows generated and forwarded by individual nodes. To identify and understand such phenomena, we model a network as a two-dimensional cellular automaton. We suspect such models can promote better understanding of the spatial-temporal evolution of network congestion, and other emergent phenomena in communication networks. To search the behavior space of the model, we study dynamic patterns arising from interactions among traffic flows routed across shared network nodes, as we employ various configurations of parameters and two different congestion-control algorithms. In this paper, we characterize correlation in congestion behavior within the model at different system sizes and time granularities. As expected, we find that long-range dependence (LRD) appears at some time granularities, and that for a given network size LRD decays as time granularity increases. As network size increases, we find that long-range dependence exists at larger time scales. To distinguish effects due to network size from effects due to collective phenomena, we compare congestion behavior within networks of selected sizes to congestion behavior within comparably sized sub-areas in a larger network. We find stronger long-range dependence for sub-areas within the larger network. This suggests the importance of modeling networks of sufficiently large size when studying the effects of collective dynamics.     

一种基于缓存交互的命名数据网络拥塞控制算法

研究了命名数据网络(NDN)的拥塞控制。为了解决突发流量问题和提高吞吐量及网络资源利用率,考虑了路由器缓冲区大小与拥塞控制机制的相互影响以及NDN内部署缓存这一重要特性,提出了一种基于缓存交互的NDN拥塞控制算法。该算法通过利用NDN中的路由器缓存,在逻辑上动态扩充缓冲区大小并控制Data包的发送速率,同时与现有的NDN拥塞控制算法相结合,动态调整Interest包发送速率阈值,以平滑突发流量,缓解网络拥塞。基于ndn SIM的仿真实验结果表明,该算法能有效提高NDN的传输效率、吞吐量和网络资源利用率。     

A network-wide exact optimization approach for multiobjective routing with path protection in multiservice multiprotocol label switching networks

A multiobjective routing model for multiprotocol label switching networks with multiple service types and path protection is presented in this article. The routing problem is formulated as a biobjective integer program, where the considered objectives are formulated according to a network-wide optimization approach, i.e. the objective functions of the route optimization problem depend explicitly on all traffic flows in the network. A disjoint path pair is considered for each traffic trunk, which guarantees protection to the associated connection. A link-path formulation is proposed for the problem, in which a set of possible pairs of paths is devised in advance for each traffic trunk. An exact method (based on the classical constraint method for solving multiobjective problems) is developed for solving the formulated problem. An extensive experimental study, with results on network performance measures in various randomly generated networks, is also presented and discussed.     

Robust end-to-end loss differentiation scheme for transport control protocol over wired/wireless networks

The authors propose a robust end-to-end loss differentiation scheme to identify the packet losses because of congestion for transport control protocol (TCP) connections over wired/wireless networks. The authors use the measured round trip time (RTT) values to determine whether the cause of packet loss is because of the congestion over wired path or regular bit errors over wireless paths. The classification should be as accurate as possible to achieve high throughput and maximum fairness for the TCP connections sharing the wired/wireless paths. The accuracies of previous schemes in the literature depends on varying network parameters such as RTT, buffer size, amount of cross traffic, wireless loss rate and congestion loss rate. The proposed scheme is robust in that the accuracy remains rather stable under varying network parameters. The basic idea behind the scheme is to set the threshold for the classification to be a function of the minimum RTT and the current sample RTT, so that it may automatically adapt itself to the current congestion level. When the congestion level of the path is estimated to be low, the threshold for a packet loss to be classified as a congestion loss is increased. This avoids unnecessary halving of the congestion window on packet loss because of the regular bit errors over the wireless path and hence improves the TCP throughput. When the congestion level of the path is estimated to be high, the threshold for a packet loss to be classified as the congestion loss not to miss any congestion loss is decreased and hence improves the TCP fairness. In ns 2 simulations, the proposed scheme correctly classifies the congestion losses under varying network parameters whereas the previous schemes show some dependency on subsets of parameters.     

Congestion-aware proactive vertical handoff algorithm in heterogeneous wireless networks

In heterogeneous wireless networks, when a mobile host/handset (MH) with multiple wireless interfaces changes its location or requires a certain network service, the MH will require a switch between different wireless networks (namely vertical handoff). A congestion-aware proactive vertical handoff algorithm is proposed, which uses a data pre-deployment technology to realise soft handoff between cellular interface and ad hoc interface. Here, the vertical handoff algorithm is implemented in an experimental heterogeneous network structure called converged ad hoc and cellular network, which is an ad hoc overlay system considering the balancing of the traffic between adjacent cellular cells. By evaluations, it is shown that the proposed algorithm can realise low handoff delay and low packet losses, and help to ease congestion issue existing in the heterogeneous networks.     

Improve urban passenger transport management by rationally forecasting traffic congestion probability

A Bayesian network (BN) approach is proposed in this study to analyse the overall traffic congestion probability of an urban road network in consideration of the influence of applying various transport policies. The continually expanding urbanised region of Beijing has been chosen as the study area because of its rapid expansion and motorisation, which lead to the severe traffic congestion occurring nearly every day. It is demonstrated that the proposed BN approach is able to rationally predict the probability of the overall traffic congestion that will take place given a certain transport policy. It is also proven that increasing the number of buses providing convenient passenger transport service in the urbanised region of Beijing will most effectively reduce the probability of the traffic congestion in this area, especially when the newly constructed roads in the same region are put into use.     

Loss rate-based burst assembly to resolve contention in optical burst switching networks

Two loss rate-based optical burst assembly techniques addressing contention resolution are studied. These techniques stem from the burst assembly schemes using adaptive thresholds, which have been introduced earlier by the authors. The loss rates on the links/paths leading to the destination nodes are used to estimate congestion levels. Three alternative time and size threshold value pairs are employed based on the congestion level observed. Here, the aim is to generate short bursts under heavy traffic and long bursts under light traffic conditions in order to enhance performance. The results that are obtained in terms of byte loss rate and delay are compared with those of the hybrid burst assembly. It is observed that the adaptive techniques significantly enhance the byte loss rate as traffic gets heavier while keeping end-to-end delay in a feasible range.     

Spatial econometrics models for congestion prediction with in-vehicle route guidance

The congestion dependence relationship among links using microsimulation is explored, based on data from a real road network. The work is motivated by recent innovations to improve the reliability of Dynamic Route Guidance (DRG) systems. The reliability of DRG systems can be significantly enhanced by adding a function to predict the congestion in the road network. The application of spatial econometrics modelling to congestion prediction is also explored, by using historical traffic message channel (TMC) data stored in the vehicle navigation unit. The nature of TMC data is in the form of a time series of geo-referenced congestion warning messages, which is generally collected from various traffic sources. The prediction of future congestion could be based on the previous year of TMC data. Synthetic TMC data generated by microscopic traffic simulation for the network of Coventry are used in this study. The feasibility of using spatial econometrics modelling techniques to predict congestion is explored. The results are presented at the end.     

Rate-adaptive video streaming through packet dispersion feedback

The anticipated growth of IPTV makes selection of suitable congestion controllers for video-stream traffic of vital concern. Measurements of packet dispersion at the receiver provide a graded way of estimating congestion, which is particularly suited to video as it does not rely on packet loss. A closed-loop congestion controller, which dynamically adapts the bitstream output of a transcoder or video encoder to a rate less likely to lead to packet loss, is presented. The video congestion controller is based on fuzzy logic with packet dispersion and its rate of change forming the inputs. Compared with TCP emulators such as TCP-friendly rate control (TFRC) and rate adaptation protocol (RAP), which rely on packet loss for real-time congestion control, the fuzzy-logic trained system?s sending rate is significantly smoother when multiple video-bearing sources share a tight link. Using a packet dispersion method similarly results in a fairer allocation of bandwidth than TFRC and RAP. These gains for video traffic are primarily because of better estimation of network congestion through packet dispersion but also result from accurate interpretation by the fuzzy-logic controller.     

Efficient Routing Protocol with Localization Based Priority & Congestion Control for UWSN

The nodes in the sensor network have a wide range of uses, particularly on under-sea links that are skilled for detecting, handling as well as management. The underwater wireless sensor networks support collecting pollution data, mine survey, oceanographic information collection, aided navigation, strategic surveillance, and collection of ocean samples using detectors that are submerged in water. Localization, congestion routing, and prioritizing the traffic is the major issue in an underwater sensor network. Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource. Minimization of localization error using the proposed angle-based forwarding scheme is explained in this paper. We choose the shortest path to the destination using the fitness function which is calculated based on fault ratio, dispatching of packets, power, and distance among the nodes. This work contemplates congestion conscious forwarding using hard stage and soft stage schemes which reduce the congestion by monitoring the status of the energy and buffer of the nodes and controlling the traffic. The study with the use of the ns3 simulator demonstrated that a given algorithm accomplishes superior performance for loss of packet, delay of latency, and power utilization than the existing algorithms.     

Network Quality Assessment in Heterogeneous Wireless Settings: An Optimization Approach

The identification of an effective network which can efficiently meet the service requirements of the target, while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless medium. The wrong selection can contribute to unwanted situations like frustrated users, slow service, traffic congestion issues, missed and/or interrupted calls, and wastefulness of precious network components. Conventional schemes estimate the handoff need and cause the network screening process by a single metric. The strategies are not effective enough because traffic characteristics, user expectations, network terminology and other essential device metrics are not taken into account. This article describes an intelligent computing technique based on Multiple-Criteria Decision-Making (MCDM) approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless settings. In different components the handover need is assessed and the desired network is chosen. Further, fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a decision. The proposed research endeavor will support designers and developers to identify, select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless settings. The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.     

Load balancing in the provisioning of hose model virtual private networks with multi-path routing

Load balancing in the provisioning of virtual private network (VPN) service in the hose model is studied. Single-path routing and tree routing for the hose model tend to aggregate bandwidth reservations on a small number of links, thus leading to congestion problems in service provider networks. If the link capacity is depleted as a result of improper routing, all future non-VPN traffic will be blocked. We propose a novel multi-objective multi-path (MOMP) routing linear program with the maximum fraction of traffic on a path (MFTP) constraint to solve the problem. The MOMP routing algorithm is able to reduce the bandwidth reservation on the most loaded link by as much as 50%, thus effectively alleviating the potential congestion problems in service provider network. The MFTP constraint provides a guarantee of the availability of multiple paths for each VPN endpoint pair. Further reduction of the bandwidth reservation can be achieved depending on the MFTP value. This is highly significant.     

Collision Observation-Based Optimization of Low-Power and Lossy IoT Network Using Reinforcement Learning

The Internet of Things (IoT) has numerous applications in every domain, e.g., smart cities to provide intelligent services to sustainable cities. The next-generation of IoT networks is expected to be densely deployed in a resource-constrained and lossy environment. The densely deployed nodes producing radically heterogeneous traffic pattern causes congestion and collision in the network. At the medium access control (MAC) layer, mitigating channel collision is still one of the main challenges of future IoT networks. Similarly, the standardized network layer uses a ranking mechanism based on hop-counts and expected transmission counts (ETX), which often does not adapt to the dynamic and lossy environment and impact performance. The ranking mechanism also requires large control overheads to update rank information. The resource-constrained IoT devices operating in a low-power and lossy network (LLN) environment need an efficient solution to handle these problems. Reinforcement learning (RL) algorithms like Q-learning are recently utilized to solve learning problems in LLNs devices like sensors. Thus, in this paper, an RL-based optimization of dense LLN IoT devices with heavy heterogeneous traffic is devised. The proposed protocol learns the collision information from the MAC layer and makes an intelligent decision at the network layer. The proposed protocol also enhances the operation of the trickle timer algorithm. A Q-learning model is employed to adaptively learn the channel collision probability and network layer ranking states with accumulated reward function. Based on a simulation using Contiki 3.0 Cooja, the proposed intelligent scheme achieves a lower packet loss ratio, improves throughput, produces lower control overheads, and consumes less energy than other state-of-the-art mechanisms.     

Reactive and proactive routing in labelled optical burst switching networks

Optical burst switching architectures without buffering capabilities are sensitive to burst congestion. The existence of a few highly congested links may seriously aggravate the network throughput. Proper network routing may help in congestion reduction. The authors focus on adaptive routing strategies to be applied in labelled OBS networks, that is, with explicit routing paths. In particular, two isolated alternative routing algorithms that aim at network performance improvement because of reactive route selection are studied. Moreover, a nonlinear optimisation method for multi-path source-based routing, which aims at proactive congestion reduction is proposed. Comparative performance results are provided and some implementation issues are discussed.     

Analysis of effect of load-based excess bandwidth reservation on performances of differentiated services in E-PON

Performances of differentiated services in the upstream transmission of Ethernet passive optical network (E-PON) are affected by bandwidth reservation algorithm of an optical network unit, since data packets can be transmitted to an optical line termination only during the reserved transmission window. The effects of time-slot reservation on differentiated services are analysed and an adaptive class-based excess bandwidth reservation algorithm, called service quality pre-engagement (SQP), which reserves a time-slot based on the backlog queue and traffic arrival pattern of class is proposed. SQP applies the prediction-based bandwidth reservation to selected forward reservation classes (FRCs) which are determined by the introduced dynamic FRC selection. The proposed short-term service work-based time-slot reservation and long-term adaptive FRC selection optimise time-slot reservation according to traffic load of class. Analytic and simulation results show that this approach improves the performance of differentiated services, especially in terms of system buffer size, light-load penalty and service fairness, while guaranteeing high link utilisation and throughput     

Providing differentiated services in CDMA wireless networks

With much more advanced techniques employed, various applications can be supported by 3G CDMA-based wireless networks. Providing differentiated service over wireless networks has become a very important issue in the design of wireless networks. A new media access control protocol with a hierarchical scheduling algorithm to provide differentiated service for CDMA-based wireless networks is proposed. This protocol evolves from the distributed queuing random access protocol for CDMA wireless network. The proposed protocol has been designed to have an ability to accommodate integrated traffic in the networks with effective scheduling schemes. A series of simulation experiments have been carried out to evaluate the performance of the proposed protocol with the hierarchical scheduling algorithm. The results reveal that the proposed solution performs effectively in the integrated traffic composed of messages with or without time constraints and achieves proportional fairness among different types of traffic.