Analytical models of blocking probability for multi-granularity cross-connect-based optical networks

Multi-granularity optical cross-connect (MG-OXC)-based optical network is a promising optical network architecture as it is capable of flexible switching at different granularity levels. In MG-OXC-based optical networks, wavelength conversion (WC) capability and the number of usable add/drop ports of the nodes are two key factors affecting its performance. Two analytical models of blocking probability for MG-OXC-based optical networks both without WC capability and with sparse WC capability are proposed, exploiting Erlang?s loss formula and birth?death process. Based on the models and simulation, the impact of WC capability and the number of add/drop ports on the blocking probability are investigated. Three kinds of granularities (i.e. fibre, waveband and wavelength) are considered in MG-OXC nodes to reduce the complexity and size of switch fabric. Both the analytical and simulation results are given on two network topologies under dynamic traffic patterns. Simulation results show that the proposed models are accurate and effective for the analysis of blocking probability in MG-OXC-based optical networks.     

Traffic Engineering in Dynamic Hybrid Segment Routing Networks

The emergence of Segment Routing (SR) provides a novel routing paradigm that uses a routing technique called source packet routing. In SR architecture, the paths that the packets choose to route on are indicated at the ingress router. Compared with shortest-path-based routing in traditional distributed routing protocols, SR can realize a flexible routing by implementing an arbitrary flow splitting at the ingress router. Despite the advantages of SR, it may be difficult to update the existing IP network to a full SR deployed network, for economical and technical reasons. Updating partial of the traditional IP network to the SR network, thus forming a hybrid SR network, is a preferable choice. For the traffic is dynamically changing in a daily time, in this paper, we propose a Weight Adjustment algorithm WASAR to optimize routing in a dynamic hybrid SR network. WASAR algorithm can be divided into three steps: firstly, representative Traffic Matrices (TMs) and the expected TM are obtained from the historical TMs through ultra-scalable spectral clustering algorithm. Secondly, given the network topology, the initial network weight setting and the expected TM, we can realize the link weight optimization and SR node deployment optimization through a Deep Reinforcement Learning (DRL) algorithm. Thirdly, we optimize the flow splitting ratios of SR nodes in a centralized online manner under dynamic traffic demands, in order to improve the network performance. In the evaluation, we exploit historical TMs to test the performance of the obtained routing configuration in WASAR. The extensive experimental results validate that our proposed WASAR algorithm has superior performance in reducing Maximum Link Utilization (MLU) under the dynamic traffic.     

Measurement and Control of Packet Loss Probability for MPLS VPN Services

Multiprotocol-label-switch virtual private network (VPN) service has emerged as a value-added cost-effective VPN- based service, and its market opportunity is tremendous for network service providers (NSPs). Quality of service (QoS) control is one of the critical issues to be addressed, for NSPs to maximize their profits. This paper proposes a QoS control system that combines the service admission control (SAC) and the rate feedback control together to maintain the preset QoS parameters (the packet loss probability case) in the provider's backbone network. First, one measurement module employs distributed intelligent agents to measure the VPN traffic from all of the heterogenous remote network nodes. The packet loss probability is then estimated on line by applying the large-deviation theory. SAC strategy decides the amount of permitted VPN services, while the feedback controller dynamically throttles ingress traffic rates of instantiated VPN services to maintain the preset packet loss targets. The performance is evaluated in the live network of the National Capital Institute of Telecommunications (NCIT$ast$net2). Numeric results show that, under appropriately selected control parameters, it is possible to maintain the network operation within a prescribed loss limit.     

Location management for packet switched services in 3G partnership project networks

In order for third-generation partnership project (3GPP) networks to cope with the rapid growth of IP data traffic, the location management requires further enhancement to accommodate the burst data traffic characteristics of packet switched (PS) services. The universal mobile telecommunication system (UMTS) location management solutions for PS services in 3GPP networks has been investigated, and an inactivity counter mechanism in PS domain to reduce the location management cost of inactivate users has been proposed. An analytical model accommodating diverse call and mobility characteristics of user equipment to evaluate the performance of the inactivity counter mechanism has also been developed. Using the proposed model, the performance of the inactivity counter mechanism in UMTS terrestrial radio access network recommended by 3GPP is investigated, the cost reduction obtained by the proposed mechanism when compared with the original location strategy used in the PS domain is then analysed, which also shows the effect of system parameters and users' mobility and service patterns on the location management costs.     

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.     

Reservation signalling mechanism for reducing blocking probability in optical burst switching networks with limited wavelength conversion capabilities

First, the optical burst switching (OBS) network with limited wavelength conversion capability (LWCC) is decomposed into multiple wavelength continuous segments according to the position of wavelength converters. Based on the decomposed network model, two reservation signalling mechanisms for OBS-LWCC networks, namely wavelength-amend-on-demand (WAoD) and contention-based limited signalling protocol (CLSP), are proposed to reduce the blocking probability in the OBS-LWCC networks. In WAoD, the congested node sends a feedback message to the closest upstream switch with wavelength conversion capability. The notified switch will change the burst wavelength to the one assigned by the congested node to avoid collision in advance. Extensive simulation results indicate that by applying the wavelength reconfiguration method to the core nodes without wavelength conversion capability, the proposed WAoD scheme can improve the blocking performance in the OBS-LWCC networks significantly. Furthermore, CLSP, which combines the burst time-slot reconfiguration with the wavelength reconfiguration of WAoD, always has the lowest burst loss probability when compared with both the conventional and the proposed reservation mechanisms.     

一种基于P圈的ASON节点保护方案

在研究自动交换光网络（ASON）中发生节点故障时的保护方法的基础上,提出了一种针对节点故障使用P圈实现业务保护的方案,同时提出了一种在确保发生单链路故障时实现100％业务恢复率的基础上进行节点故障保护的启发式算法,并通过OPNET软件搭建的ASON仿真平台,在泛欧COST239网络拓扑和北美NSFnet网络拓扑上,采用静态业务模型对该算法进行了仿真评估。仿真结果证明,该算法在拥有故障业务快速恢复能力的同时,相比已有算法具有更低的资源冗余度。     

Design and performance analysis of code families for multi-dimensional optical CDMA

A code design algorithm for application in multi-dimensional optical code division multiple access (MD-OCDMA) for asynchronous optical fibre communication is proposed. Two-dimensional (2D) wavelength-time or space-time OCDMA and three-dimensional (3D) space-wavelength-time OCDMA are subsets of MD-OCDMA. Some applications and the performance analysis of the algorithm in 2D multipulse per row codes and 3D multipulse per plane codes are shown. In the applications discussed, this design ensures a maximum cross-correlation of '1' between any two codes. The performance metrics studied are the probability of error due to multiple-access interference for different numbers of active users and optimum temporal length for different values of cardinality. The performance analysis shows that the proposed 2D design offers very low probability of error due to multiple-access interference at lower cardinality when compared with other 2D designs using equivalent code dimension. A comparison of the proposed 3D design with an existing 3D design shows better performance at lower cardinality. The 3D designs show better performance when compared with the 2D designs.     

Authentication of Vehicles and Road Side Units in Intelligent Transportation System

Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state information of the communication link. We consider the communication link between vehicle-tovehicle, and vehicle-to-infrastructure. We evaluate the performance of our proposed technique by measuring the rogue attack probability, false alarm rate (FAR), misdetection rate (MDR), and utility function of a receiver based on the test threshold values of reinforcement learning algorithm. The results show that the FAR and MDR are decreased significantly by selecting an appropriate threshold value in order to improve the receiver’s utility.     

An Efficient Algorithm for Global Path Optimization in MPLS Networks

This paper proposes an algorithm to solve the optimization of label switched paths (LSPs) in multiprotocol label switching (MPLS) networks. The underlying optimization problem in this task is the well-known unsplittable multicommodity flow problem equipped with practically relevant objective functions and specialized with hard technical requirements.The proposed heuristic algorithm is based on network flow theory. It incorporates iterative shortest path search and performs adaptive edge weight adjustments in order to successfully satisfy all the required traffic demands and to maximize user-defined objectives. The robust algorithm facilitates the incorporation of several strategic and optimization objectives and the fulfillment of certain hard technical requirements of the target problem domain as well. Novel features of the approach include a new adaptive path allocation/deallocation strategy based on the identification of bottleneck links, demand ordering and preprocessing phases, and a systematic path allocation control method.The efficiency of the method is empirically shown on randomly generated networks with practical sizes and topologies, and on a real-world IP (Internet Protocol) backbone network. The algorithm is able to successfully solve difficult problem instances comprising very large instances with 1000 nodes, 3500 edges and 999000 traffic demands. The computational tests demonstrate that the proposed approach can be efficiently applied to solve problem instances that embed MPLS specific hard technical requirements. Furthermore, it is shown that our algorithm offers significantly better performance than the straightforward adaptations of existing methods that were developed for related network optimization problems. Namely, our algorithm produces acceptable results quicker, it can solve problems that were not previously solvable, and it yields better results than the alternative methods. The extensive empirical tests demonstrate the combinatorial properties of the target problem and the performance aspects of the algorithm and its components as well.     

Inter-vehicle mobile ad hoc network for road transport systems

Access to information services while on the move is becoming increasingly prevalent within transport systems. Whereas Internet access is now common place in trains, it still remains a challenge for vehicles, particularly when travelling through high speed motorways. Motorway vehicles equipped with wireless communication nodes form an ad hoc network have been examined by which data can be exchanged among them without the need for a pre-installed infrastructure. The main challenge with such an infrastructure-less network is developing communications and protocols that can deliver robust and reliable ad hoc communications between vehicles, when the relative speed between vehicles that can be extremely high under opposite traffic conditions. To address this opposite direction effect, a solution has been presented by minimising the effect of opposite traffic on routing packets. Firstly, a router direction index is introduced to enhance the performance of ad hoc on demand distance vector protocol in updating its routing table and secondly, a new queue priority mechanism is proposed which is based on cross-layer collaboration. Simulations were performed for an ad hoc network consisting of 200 vehicles driving with speeds between 90 and 120 km/h on a two-way motorway for different traffic loads sent through a Gateway adjacent to the motorway. The results obtained demonstrate a performance increase in the average data goodput and less routing overhead for the proposed solution     

考虑非平稳车载过程的在役桥梁时变可靠度分析

近年来,我国有大批桥梁得以新建。与此同时,日益增加的车辆荷载使得在役桥梁面临着更大的服役风险。在已有研究中,桥梁结构的可靠度评估将车载随机过程看作平稳泊松过程,且假定荷载效应概率模型在评估期内独立同分布。历史数据表明,我国的汽车荷载存在明显的逐年增加的趋势,随时间不再服从同一分布,已有方法也不再适用。为此,该文改进了已有方法,提出了考虑非平稳车载过程的在役桥梁时变可靠度评估新方法。算例表明,改进的方法简便易行,结果准确。已有方法可看作是该文改进方法的特例。随后,利用这一方法研究了结构可靠度对车载随机过程参数的敏感性。结果表明,车载随机过程参数对结构可靠度的影响显著。在20年的评估期内,均值每年增加1.1%或标准差每年增加1.3%,都会造成结构的失效概率增大两倍。     

基于虚拟化的轻量级背景流量节点生成及部署算法研究

进行了网络攻防分析,针对传统的背景流量模拟技术在生成及部署方面存在背景流量大小}限、背景流量真实性不足、背景流量生成工具部署的数量和位置}限的问题,提出了一种基于虚拟化的轻量级背景流量节点生成及部署算法,该算法是一种基于资源量的目标流量映射、基于最短路由的背景流量应用添加、基于最少通信代价的节点映射的三阶段算法,解决了背景流量节点在网络攻防实验中大规模快速生成及灵活部署的问题。实验结果表明,使用轻量级背景流量节点,生成的背景流量满足网络自相似性,资源消耗小、启动速度快,并且可根据实际网络攻防实验的需求进行动态、灵活、快速的大规模部署。     

Probabilistic evaluation of initiation time of chloride-induced corrosion

The paper presents a model for chloride ingress into concrete. The model accounts for two mechanisms which control the chloride ingress—diffusion and convection. Using one-dimensional (1-D) formulation of the model, the influence of chloride binding and ambient humidity on chloride ingress into concrete has been investigated. Based on results of this investigation parameters for probabilistic analysis have been selected. Probabilistic evaluation of the time to corrosion initiation has then been carried out for a reinforced concrete (RC) wall (1-D problem) and a RC column (2-D problem) in a marine environment. Results of the analysis show that for the same thickness of the concrete cover the probability of corrosion initiation in the corner reinforcing bars of the RC column is much higher than in reinforcing bars in the middle part of the RC wall. The results demonstrate the importance of 2-D modelling for correct prediction of corrosion initiation in such RC elements as columns and beams.     

Analysis on D2D Heterogeneous Networks with State-Dependent PriorityTraffic

In this work, we consider the performance analysis of state dependent priority traffic and scheduling in device to device (D2D) heterogeneous networks. There are two priority transmission types of data in wireless communication, such as video or telephone, which always meet the requirements of high priority (HP) data transmission first. If there is a large amount of low priority (LP) data, there will be a large amount of LP data that cannot be sent. This situation will cause excessive delay of LP data and packet dropping probability. In order to solve this problem, the data transmission process of high priority queue and low priority queue is studied. Considering the priority jump strategy to the priority queuing model, the queuing process with two priority data is modeled as a two-dimensional Markov chain. A state dependent priority jump queuing strategy is proposed, which can improve the discarding performance of low priority data. The quasi birth and death process method (QBD) and fixed point iteration method are used to solve the causality, and the steady-state probability distribution is further obtained.Then, performance parameters such as average queue length, average throughput, average delay and packet dropping probability for both high and low priority data can be expressed. The simulation results verify the correctness of the theoretical derivation. Meanwhile, the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.     

OFDM水声通信下行非正交多址接入功率分配方法研究

针对基于功率域非正交多址接入（Power Domain Non-orthogonal Multiple Accesses,PD-NOMA）的正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）水声下行通信系统的功率分配问题,提出了一种基于中断概率的功率分配方法。用户节点在系统初始化阶段根据源节点广播的组网数据包获取水声信道的统计特征,源节点根据水下用户反馈的信道特征参数建立水下用户的中断概率模型,以最小化两用户的中断概率和为目标建立目标函数,在中断概率区域边界上遍历搜索最优的功率分配系数。仿真结果表明,该方法在保证公平性的条件下,有效降低了用户节点的中断概率,提高了系统的频谱利用率和误码性能。     

Unipolar codes for optical spectral-amplitude code-division multiple-access systems based on combinatorial designs

A novel class of optical signature codes based on combinatorial designs is proposed for optical spectral-amplitude code-division multiple-access (CDMA) systems. It is applicable to both synchronous and asynchronous incoherent optical CDMA and is compatible with both frequency-encoded and time-spreading schemes. Simplicity of construction, larger code cardinality and larger flexibility in cross-correlation (CC) control make the proposed code family an interesting candidate for future optical CDMA applications that require a large number of simultaneous users. It has been shown that the system performance can be significantly improved by using the proposed codes with ideal in-phase CC in preference to Hadamard codes.     

Improved Enhanced Dbtma with Contention-Aware Admission Control to Improve the Network Performance in Manets

DBTMA relies entirely on RTS/CTS dialogue for un-collided transmission of data. The purpose is to improve the QoS at MAC layer by developing it over 802.11e standard. However, DBTMA does not guarantee real-time constraints without efficient method for controlling the network loads. The main challenges in MANETs include prediction of the available bandwidth, establishing communication with neighboring nodes and predicting the consumption of bandwidth flow. These challenges are provided with solutions using Contention-Aware Admission Control (CACP) protocol. In this paper, the EDBTMA protocol is combined with CACP protocol that introduces bandwidth calculation using admission control strategy. The calculation includes certain metrics like: admission control and bandwidth consumption. To compute the bandwidth of channel, bandwidth utilization and traffic priority is distinguished through dual busy tone is proposed. This operates distinctly on its own packet transmission operation. This CACP mechanism defends the conventional traffic flows from new nodes and based on the measured status information of the channel, it QoS of the admitted flows is maintained. This ensures maximum amount of bandwidth flows accommodated by resources and determines the resources in a system meet the new flow requirements while maintaining existing bandwidth flow levels.     

Packet contention resolution in slotted optical packet switch using ant-colony based algorithm

An ant-based contention resolution scheme for the slotted optical packet switched networks has been proposed, and the optimal number of fibre delay lines (FDLs) used in the switch under various traffic loads is investigated. The proposed algorithm can makes FDLs and output port assignment so as to improve the cell-loss rate under various traffic loads. It is found for traffic loads 0.9, 0.6, 0.3, the optimum value for FDL is 64 128 and 128.     

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.