Implementation of a bandwidth allocation scheme in a token-passingfieldbus network

This paper presents a method for implementing a bandwidth allocation scheme on Profibus that operates on a token-passing discipline basis. In order to implement the bandwidth allocation scheme, this study incorporates the following additional functions to the fieldbus datalink layer (FDL) protocol of Profibus. First, the medium bandwidth of the network system is separated into both periodic and time-available intervals, and, second, node timers are synchronized over a local link. The validity of this bandwidth allocation scheme is determined using an experimental model of a network system. The results obtained from the experimental model show that the proposed scheme restricts the delay of both periodic and time-critical data to a pre-specified bound. The proposed bandwidth allocation scheme also fully utilized the bandwidth resource of the network system     

Adaptive wavelet-based multifractal model applied to the effective bandwidth estimation of network traffic flows

The authors investigate effective bandwidth estimation and Quality of Service (QoS) aware bandwidth provisioning for multifractal network traffic flows. They develop a novel adaptive wavelet-based multifractal model (AWMM) by using properties of the wavelet coefficients of multifractal cascade processes. The proposed AWMM has real-time updating capability and proves to be efficient in capturing multifractal network traffic characteristics. In addition, the authors derive an analytical expression for the effective bandwidth estimation of AWMM traffic flows, capable of being used to meet desired byte loss probabilities. Finally, they present an online effective bandwidth estimation algorithm that is incorporated into an adaptive bandwidth provisioning scheme and comparatively evaluated against some other bandwidth allocation methods.     

一种基于节目流行度的自适应流调度方案

提出了一种基于节目流行度的自适应流调度方案。该方案根据节目点播请求的强度自适应地调整分配给节目的信道数和带宽,并给出了在信道数改变过程中如何实现信道平滑过渡的方法。该方案综合了周期广播算法和流合并算法的优点。实验表明,采用此方案,在点播请求很少时能获得同流分并算法（如补丁算法）一样的性能,在点播请求很多时又有和周期广播算法一样少的服务带宽要求。     

Network lifetime-aware data collection in Underwater Sensor Networks for delay-tolerant applications

Development of energy-efficient data collection and routing schemes for Underwater Wireless Sensor Networks (UWSNs) is a challenging issue due to the peculiarities of the underlying physical layer technology. Since the recharging or replacement of sensor nodes is almost impossible after deployment, the critical issue of network lifetime maximization must be considered right from the beginning of designing the routing schemes. We propose a mobile sink (MS)-based data collection scheme that can extend network lifetime, taking into account power-constrained sensor nodes, partitioned networks with geographically distant data collection points and periodic monitoring applications with delay-tolerance. Lifetime extension is achieved by mitigating the ‘sink neighbourhood problem’ and by deferring the data transmissions until the MS is at the most favourable location for data transfer. Unlike the models available for terrestrial WSNs, we consider non-zero travel time of the MS between data collection points, thus making our model more realistic for UWSNs, both connected and partitioned. The performance of the proposed mobility-assisted data collection scheme is thoroughly investigated using both analytical and simulation models. The analytical results are compared to those of existing models to assess their effectiveness and to investigate the trade-offs. Results show that, with a network size of 60 nodes, the network lifetime achieved by the proposed model is 188% higher than that of static sink model and 91% higher than that of mobile sink model (MSM). The proposed maximum lifetime routing scheme is implemented in the network simulation platform OMNET++, for validating the analytical results as well as for evaluating other performance metrics that are not tractable via analytical methods. Both analytical and simulation results demonstrate the superiority of the proposed model in capturing realistic network conditions and providing useful performance indicators prior to network deployment.     

A distributed measurement architecture for industrial applications

In this paper, a distributed digital measurement architecture for industrial applications is proposed. The architecture is arranged on three hierarchical communication levels: the fieldbus, the intranet, and the Internet. Particular attention has been paid to the lower level, the field level, implemented using a low-priced smart front-end. It is based on the H8/3048F Hitachi microcontroller and embodies a fieldbus interface (I/F). The same board can be linked to a VXIbus controller by means of a suitable register-based interface. The proposed network can embody a number of analog signal conditioning circuits, processor, and communication capabilities, to meet the industrial needs. We propose two applications of this distributed measurement architecture: the monitoring of power quality in an electrical distribution network and the management of a water distribution system. Experimental results showing the system performance are also included in the paper.     

An Adaptive Power Allocation Scheme for Performance Improvement of Cooperative SWIPT NOMA Wireless Networks

Future wireless networks demand high spectral efficiency, energy efficiency and reliability. Cooperative non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) is considered as one of the novel techniques to meet this demand. In this work, an adaptive power allocation scheme called SWIPT based adaptive power allocation (SWIPT-APA-NOMA) is proposed for a power domain NOMA network. The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power. A detailed analysis on the bit error rate (BER) performance of the proposed scheme is done and closed form expression is obtained. Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme. It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme. Further, it offers 96.06% improvement in the capacity for a cumulative noise figure and fading margin of 10 dB.     

Mobile agent based approach for QoS routing

A mobile agent based on-demand quality of service (QoS) unicast routing scheme for supporting multimedia applications is proposed that considers bandwidth, delay and packet loss as QoS metrics for feasible path computation. A mobile agent is employed to find multiple QoS paths and select a best path among them to preserve resources so as to increase call success ratio and network bandwidth utilisation as well as adapt to network dynamics. The scheme is simulated in various network scenarios (sparse and dense networks) to verify performance and operation effectiveness, and compared with RSVP-based QoS routing by using an internet routing protocol. The results demonstrate significant improvements in call success ratio and network bandwidth utilisation compared with RSVP-based QoS routing, both in case of sparse and dense networks. Benefits of the agent-based scheme are adaptability, flexibility, and support for component-based software engineering features such as software reuse, customisation and maintainability     

Darwinian approach for dynamic spectrum allocation in next generation systems

The authors present the use of a genetic algorithm (GA) model as a solution approach to the dynamic spectrum allocation (DSA) problem considered as a difficult combinatorial optimisation problem. The proposed multi-objective GA model enhances overall spectral efficiency of the network, while optimising its own spectrum utilisation to generate accessible spectrum opportunities for other radio technologies. A novel two-dimensional encoding technique is defined to represent solutions in the problem domain and the technique enables significantly shorter convergence times. A simulation tool has been developed to model the GA-based DSA and to compare the new scheme with the conventional fixed spectrum allocation (FSA) scheme under both uniform and non-uniform traffic distributions. The proposed scheme significantly outperformed the FSA scheme both in terms of spectral efficiency gain and spectral utilisation.     

基于随机逼近动态带宽分配的CAC研究

ATM网络中，基于动态带宽分配的CAC，即可以提高ATM网络资源的利用率又能保证业务的QoS要求。本文运用自适应随机逼近算法研究了ON／OFF信源模型的带宽估计及接入问题，数值计算的结果表明，随机逼近能较好地逼近实际值，与社会网络方法相比，随机逼近算法的特点是不需要离线训练，也不需要已准好的样本，这能在网络实际运行中自动调整自动收敛。     

Effective transmission opportunity allocation scheme for real-time variable bit rate traffic flows with different delay bounds

The medium access control of IEEE 802.11e defines a novel coordination function, namely, hybrid coordination function (HCF), which allocates transmission opportunity (TXOP) to stations taking their quality of service (QoS) requirements into account. However, the reference TXOP allocation scheme of HCF controlled channel access, a contention-free channel access function of HCF, is only suitable for constant bit rate traffic. For variable bit rate traffic, packet loss may occur seriously. The authors propose a TXOP allocation scheme to efficiently allocate bandwidth and meet the QoS requirements in terms of both delay bound and packet loss probability. To achieve high bandwidth efficiency, the authors take advantage of not only intra-flow multiplexing gain of traffic flows with large delay bounds, but also inter-flow multiplexing gain of multiple traffic flows with different delay bounds. According to numerical results obtained by computer simulations, the proposed TXOP allocation scheme results in much higher bandwidth efficiency than previous algorithms under the same constraints of delay bounds and packet loss probability.     

EPON上行接入动态带宽分配算法的研究

以太无源光网络的上行方向需要一种多址接入技术来防止以太数据包的碰撞。时分多址技术应用广泛,而波分多址技术极具潜力,是发展的方向。基于时分多址技术,提出了一种改进的动态带宽分配算法,结合了轮询机制和申请的优先级。通过建模仿真,证明了该算法可以取得较小的平均包延时和较高的带宽利用率。     

5G异构接入网系统频谱资源的统一化表示及动态分配

针对5G通信网络系统提供以大容量、高速率、低时延为主要特征的服务导致频谱资源紧缺现象日趋严重的问题,进行了5G频谱资源动态分配的研究,给出了5G异构接入网频谱资源特征描述、表达方法和一种基于双层优化的动态频谱分配方案。仿真实验结果表明,给出的动态频谱分配方案在系统吞吐量和分配公平性两个指标上均有较好表现,具有较好应用价值。     

Transmission Control under Multi-Service Disciplines in Wireless Sensor Networks

The wireless sensor network (WSN), as the terminal data acquisition system of the 5G network, has attracted attention due to advantages such as low cost and easy deployment. Its development is mainly restricted by energy. The traditional transmission control scheme is not suitable for WSNs due to the significant information interaction. A switchable transmission control scheme for WSNs based on a queuing game (SQGTC) is proposed to improve network performance. Considering that sensor nodes compete for the resources of sink nodes to realize data transmission, the competitive relationship between nodes is described from the perspective of a game. Different types of sensor node requests require a sink node to provide different service disciplines. Mathematical models of social welfare are established for a sink node under the service disciplines of first-come, first-served (FCFS), egalitarian processor sharing (EPS), and shortest service first (SSF). The optimal service strategies are obtained by maximizing social welfare. The sensor nodes provide the expected benefits and satisfy the service requirements of the requests, and the sink node switches the transmission control strategy for the service. Simulation results show that the proposed scheme improves the data transmission efficiency of WSNs and achieves the optimal allocation of resources.     

Channel estimation and interference cancellation in CP?CDMA systems

A novel iterative channel estimation approach is proposed for cyclic prefix-code division multiple access systems. Code-multiplexed pilots are used for channel estimation while maintaining bandwidth efficiency. The proposed method achieves a significant improvement when compared to the conventional correlation approach by reconstructing data signals for channel estimation. Simulation results demonstrate good estimation capability with an allocation of only 10% of the whole power to the pilot channel. In addition, an integrated channel estimator and parallel interference cancellation (PIC) detector are proposed. Data signals are reconstructed for channel estimation while the interference contributed by different data channels as well as the pilot channel are regenerated and subtracted from the received signal at the final stage. The channel estimation error reduces at each iteration and the PIC at the last stage enables further bit error rate performance improvement to be achieved for the system. The performance of the proposed scheme is studied through simulations and results verify its effectiveness     

一种新型的基于数据平面共享环的IP over ASTN机制

提出了一种重叠模型下新型的基于数据平面共享环的IP over ASTN机制,其优点是利用IP网络中路由器自身具备的能力和在ASTN边缘节点引入基于以太网的二层交换能力,以较低的环路带宽代价实现各IP网间可达性信息传达,同时避免了对路由器的基本运行机制的较复杂修改。分析了相应的组网形式、边缘节点结构和网络运行机制,并对其中具有关键意义的带宽限制参数提出两种参数确定算法。     

Resource Allocation in Edge-Computing Based Wireless Networks Based on Differential Game and Feedback Control

In this paper, we have proposed a differential game model to optimally solve the resource allocation problems in the edge-computing based wireless networks. In the proposed model, a wireless network with one cloud-computing center (CC) and lots of edge services providers (ESPs) is investigated. In order to provide users with higher services quality, the ESPs in the proposed wireless network should lease the computing resources from the CC and the CC can allocate its idle cloud computing resource to the ESPs. We will try to optimally allocate the edge computing resources between the ESPs and CC using the differential game and feedback control. Based on the proposed model, the ESPs can choose the amount of computing resources from the CC using feedback control, which is affected by the unit price of computing resources controlled by the CC. In the simulation part, the optimal allocated resources for users’ services are obtained based on the Nash equilibrium of the proposed differential game. The effectiveness and correctness of the proposed scheme is also verified through the numerical simulations and results.     

Intelligent Adaptive Backstepping Control System for Magnetic Levitation Apparatus

We propose an intelligent adaptive backstepping control system using a recurrent neural network (RNN) to control the mover position of a magnetic levitation apparatus to compensate for uncertainties, including friction force. First, we derive a dynamic model of the magnetic levitation apparatus. Then, we suggest an adaptive backstepping approach to compensate disturbances, including the friction force, occurring in the motion control system. To further increase the robustness of the magnetic levitation apparatus, we propose an RNN estimator for the required lumped uncertainty in the adaptive backstepping control system. We further propose an online parameter training methodology, derived by the gradient descent method, to increase the learning capability of the RNN. The effectiveness of the proposed control scheme has been verified by experiment. With the proposed adaptive backstepping control system using RNN, the mover position of the magnetic levitation apparatus possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic trajectories     

Mean Opinion Score Estimation for Mobile Broadband Networks Using Bayesian Networks

Mobile broadband (MBB) networks are expanding rapidly to deliver higher data speeds. The fifth-generation cellular network promises enhanced-MBB with high-speed data rates, low power connectivity, and ultra-low latency video streaming. However, existing cellular networks are unable to perform well due to high latency and low bandwidth, which degrades the performance of various applications. As a result, monitoring and evaluation of the performance of these network-supported services is critical. Mobile network providers optimize and monitor their network performance to ensure the highest quality of service to their end-users. This paper proposes a Bayesian model to estimate the minimum opinion score (MOS) of video streaming services for any particular cellular network. The MOS is the most commonly used metric to assess the quality of experience. The proposed Bayesian model consists of several input data, namely, round-trip time, stalling load, and bite rates. It was examined and evaluated using several test data sizes with various performance metrics. Simulation results show the proposed Bayesian network achieved higher accuracy overall test data sizes than a neural network. The proposed Bayesian network obtained a remarkable overall accuracy of 90.36% and outperformed the neural network.     

Efficiency measurement for mixed two-stage nonhomogeneous network processes with shared extra intermediate resources

Unreasonable allocation of shared resources reduces the system efficiency and is a considerable operational risk. Sub-processes with insufficient portion of shared resources could not help accomplish complicated tasks, and overstaffing and idle resources will occur in the sub-processes assigned with redundant shared resources. This unfair portion distribution may cause internal contradictions among sub-processes and even lead to the collapsing of the entire system. This study proposes a data-driven, mixed two-stage network data envelopment analysis model. This method aims to reasonably define the allocation portion of shared extra intermediate resources among several nonhomogeneous subsystems and measure the overall system performance. A data set of 58 international hotels is used to test the features of the proposed model.