基于服务拓扑切分机制的无线传感网虚拟映射算法

为解决无线传感网部署过程中存在资源调度困难、映射成功率较低及传输性能不佳等问题,提出了一种基于服务拓扑切分机制的无线传感网虚拟映射算法。首先,基于图论思想,构建了物理网络与虚拟网络的映射关系,将网络按能耗、带宽、时延等指标进行切分,再构建多约束评估机制,达到整合优化评估网络映射的效果。随后,将业务请求拆分为若干个拓扑服务片,对传输链路进行逐项映射,并结合时延最小化原则对链路匹配排序,将业务进行精准匹配并优化传输质量。依据节点能耗及节点剩余能量最优匹配原则,选取服务能力最佳的节点。最后,构建多参数评估机制,将带宽较高且时延较低的链路置于较高优先级别并进行匹配带宽映射,进而提高网络传输及服务承载性能。仿真实验表明,与常用的网络虚拟映射算法相比,所提算法具有更高的节点链路映射成功率和网络传输带宽,以及更低的节点能耗。     

基于GSA算法的WVN资源映射数学模型

由于传统方法没有从满足成本最小需求角度出发,建立虚拟网络映射目标,导致底层链路利用率较高,剩余带宽较低以及请求接受率不高的问题,于是研究基于GSA算法的无线虚拟网络资源映射数学模型.充分考虑无线虚拟网络资源映射成本、映射收益以及虚拟网络请求接受率建立数学模型,设置节点CPU资源约束、节点映射位置约束、链路带宽资源约束等...     

基于多链路故障的网络切片生存性算法

为了保证当底层网络的多条物理链路发生故障时用户业务能够不间断,提出一种基于多链路故障的网络切片生存性算法。通过区分切片上承载的业务类型,当高可靠低延迟切片请求到达后,将物理节点按节点重要度排序后进行映射,再对故障链路采用多备份路径算法,选取带宽资源消耗最少的路径依次对故障链路进行重映射,当高带宽切片请求到达后,采用广度优先搜索的节点映射算法,再通过多备份路径对故障链路进行恢复。仿真结果表明,该算法能够提高切片平均映射成功率、长期平均收益开销比、物理链路利用率和故障恢复率,缩短平均故障恢复时延。     

基于风险均衡度的电力5G通信链路自动选择方法研究

为有效自动选择通信链路，降低通信全局风险度，提出了一种基于风险均衡度的电力5G通信链路自动选择方法。首先，以最低全局风险度、最高业务通道可用性为目标函数，以通道带宽、时延与丢包率为约束条件，建立电力5G通信链路自动选择模型。以业务风险度与网络业务风险均衡度等为指标，评估业务风险度。按照风险度大小，由低至高排序通信业务，利用通信链路自动选择模型，优先为风险度较低的业务选择链路。通过量子遗传算法求解通信链路自动选择模型，获取最低全局风险度与最高业务通道可用性值，完成通信链路自动选择。实验证明：该方法可有效获取各通信业务风险度，自动选择通信链路，降低全局风险度，提升业务通道可用性和通道带宽，减少通道时延与丢包率，风险均衡效果较优。     

多重链路时延优化动态可用带宽分配算法

为了优化多重链路多业务环境下的时延,首先分析了带宽分配及链路中数据传输时延计算方法,提出一种时延优化的动态可用带宽分配算法(DODBA)。该算法基于不同优先级业务的时延比较实现了剩余可用带宽的重新分配。仿真实验证明了DODBA的有效性,能控制各链路不同业务的时延,并提高了系统带宽资源的利用率。DODBA可用于解决大型宽带网络接入控制中的实际问题。     

基于Kalman优化的MPEG-4视频业务模型

提出了一种支持MPEG-4可比特率视频业务模型，用Kalman优化的方法，对未来帧进行线形预测，而不需要更多的先验信息，进行动态带宽分配，提高带宽的利用率，用这种方法，对MPEG-4业务进行建模，并利用该模型讨论了在不同带宽利用率的情况下丢包情况，实验仿真结果表明，该方法与实际视频业务在相同条件下的丢包率误差较小，适于实时视频业务的预测与资源预留。     

企业级网络虚拟映射带宽与能耗优化平衡策略

利用现有的网络环境运行大规模数据分析和处理任务是企业当前的实际需求。满足需求的途径之一是网络虚拟化技术。相比于云平台虚拟网络映射以最大化收益为出发点,企业级网络虚拟映射要以降低运行费用为目标,同时考虑节点间链路的带宽小的特点。以能源和带宽消耗优化为目标,建立了整数线性规划模型,第一步确定虚拟节点和链路映射到底层物理节点和链路的位置,第二步确定采用哪条链路传输所需镜像。实验参数来源于实际值,分析了单一优化模型和本文模型在实验数值上的差异,最终证明本文模型可以在带宽消耗优化和能耗消耗优化取得较好的平衡。     

面向物联网的能耗感知虚拟网络映射算法

物联网中传感器节点间规模庞大的数据交互使得能耗过大问题日趋严重,传统能耗感知算法无法适用于节点能耗不均的物联网环境。针对该问题,重新构建基于无线传感器网络的能耗模型,在考虑节点异构性和链路时效性的同时保证能耗最小。在此基础上,提出一种改进的能耗感知虚拟网络映射算法,在节点映射阶段,基于最接近剩余容量原则将虚拟节点映射至同类型且能耗最小的物理节点上,并为不同时延下的链路分配合适的资源。仿真结果表明,相比EA-VNE、EA-VNEH算法,该算法通过资源整合的方式,可以提高底层资源利用率,降低虚拟网络映射能耗,且随着引入参数的增加,能够实现更细粒度的资源分配。     

基于SDN与NDN的卫星网络多约束路由算法

针对NDN卫星网络内容传输时延高、丢包率高且请求命中率低的问题,提出了一种基于SDN与NDN的卫星网络多约束路由算法,并命名为SNMcRA。基于SDN的集中控制与全局视图,通过建立多约束路由模型,将链路多约束信息与蚁群算法相结合以求解满足时延、带宽、丢包率多约束的代价最小路径,由节点在包转发的过程中动态完成转发表FIB和待定请求表PIT的构建。实验结果表明,该算法与DSP算法相比时延降低了35%,带宽利用率提升了29%,丢包率降低了17%,并且在请求命中率方面也具有显著优势。     

基于业务类型的网络切片可靠性映射算法

网络切片是5G网络的基础架构技术,为在多个切片共享同一底层网络资源的同时保证切片的可靠性,提出一种区分业务类型的网络切片可靠性映射算法,解决底层网络链路故障、网络切片可靠性与资源利用率相互矛盾的问题。通过区分切片承载业务类型,对高可靠低时延切片请求的链路提前构建备份路径,并采用基于最大生成树链路的备份资源共享保护方法,对高带宽切片请求则采用基于链路可靠性的重映射算法恢复故障链路。仿真结果验证了该算法的有效性,与SVNE1+1和DPS-VNRA算法相比,其在切片成功运行率、长期收益开销比、物理链路利用率和故障恢复率方面均具有优势。     

Analysis of link-level hybrid FEC/ARQ-SR for wireless links and long-lived TCP traffic

Since the TCP protocol uses the loss of packets as an indication of network congestion, its performance degrades over wireless links, which are characterized by a high bit error rate. Different solutions have been proposed to improve the performance of TCP over wireless links, the most promising one being the use of a hybrid model at the link level combining Forward Error Correction (FEC), Automatic Repeat Request with Selective Repeat (ARQ-SR), and an in-order delivery of packets to IP. The drawback of FEC is that it consumes some extra bandwidth to transmit the redundant information. ARQ-SR consumes extra bandwidth only when packets are lost, its drawback is that it increases the round-trip time (RTT), which may deteriorate the performance of TCP. Another drawback of ARQ-SR is that a complete packet can be retransmitted to correct a small piece of errored data. We study in this paper the performance of TCP over a wireless link implementing hybrid FEC/ARQ-SQ. The study is done by simulating and modeling long-lived TCP transfers over wireless links showing Bernoulli errors. We are motivated by how to tune link-level error recovery, e.g. amount of FEC, persistency of ARQ, so as to maximize the performance of TCP. We provide results for different physical characteristics of the wireless link (delay, error rate) and for different traffic loads (number of TCP connections).     

一种基于带宽估计的无线网拥塞控制机制

针对无线网提出了一种基于带宽估计的拥塞控制机制。该机制利用TCP确认帧携带的数据包到达时间来估算包到达速率，从而得到带宽的估计值。在此基础上用带宽的估计值更新拥塞窗口，避免在发生链路错误时启动拥塞控制机制，由此提高了TCP在无线网上的性能。实验结果表明，算法能减少链路差错对TCP性能带来的影响，提高了TcP在无线网上的吞吐率。     

一种新的基于IMS的SIP重传机制

目前，IP多媒体子系统（IMS）中基于会话初始化协议（SIP）的会话建立时间受到无线信道约束带宽、帧错误率（FER）值的影响，交换的消息数量、消息长度以及重传机制对于会话建立的时延有很大的影响，延长了会话建立的时间。将基于SIP的会话建立与无线信道的性能结合，提出一种新的SIP自适应重传机制。实验结果表明，该重传机制缩短了会话建立的时间，对IMS端到端的服务质量（QoS）性能有明显的改善。     

Joint routing, scheduling, and power control for multichannel wireless sensor networks with physical interference

Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor networks. In this paper, we develop a distributed and online algorithm that jointly solves multipath routing, link scheduling, and power control problem, which can adapt automatically to the changes in the network topology and offered load. We particularly focus on finding the resource allocation that realizes trade-off among energy consumption, end-to-end delay, and network throughput for multichannel networks with physical interference model. Our algorithm jointly considers 1) delay and energy-aware power control for optimal transmission radius and rate with physical interference model, 2) throughput efficient multipath routing based on the given optimal transmission rate between the given source-destination pairs, and 3) reliable-aware and throughput efficient multichannel maximal link scheduling for time slots and channels based on the designated paths, and the new physical interference model that is updated by the optimal transmission radius. By proving and simulation, we show that our algorithm is provably efficient compared with the optimal centralized and offline algorithm and other comparable algorithms.     

基于TCP友好速率控制和前向纠错的MPEG-2视频传输

针对Internet视频传输面临拥塞控制和数据包丢失的问题，结合TCP友好的速率控制算法和前向纠错机制建立视频传输的分层体系构架和控制策略。传输体系同时采用以GOP为基本分析单元的视频帧速率预测模型，实现根据网络丢包率的变化动态地优化配置前向纠错的冗余信息。实验证明，传输体系采用动态优化的前向纠错能实时地适应带宽的变化，有效地降低数据包丢失带来的影响，从而改善视频回放质量。     

Bandwidth allocation for video transmission with differentiated quality of experience over wireless networks

Delivering digital video content with enhanced quality of experience to the end users over error-prone multi-hop wireless networks is a challenging issue. In video transmission over such wireless networks, many network-based (packet loss, delay, etc.) and source-based (encoding quantization level etc.) parameters can impose some levels of impairment on the perceived video quality. In a video quality enhancement strategy, accurate video quality metrics play a crucial role in the designing process of optimal rate (bandwidth) allocation algorithms. Many cross-layer optimization (CLO) based rate allocation strategies have been developed for this purpose which consider different objective functions (congestion level, total packet loss, etc.) in wireless networks. The main contributions of the proposed work are twofold. At first, an optimal bandwidth allocation framework is being developed in which based on some network-specific constraints and by incorporating an accurate video quality metric, the total weighted quality of experience of some competing video sources is being optimized bases on cross-layer design techniques. Secondly, these optimal rates have been used for differentiated Quality of Experience (QoE) enforcement between multiple competing video sources. The resulting optimal rates can be used as rate-feedbacks for on-line rate adaptation of a moderate video encoder such as MPEG4. The aforementioned weight parameters are selected based on the importance of each video sequence’s quality and can be associated with some previous service level agreement (SLA) based prices. Some numerical analysis have been presented to validate the theoretical results and to verify the claims.     

Real-time video streaming over multipath in multi-hop wireless networks

Given the limited wireless link throughput, high loss rate, and varying end-to-end delay, supporting video applications in multi-hop wireless networks becomes a challenging task. Path diversity exploits multiple routes for each session simultaneously, which achieves higher aggregated bandwidth and potentially decreases delay and packet loss. Unfortunately, for TCP-based video streaming, naive load splitting often results in inaccurate estimation of round trip time (RTT) and packet reordering. As a result, it can suffer from significant instability or even throughput reduction, which is also validated by our analysis and simulation in multi-hop wireless networks. To make real-time TCP-based streaming viable over multi-hop wireless networks, we propose a novel cross-layer design with a smart traffic split scheme, namely, multiple path retransmission (MPR). MPR differentiates the original data packets and the retransmitted packets and works with a novel QoS-aware multi-path routing protocol, QAOMDV, to distribute them separately. MPR does not suffer from the RTT underestimation and extra packet reordering, which ensures stable throughput improvement over single-path routing. Through extensive simulations, we further demonstrate that, as compared with state-of-the-art multi-path protocols, our MPR with QAOMDV noticeably enhances the TCP streaming throughput and reduces bandwidth fluctuation, with no obvious impact to fairness.     

Adaptive hybrid error correction model for video streaming over wireless networks

The Hybrid ARQ (HARQ) mechanism is the well-known error packet recovery solution composed of the Automation Repeat reQuest (ARQ) mechanism and the Forward Error Correction (FEC) mechanism. However, the HARQ mechanism neither retransmits the packet to the receiver in time when the packet cannot be recovered by the FEC scheme nor dynamically adjusts the number of FEC redundant packets according to network conditions. In this paper, the Adaptive Hybrid Error Correction Model (AHECM) is proposed to improve the HARQ mechanism. The AHECM can limit the packet retransmission delay to the most tolerable end-to-end delay. Besides, the AHECM can find the appropriate FEC parameter to avoid network congestion and reduce the number of FEC redundant packets by predicting the effective packet loss rate. Meanwhile, when the end-to-end delay requirement can be met, the AHECM will only retransmit the necessary number of redundant FEC packets to receiver in comparison with legacy HARQ mechanisms. Furthermore, the AHECM can use an Unequal Error Protection to protect important multimedia frames against channel errors of wireless networks. Besides, the AHECM uses the Markov model to estimate the burst bit error condition over wireless networks. The AHECM is evaluated by several metrics such as the effective packet loss rate, the error recovery efficiency, the decodable frame rate, and the peak signal to noise ratio to verify the efficiency in delivering video streaming over wireless networks.     

多节点共享保障时隙分配策略

在现代工业无线网络中,IEEE 802.15.4标准以其独特的低功耗、低成本特点被广泛应用。IEEE 802.15.4可以提供最低0.006%的占空比,最大限度降低功耗,同时提供的保障时隙GTS机制为节点提供了实时服务保障。然而,在为大规模节点提供保障时,IEEE 802.15.4提供的GTS机制缺乏灵活性,只能为有限节点提供实时保障服务。本文针对这一问题提出一种多节点共享保障时隙分配策略,允许多个数据流在满足延迟需求前提下,共享同一个GTS减少带宽浪费。分析表明,多节点共享的保障时隙分配策略与普通分配方法相比,可有效提高带宽利用率。     

An adaptive neural network admission controller for dynamicbandwidth allocation

In an access node to a hybrid-switching network (e.g., a base station handling the downlink in a cellular wireless network), the output link bandwidth is dynamically shared between isochronous (guaranteed bandwidth) and asynchronous traffic types. The bandwidth allocation is effected by an admission controller, whose goal is to minimize the refusal rate of connection requests as well as the loss probability of packets queued in a finite buffer. Optimal admission control strategies are approximated by means of backpropagation feedforward neural networks, acting on the embedded Markov chain of the connection dynamics. The case of unknown, slowly varying, input rates is explicitly considered. Numerical results are presented, comparing the approximation with the optimal solution obtained by dynamic programming.