A Compressed Sensing Based DV-Hop Location Algorithm for Wireless Sensor Networks

A compressed sensing based DV-hop location algorithm is presented to improve the performance of the conventional DV-hop location algorithm in WSNs （wireless sensor networks）. The sensor network can be divided into multiple grids. Compared with the grid number, the number of targets in the network is generally sparse. Therefore, the localization of the targets in the network can be transformed into a sparse signal reconstruction issue. Theoretical analysis and experimental results on the proposed algorithm show that it is able to greatly reduce the amount of data flow in the network, balance the load of communication, prolong the lifetime of the WSNs, and improve the target location accuracy, compared to the DV-hop location ones.     

Efficiency/Fairness Tradeoffs in Networks with Wireless Components and Transient Congestion

Our work explores the impact of aggressive/conservative congestion control strategies on the fairness and efficiency of reliable transport protocols, in a wired/wireless environment. Based on experiments, we study the behavior of congestion control mechanisms in response to wireless errors, and transient congestion caused by a small number of competing flows. We show that: (i) the traditional TCP algorithm proves to be inadequate in terms of efficiency and fairness when random wireless errors occur in the network and, (ii) an aggressive strategy does not necessarily yield better performance. On the contrary, in the combined presence of transmission errors and transient congestion a conservative strategy appears superior.     

无线传感器网络的拥塞控制技术

无线传感器网络的多对一通信方式、无线链路的相互干扰、网络的动态变化和资源受限等特性,使得无线传感器网络容易出现拥塞,严重影响网络的QoS传输性能和生存周期,因此拥塞控制成为无线传感器网络服务质量保障机制的关键技术之一.在分析无线传感器网络特点的基础上,说明了拥塞检测和拥塞避免的策略,重点介绍和分析了基于速率控制、流量调度和传输调度等典型的拥塞解除算法,最后对拥塞控制技术的发展趋势进行了展望.     

Ad Hoc无线网络跨层设计综述

为了进一步适应Ad hoe无线网络环境下各种应用的需要,提高网络性能,Ad hoe无线网络的跨层设计已成为目前国内外网络研究的热点和难点问题之一。给出了Adhoe无线网络跨层设计的定义,分析了跨层设计的原因、优势和主要技术;对跨层设计的方法进行了分类,主要包括四种方法：层间传递相关信息,联合优化网络相关层,融合相邻层,分层作为网络最优化分解,并对它们进行了分析比较和评价;最后探讨了Adhoe无线网络跨层设计面临的挑战和今后的研究方向。     

基于Jacobi ADMM的传感网分布式压缩感知数据重构算法

针对无线传感网中分布式数据收集及应用,采用分布式压缩感知理论中的JSM-1 (joint sparse model-1)模型,提出了一种基于Jacobi ADMM (alternating direction method of multipliers)的分布式压缩感知数据重构算法.该算法通过在簇头节点间交换公共信息以挖掘关联数据集的公共部分,并在各个簇头节点内部更新各自的独立部分,从而实现无线传感网中相关感知数据的分布式压缩重构.首先,将无线传感网中的数据收集问题抽象为一个分布式优化问题.然后,为了能够有效地解决分布式计算过程中产生的不收敛问题,在优化目标函数中引入了近似项,从而使得子优化问题具有严格凸性,并利用交替方向乘子法求解压缩感知数据的重构问题.最后,分别利用合成数据集和真实数据集进行验证.实验结果表明：与现有其他数据重构算法相比,基于Jacobi ADMM的分布式压缩感知数据重构算法具有更高的数据重构精度.     

强动态Ad Hoc网的拥塞控制:价格协作和滚动优化

Ad Hoc网络存在着无线多跳连接、节点移动这两个本质的特点.前者引起了与固定网络截然不同的信息流竞争新特点,后者导致了网络状态不断发生变化.首先,在采用链路干扰集描述信息流竞争特点的基础上,将小时间段内网络状态不变的拥塞控制问题表达成非线性优化问题;其次,运用基于对偶分解理论的价格协作法PCA(price cooperation approach)求解该优化问题,构建了一个基于链路干扰集的价格框架.同时,运用队列长度监控、邻居集合近似和HELLO捎带信息这3种技术将PCA转化成在实际Ad Hoc网络环境中可实施的协议.另一方面,运用状态检测和滚动优化方法,有针对性地解决Ad Hoc网络状态不确定时变性带来的问题,相应地设计了自适应优化策略AOS(adaptive optimization strategy).MATLAB仿真结果表明,AOS策略比PCA对网络状态的变化具有更好的自适应性能.NS仿真实验结果表明了PCA和PCA AOS在几乎所有的仿真场景和移动环境下,在重要的性能指标,包括吞吐量、丢包率、公平性等方面,都比TCP,ATCP和ATP有了明显的改进.     

无人机无线网络中基于队列稳定的无线与计算资源分配优化

无人机(UAV)无线网络中,UAV承载基站设备,可灵活提供无线通信服务,支持在高质量的无线信道状态下进行数据传输;另一方面,将边缘计算服务器部署到基站侧,计算资源更靠近用户,通过任务卸载,能够直接在基站侧进行计算处理,缓解无线网络的去程链路压力;但是,考虑到能耗受限问题,如何通过资源优化来降低网络能耗并保证用户到基站的数据传输和任务处理的稳定性依然是研究的难题;针对UAV无线网络中用户向UAV基站发送数据并卸载计算任务的场景,研究了在数据传输和任务处理稳定性约束下进行无线与计算资源优化的能耗最小化问题,构建数据队列与任务队列,采用李雅普诺夫优化理论对问题进行转化和分解,获得能耗与队列的折中关系,并通过仿真分析评估了所提解决方案的有效性。     

无线传感器网络能量优化与建模技术综述

由于无线传感器网络的能量受限,如何优化网络能量消耗和评估网络生存周期是当前无线传感器网络研究的首要挑战。在分析无线传感器网络能量消耗特征的基础上,调研传感器网络节点和网络系统的能量优化策略;并针对能量优化存在的不足,分析近几年兴起的无线传感器网络能耗建模工作;从基于无线通信、状态转换、协议栈等方面归纳总结无线传感器网络能耗模型的建模方法;指出跨层能量优化以及软硬件综合的能耗建模技术是无线传感器网络能量研究的重点。     

Integrated Dynamics Control and Energy Efficiency Optimization for Overactuated Electric Vehicles

A large number of studies have been conducted on the dynamics control of electric vehicles or on the optimization of their energy efficiency but few studies have looked at both of these together. In this study, an integrated dynamics control and energy efficiency optimization strategy is proposed for overactuated electric vehicles, where the control of both longitudinal and lateral dynamics is dealt with while the energy efficiency is optimized. First, considering the trade‐off between control performance and energy efficiency, criteria are defined to categorize the vehicle motion status as linear pure longitudinal motion and non‐linear motion or turning motion. Then different optimization targets are developed for different motion status. For the pure linear longitudinal motion and cornering motion, the energy efficiency and vehicle dynamics performance are equally important and a trade‐off control performance between them needs to be achieved. For the non‐linear turning motion, vehicle handling and stability performance are the primary concerns, and energy efficiency is a secondary target. Based on the defined targets, the desired longitudinal and lateral tyre forces and yaw moment are then optimally distributed to the wheel driving and steering torques. Finally numerical simulations are used to verify the effectiveness of the proposed strategies. The simulation results show that the proposed strategies can provide good dynamics control performance with less energy consumption.     

Internet拥塞控制系统校正控制器的一种新的设计方法

当前Internet拥塞控制系统中,作为闭环拥塞控制系统的校正控制器,采用了AQM(Active Queue Management)控制器技术;AQM控制器中通常采用RED(Random Early Detection)算法,但RED算法存在一系列缺点;文章在校正控制器的设计中,采用状态反馈控制算法,以提高Internet拥塞控制系统的控制性能。内容包括:被控制系统模型、状态反馈控制器设计及状态变量测量等问题;最后通过NS2平台上的仿真计算,验证了所提出方法在动态性能上优于RED算法。     

计算机网络服务质量优化方法研究综述

优化方法为设计更好的计算机网络服务质量保证机制提供了有力的理论支持.相较于传统启发式的网络设计方法,优化方法可以从理论上找到问题的最优解,从而从根本上克服了启发式方法不能证明方案优劣程度的缺陷.因此,基于优化方法的机制设计与性能评价成为了当前网络服务质量领域中的一个前沿研究领域.大量的研究着眼于从优化理论的角度重新建立...     

联合弹性碰撞与梯度追踪的WSNs压缩感知重构

为提高压缩感知(Compressed sensing, CS)大规模稀疏信号重构精度, 提出了一种联合弹性碰撞优化与改进梯度追踪的WSNs (Wireless sensor networks)压缩感知重构算法.首先, 创新地提出一种全新的智能优化算法---弹性碰撞优化算法(Elastic collision optimization algorithm, ECO), ECO模拟物理碰撞信息交互过程, 利用自身历史最优解和种群最优解指导进化方向, 并且个体以N(0, 1)概率形式散落于种群最优解周围, 在有效提升收敛速度的同时扩展了个体搜索空间, 理论定性分析表明ECO依概率1收敛于全局最优解, 而种群多样性指标分析证明了算法全局寻优能力.其次, 针对贪婪重构算法高维稀疏信号重构效率低、稀疏度事先设定的缺陷, 在设计重构有效性指数的基础上将ECO应用于压缩感知重构算法中, 并引入拟牛顿梯度追踪策略, 从而实现对大规模稀疏度未知数据的准确重构.最后, 利用多维测试函数和WSNs数据采集环境进行仿真, 仿真结果表明, ECO在收敛精度和成功率上具有一定优势, 而且相比于其他重构算法, 高维稀疏信号重构结果明显改善.     

Cross‐layer resource control and scheduling for improving interactivity in Android

Android smartphones are often reported to suffer from sluggish user interactions due to poor interactivity. This is partly because Android and its task scheduler, the completely fair scheduler (CFS), may incur perceptibly long response time to user‐interactive tasks. Particularly, the Android framework cannot systemically favor user‐interactive tasks over other background tasks since it does not distinguish between them. Furthermore, user‐interactive tasks can suffer from high dispatch latency due to the non‐preemptive nature of CFS. To address these problems, this paper presents framework‐assisted task characterization and virtual time‐based CFS. The former is a cross‐layer resource control mechanism between the Android framework and the underlying Linux kernel. It identifies user‐interactive tasks at the framework‐level, by using the notion of a user‐interactive task chain. It then enables the kernel scheduler to selectively promote the priorities of worker tasks appearing in the task chain to reduce the preemption latency. The latter is a cross‐layer refinement of CFS in terms of interactivity. It allows a task to be preempted at every predefined period. It also adjusts the virtual runtimes of the identified user‐interactive tasks to ensure that they are always scheduled prior to the other tasks in the run‐queue when they wake up. As a result, the dispatch latency of a user‐interactive task is reduced to a small value. We have implemented our approach into Android 4.1.2 running with Linux kernel 3.0.31. Experimental results show that the response time of a user interaction is reduced by up to 77.35% while incurring only negligible overhead. Copyright © 2014 John Wiley & Sons, Ltd.     

一种提高TCP与UDP数据流公平性的拥塞控制机制

在UDP业务流逐步占据大部分网络带宽的情况下,如何在网络层对UDP包进行拥塞控制显得尤为重要。在网络拥塞时,由于UDP包本身缺乏反馈机制,将会产生严重的丢包或者UDP抢占TCP带宽的现象。文中提出了基于网络层的发送端缓冲队列管理的拥塞控制机制,可以均衡TCP和UDP的带宽使用,同时通过对路由器ICMP网络拥塞报文的处理,建立了高效的流量调节策略,并进行了网络仿真实验。实验结果表明,基于该机制的拥塞控制可以有效改善网络不同业务流带宽使用的不公平性。     

无线多跳网络结合功率控制的物理载波侦听分析模型

载波侦听阈值的选取对无线多跳网络MAC层的协议性能有着重要影响.已有研究中忽略了确认报文、累积干扰在不同的载波侦听阈值下对系统性能的影响,并在分析中夸大了隐藏节点所导致的信道冲突.针对上述问题,提出了一种结合功率控制的物理载波侦听分析模型.该模型以网络整体性能为优化目标,对全网的累积干扰与空间复用度进行分析,给出节点的平均信道容量.此外,对信道状态建立马尔可夫链模型,提出了4类载波侦听范围内发生的信道冲突以及两类全网累积干扰所引发的信道冲突.分析上述各类冲突对信道利用率的影响,并结合节点的平均信道容量给出优化的载波侦听阈值以及传输功率.与已有研究相比,模型中明确分析确认报文、累积干扰以及隐藏节点对信道冲突的影响.分析结果表明,如果不考虑上诉因素将无法获得最优的载波侦听范围,并且会导致网络性能的下降.     

Design and experimental testing of an optimization-based flow control algorithm for Energy Harvesting Wireless Sensor Networks

In this paper a distributed flow control law is proposed to maximize throughput and to minimize energy consumption in Energy Harvesting Wireless Sensor Networks (EH-WSNs). We preliminary recast the control problem in terms of primal–dual optimization one taking into account the bandwidth and energy autonomy node constraint. Then, we devise a distributed flow rate control implemented at each node that allows the overall network to converge to the optimal solution of the original problem. The closed loop EH-WSN stability and convergence to the optimal equilibrium are proven. The effectiveness of the proposed control law in terms of throughput and network lifetime performance is experimentally validated by a small representative EH-WSN. The experimental results are in a good agreement with the theoretical ones.     

多感知范围无线传感器网络中一种分布式目标覆盖算法

基于多感知范围无线传感器网络中节点与目标的覆盖关系,设计了一种目标生命期评估机制。鉴于网络生命期由具有最小生命期的目标决定,在分析节点感知半径变更影响的基础上,提出了两种提高最小目标生命期的策略,建立了一个动态目标覆盖博弈模型,并证明了该博弈存在纯策略的纳什均衡。本文设计了一种分布式目标覆盖算法,算法中节点根据邻居节点的能量分布和目标覆盖情况,选用最优感知半径,以确保目标完全覆盖并延长最小目标生命期。仿真结果表明,在不同的网络中所提算法均能有效地延长网络生命期。     

一种基于压缩感知和动态时间规整的信号肽特征提取新算法

准确识别出信号肽对蛋白质的研究和定位有着非常重要的意义。压缩感知技术能够在保留生物序列主要信息的同时降低冗余信息,将高维信息投影到低维空间上进行特征提取。因此本文基于压缩感知技术再结合动态时间规整算法提取出新的特征向量,提出一种高鉴别性的信号肽特征提取新方法。该算法所提取的特征不但体现了信号肽中的氨基酸组成、排列顺序、结构等重要信息,还能把信号肽的不同区域在时间维度中非线性地弯曲对整,为机器学习算法提供有效的信号肽特征表达。实验结果显示,新方法提取的特征向量在3个数据集Eukaryotes, Gram+ bacteria, Gram-bacteria上的识别率分别达到99.65%, 98.05%和98.56%,并且这种方法能简单地运用到其他生物序列的识别过程中。     

无线传感器网络MAC层能耗与时延的权衡

无线传感器网络节点设计的最重要约束之一就是要求低能耗,这与传统网络依赖持续的能源供应而致力于提供尽可能高的服务质量截然不同.研究了一个结合无线传感器网络的能耗特性而提出的MAC协议S-MAC协议,并在对802.11MAC、S-MAC中的能耗状态与时延特征进行理论和数学分析的基础上,通过仿真实验得出了在模拟网络环境中802.11MAC和S-MAC的能耗和平均时延,S-MAC协议中引入节点周期性睡眠、冲突串音避免和消息传递等新技术,以牺牲时延为代价换取高效的能量利用,提供了一种高效可扩展的在能耗和时延之间进行权衡的方案.     

射频供能传感网中能量源布置和发送功率优化

射频能量捕获无线传感网（RF energy harvesting wireless sensor network,简称RFEH-WSN）是无线传感网的热点研究领域之一,专用射频能量源设备（energy transmitter,简称ET）的使用进一步增强了网络的可控制性和实用性.这类应用中一个值得研究的问题就是如何配置给定数量的ET,从而在满足节点能量需求的前提下优化布置位置和发送功率,减少能量消耗.首先对ET布置和发送功率联合优化问题建模,明确优化目标和限制条件.然后分别提出了先基于聚类算法确定ET位置再调整功率的分步优化方案,以及基于粒子群优化（particle swarm optimization,简称PSO）的布置与发送功率联合优化方案.仿真结果显示,布置和发送功率联合优化方案较分步优化方案,ET发送功率的节能效果更为明显.