基于事件捕获的无线传感网络节点能耗实时估计

无线传感网络节点能耗的动态估计对于延长网络的寿命非常关键。针对无线传感网络节点的实时能耗估计,以运行TinyOS的MICAz节点作为目标平台,对TinyOS进行了功能扩展,用nesC语言设计了一个基于事件捕获的能耗估计模块。采用数据采集卡对各硬件模块的功耗模型进行了标定,实验结果表明该方法的时间和空间开销较小,估计精度约为4%。     

区域数字公路网T-GIS的建立及应用系统开发

把GIS技术应用到公路交通领域，是提高公路网规划、建没、管理水平的重要途径之一。该文分析了数字公路的概念及特点，结合赣州市城乡数字公路网T-GIS的建立，给出了系统的总体设计框架及技术实现方法，探讨了系统在公路网评价、出行诱导、定位跟踪等方面的应用。     

网络能耗系统模型及能效算法

网络能耗问题是当前网络研究和发展的重要问题,影响着网络的设计、应用和发展.当前网络能效算法的研究大多从网络局部角度关注于网络某一(些)设施的能耗问题,缺乏从网络全局的角度研究网络整体能耗的算法和策略.文中从网络全局角度研究网络的能耗模型和算法问题.文中基于3种基本网络数据传递模式和3种基本网络能耗机制,构建了网络能耗系统优化模型,对其中5种关键系统模型给出了详细的描述.针对几个关键系统模型,文中给出了形式化描述并且提出了相应的优化的节能路由算法.文中给出的网络系统能耗优化模型有助于对于网络能耗的理解和分析,所提出的能耗优化的网络数据包路由算法可以从网络路由的角度有效降低网络能耗.     

基于OD的区域公路交通预测系统结构与关键技术

为了简化区域公路交通预测工作,结合我国目前公路交通特征,设计并建立基于OD更新的区域公路交通预测系统非常必要。从结构和功能出发,提出系统需具备数据管理、图形管理、OD更新、需求预测和交通量预测等5个基本模块。重点分析了系统实现过程中的一些关键技术,如数据关联和融合、图形数据接口、路网检查方法、控制点选择方法、相关路段筛选等。系统的开发和应用能提高区域公路交通信息化水平,帮助制定科学合理的规划设计和管理策略。     

能量高效的WSN时间同步算法

本文主要研究了无线传感器网络时间同步技术,针对传感器网络能量有限的特点,提出了一种能量高效的时间同步算法EETS（Energy Efficient Time Synchronization）. 它采用分层成簇的策略,将网络节点划分为主次两种网络,分别使用TPSN算法和DMTS算法的思想进行时间同步,从而降低了算法复杂度,减少了通信量. 仿真结果表明,与TPSN算法相比,该算法在一定程度上降低了网络能耗,有效延长了网络的生命周期.     

Energy Aware Routing Algorithm in Manet Using Linear Programming

Mobile ad hoc networks (MANET) are wireless network without infrastructure and suffering from low power battery. Therefore the main objective in finding a route for traffic transfer from a given source to a given destination is to minimize the node energy consumption. This paper solves the problem of finding a route satisfying the main objective of minimum energy consumption and other QoS requirements such as minimum delay and maximum packet delivery ratio by using linear programming technique. Two cases are considered: 1. The traffic amount of a given request is transmitted into single path, and 2. The traffic amount of a request can be distributed into parallel paths. A preprocessing step is done first for network topology design. This step leads to formulate the first case as integer linear programming problem and the second case as linear programming and not mixed integer linear programming. The two obtained solutions are evaluated in terms of three criteria: energy consumption, execution time, and packet delivery ratio using an experimental study. The results show that the solution of second case is much better than the first case in terms of energy consumption and execution time. Packet delivery ratio in the second case is 100% while in the first case is only 76%.     

基于自学习边权重图卷积网络的用户用能分类

用户分类是用能分析的一种重要方法,而智能电表的广泛应用为用户用能分析提供了大量的可用数据.为进一步提高用户分类精度与用能特征的提取能力,本文提出了一种自学习边权重的图卷积网络.所提出的网络通过具有注意力机制的特殊初始化层将原始能耗数据转换为图,并从生成的图中提取能耗特征,最终根据图的学习特征输出用户类.为证明所提出方法的有效性,本文在实际用能数据集上进行了对比实验.实验结果表明,本文方法不仅能够更好地提取用户特征,而且取得了更好的分类性能.     

Network pruning for energy saving in the Internet

Many scientific works propose methods of reducing the amount of energy consumed by the Internet. Although the structure of the Internet was not developed with specific attention to energy consumption, there are various components on which it is possible to act. In our work, we analyze the possibility of affecting the topology of the network. We propose a heuristic called Energy Saving based on TOPology control (ESTOP), which identifies poorly used router line cards by leveraging certain topological properties of the graph modeling an Internet Service Provider (ISP). By acting on these line cards – for example, by putting them into sleep mode – we prune the Internet topology and achieve significant energy savings while preserving the primary topological characteristics of the pruned network. Although ESTOP is traffic-unaware, we assess its behavior under real traffic loads, demonstrating that its performance is comparable to the more complex traffic-aware solutions proposed in the literature.     

一种基于快速重路由的域内节能路由算法

降低互联网的能耗成为亟待解决的一个科学问题,已有的路由节能方案存在会不同程度地降低网络性能,如网络拥塞、路由振荡、路由可用性和流量分布不均匀等问题,以及需要网络的实时流量信息,从而导致算法复杂度较高的问题。设计一种基于快速重路由的绿色节能方案EEIPFRR,兼顾节能、网络性能和算法复杂度。实验结果表明,与DLF算法比较,EEIPFRR算法不仅可以降低网络能耗,并且具有较小的路径拉伸度、较低的算法复杂度和较小的最大链路利用率。     

主动休眠节点链路的高效节能虚拟网络映射

网络虚拟化,使得智能能量感知网络部署成为可能.由于当前网络为高峰负荷而设计,导致资源利用率不足及能量浪费.而网络设备能量消耗对于流量负载不敏感,资源整合成为有效节能技术.根据虚拟网络映射特点及底层网络能耗,提出虚拟网络映射节能多目标决策模型;由于该模型是混合整数规划模型,求解时间复杂度高,通过分析虚拟网络映射动态特征,构造虚拟网络映射字典库,提出底层网络资源利用率的训练方法以及主动休眠底层节点和链路算法,把虚拟网络映射在一个较小的节点和链路集合中,提高休眠节点和链路数量,实现高效节能虚拟网络映射.系统仿真结果验证了主动休眠方法能够提高底层节点和链路休眠数量,显著减少系统能耗.     

QoS vs. energy: A traffic-aware topology management scheme for green heterogeneous networks

Increasing environmental awareness combined with the high energy prices has driven the network operators to reduce their carbon dioxide footprint by adopting energy efficient green methods. In this paper, we aim to save energy by both switching base stations on/off and adaptively adjusting their transmission power according to the present traffic conditions for heterogenous wireless cellular networks. We formulate a novel linear programming model for the Traffic-Aware Topology Management (TAM) problem to find the best possible topology which minimizes the overall power consumption of the network while satisfying a certain Quality of Service level in Wideband Code Division Multiple Access packet-switched cellular networks. Although the optimization tools provide the optimum solutions, it is not possible to handle large instances due to the space and computational complexity. Hence, we propose a Green TAM Algorithm to solve the large-scale realistic instances of the formulated problem and compare our results with the results of two previously proposed methods, a greedy heuristic and a commercial optimization tool. We show that the proposed TAM scheme helps to maintain an energy-aware network and saves significant amount of energy by adjusting the network topology to the current traffic conditions adaptively.     

基于代数连通度的域内节能路由算法

通过节能路由算法减少网络能耗是网络中需要解决的一个关键性的科学问题。如今已有的节能方案都是在已知流量矩阵的前提下研究网络节能,由于实时流量难以获取,使得这些方案都难以在实际中部署。因此,文中提出一种基于代数连通度的域内节能方案(Intra-domain Energy Efficient Routing Scheme Based on Algebraic Connectivity,EERSBAC)。EERSBAC不需要网络中的实时流量矩阵,仅依靠网络中的拓扑结构就可以实现节能。首先,提出链路关键度模型,利用链路关键度模型计算出网络中所有链路的重要程度;然后,提出代数连通度模型,利用代数连通度模型可以定量的衡量网络的连通性能。实验结果表明,EERSBAC不仅能够降低网络能耗,而且具有较小的路径拉伸度。     

Optimal virtual network embedding: Energy aware formulation

Network Virtualization is a key component of the Future Internet, providing the dynamic support of different networks with different paradigms and mechanisms in the same physical infrastructure. A major challenge in the dynamic provision of virtual networks is the embedding approach taking energy efficiency into account, while not affecting the overall Virtual Network (VN) acceptance ratio. Previous research focused on either designing heuristic-based algorithms to address the efficient embedding problem or to address the energy impact.This paper proposes an integer linear programming formulation, Energy Aware–Virtual Network Embedding–Node-Link Formulation (EA–VNE–NLF), that solves the online virtual network embedding as an optimization problem, striving for the minimum energy consumption and optimal resource allocation per VN mapping. Two different objective functions are proposed: (i) addressing primarily the resource consumption problem – Bandwidth Consumption Minimization (BCM); (ii) addressing primarily the energy consumption problem – Energy Consumption Minimization (ECM).The performance of each objective function is evaluated by means of simulation and compared with an existing objective function, Weighted Shortest Distance Path (WSDP), that is considered state of the art of the resource allocation problem. The simulation results show that the objective function BCM reduces the energy consumption of the physical network by 14.4%, and improves the embedding factor by 4.3%, consuming almost the same amount of resources as requested, and slightly worsening the VN acceptance ratio by 2.3%. ECM reduces the energy consumption of the physical network by 31.4% and improves the embedding factor by 4.1%, without affecting the VN acceptance ratio when compared to WSDP.     

基于Hadoop的高速公路OD数据存储模型和计算方法

高速公路OD数据是高速公路运营管理和状况分析的一类重要数据,如何利用海量的收费数据快速生成并有效管理高速公路OD数据是当前高速公路智能化建设中的一个重要问题.针对高速公路OD数据的种类多、周期长等问题,提出一种基于Hadoop的高速公路OD矩阵存储模型和相应的计算方法.建立统计高速公路车辆旅行时间、统计高速公路车流量两类OD矩阵作为存储模型.通过基于海量真实的高速公路收费数据的实验和传统的存储高速公路收费数据对比表明本文的存储方法相对于传统的关系数据存储,拥有更高效的存储效率并节省了存储空间.     

智慧公路工程中信息资源规划

经过多年来的信息化建设和积累,交通信息资源总量呈指数级增长,交通信息资源面临的缺乏整合与共享的问题也日益凸显.本文分析了公路信息资源存在的问题,对公路信息资源规划的数据库建设以及数据资源共享进行了深入研究,基于信息工程方法论,科学规划信息资源,并完善基础数据库、业务数据库以及主题数据库的建设,在明确数据服务的发布管理、...     

基于改进的YOLOv4高速公路车辆目标检测研究

针对高速公路场景下的车辆目标检测问题,提出了一种改进的YOLOv4网络对交通场景下车辆目标进行检测的方法;制作了一个多天候、多时段、多场景的车辆目标数据集,并依据数据集得到检测模型;提出多标签检测方法,并在多标签之间建立约束关系,得到更完善的车辆信息;提出了一个图像拼接检测方法,将多幅图像通过拼接层连接后进行车辆检测,以此提升网络的运行效率。实验结果表明,多样化数据集提高了车辆检测精度,减少了车辆目标的误检、漏检,同时改进的网络结构较大提升了检测速度,上述方法可以为高速公路场景下的车辆目标检测与实际应用提供参考。     

基于联网收费数据预测行程时间的实现

高速公路海量的联网收费记录汇聚了很多极具价值的交通信息,利用数据挖掘方法,实现收费数据的增值利用具有重要的理论与应用意义。行程时间是交通规划与管理中的一项重要基础数据,以往行程时间的预测方法依赖于交通调查与检测数据,数据采集成本很高。本文以决策树理论建立起利用联网收费数据预测行程时间的思路,并借助SQL2005提供的数据挖掘功能,建立起数据分析系统,实现利用联网收费数据进行OD行程时间的预测。     

无线传感器网络基于能量效率的系统设计

无线传感器网络是传感技术、计算技术和通信技术的融合.由于传感器节点的能量限制,能量效率是设计无线传感器网络所关注的一个主要内容.文章主要研究网络节点如何配置使系统能量效率提高.通过对传感器节点无线通信能耗模型的扩展,在两种线性网络模型下,分析并仿真实现了多数据源负载时的系统能耗;通过对比分析,在无线传感器网络节点配置时,提出两种有效可行的配置机制:节点等间距放置和优化间距放置.这两种机制对提高能量效率,延长网络寿命提供了很大的帮助.     

绿色网络理论与技术研究

互联网的飞速发展,也使网络能耗急剧增长.但目前网络设备能效低下,未实现能耗比例计算的理念.而网络却为峰值负载而设计,在众多时间处于低负载,存在巨大的节能契机.首先介绍网络设备的能耗模型,继而从两方面阐述网络能耗优化的理论与技术:一方面,在假设网络总流量无法改变的前提下,为网络设备增加能源和性能状态,并优化本地控制策略,从而使单个网络设备实现能耗比例计算,或者在不提高现有网络设备能效的前提下,通过网络范围的协同和流量工程,使网络整体实现能耗比例计算的理念;另一方面,为网络提供缓存能力可以降低或缓解网络流量,从而减少网络的传输能耗或缓解其增长速度,智能的缓存部署、内容存储和请求路由能够进一步优化网络的能耗.在上述基础上,比较了各种技术的优劣,并分析了未来的研究方向.     

Efficient heuristics for energy-aware routing in networks with bundled links

Current networks are typically over-provisioned to ensure low delays, redundancy and reliability. These Quality of Service (QoS) guarantees are typically achieved using high end, high power network equipments. Their use, however, has led to concerns regarding green house gas emissions, which garnered a lot of attention recently and have resulted in a number of global initiatives aim at reducing the carbon footprint of Internet Service Providers (ISPs). These initiatives have motivated ISPs and researchers to design novel network algorithms and hardware that scale the usage or active time of a network according to traffic load. To this end, this paper considers the problem of shutting down a subset of bundled links during off-peak periods in order to minimize energy expenditure. Unfortunately, identifying the cables that minimize this objective is an NP-complete problem. Henceforth, we propose several practical heuristics based on Dijkstra’s algorithm and Yen’s k-shortest paths algorithm. We evaluated our heuristics on the Abilene network – with both real and synthetic traffic matrices and several larger random topologies with various loads. Our results show that the proposed heuristics to be effective and efficient. Moreover, our approaches could potentially reduce the energy usage of cables used in the Abilene network by up to 56.7%, assuming the traffic demands recorded on September 5, 2004.