物联网阅读笔记
姓名胡念
学号151********
专业计算机科学与技术老师姜腊林
2012_李征&刘开华_天津大学_Adaptive Resource Allocation Algorithm for Internet of Things with Bandwidth Constraint.
[Ref]Li Zheng,Liu Kaihua,Su yuting,et al.Adaptive Resource Allocation Algorithm for Internet of Things with Bandwidth Constraint[J].Journal of Tianjin University, 2012,15(4):253-258.
[笔记]
本文提出一种自适应的资源分配算法-AMSRS算法，该算法通过动态检测所发送信号的频域特性和调整不同传感或驱动组件之间的加权因子，以此来提高在网络带宽限制下的物联网性能。
摘要：
为了提高物联网上的传感和驱动信号的传输精度和效率，以及保证系统的稳定性，本文提出了一种自适应的资源分配算法，该算法根据信号的频域特点，动态地分配各部件之间的网络带宽和优先级。对开发远程感知无人控制的地面车辆（UGV）路径跟踪试验台，以及测量多个UGV跟踪的误差信号进行性能评估。评估结果表明：在相同的网络带宽约束下，本文所提算法与传统的静态算法相比：可以减少的GUV路径跟踪的积累误差和最大误差超过60%。
In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things(IoT)and ensure the system stability,an adaptive resource allocation algorithm is proposed,which dynamically assigns the network bandwidth and priority among components according to their signals’frequency domain characteristics.A remote sensed and controlled unmanned ground vehicle(UGV)path tracking test-bed was developed and multiple UGV’s tracking error signals were measured in the simulation for performance evaluation.Results show that with the same network bandwidth constraints,the proposed algorithm can reduce the accumulated and maximum errors of UGV path tracking by over60%compared with the conventional static algorithm.
介绍：
为了平衡物联网系统的不同组件的要求，本文提出自适应多重采样速率调度算(AMSRS)。首先，该算法能分析物联网的不同的组件所发送的信号的频域特性。然后动态地分配相应的信号之间的计算采样率。同时，它还可以调整组件之间的权重，由他们在分配算法中的个别任务和状态，以保证整个系统的稳定性和性能。为了评估所提出的算法，将其与传统静态算法相比，开发和模拟一个原型的无人地面车辆(UGV)路径跟踪试验台，以此来检测性能。
In this paper,to balance the requests from different components in IoT system,an adaptive multiple sampling rate scheduling(AMSRS)algorithm is proposed.Firstly,this algorithm can analyze the frequency domain characteristics of the transmitted signals from IoT’s different components.Then it dynamically allocates calculated sampling rates among signals accordingly. Meanwhile,it can also adjust the weights among components by their individual tasks and states in the allocation algorithm to guarantee the overall system stability and performance.In order to evaluate the proposed algorithm,a prototype unmanned ground vehicle(UGV)path tracking test-bed was developed and simulated to examine the performance improvement by AMSRS versus conventional static algorithm.
结论：
本文提出AMSRS算法，该算法通过动态检测所发送的信号的频域特性和调整不同传感或驱动组件之间的加权因子，以此来提高在网络带宽限制下的物联网性能。该算法可以根据组件的个人需要分配网络资源，提高物联网系统的整体性能。对开发的一个三层UGV跟踪路径实验床进行性能评估，结果表明：与静态算法相比，本文所提算法的累计误差和最大误差能分别减少73.87%和66.48%。
In this paper,an AMSRS algorithm was proposed to improve the performance of IoT with
network bandwidth constraints.By dynamically detecting the transmitted signals’frequency domain characteristics and adjusting the weighting factors among different sensing or actuating components,this algorithm can allocate network resources according to the component’s individual need and improve the overall performance of the IoT system.A three-UGV path tracking IoT test-bed was developed.Results show that compared with static algorithm,sums
of the accumulated errors and maximum errors can be reduced by73.87%and66.48% respectively.
2014_Park&Cho_Energy-Efficient Probabilistic Routing Algorithm for Internet of Things
[Ref]Park S H,Cho S,Lee J R.Energy-Efficient Probabilistic Routing Algorithm for Internet of Things[J].Journal of Applied Mathematics,2014,2014(2):1-7.
[笔记]
本文提出EEPR算法，该算法采用一个节点剩余能量和ETX值作为路由度量，所提算法具有更长的网络寿命，以及每个节点消耗的剩余能量更均匀。
摘要：
在物联网中，每个物体能与其它物体进行通信，并相互获取信息。在物联网的分布式网络中，节点的能量效率是网络性能的一个关键因素。本文提出了节能的概率路由(EEPR)算法，该算法随机地控制路由请求报文的传输，以提高网络的生命周期，以及在泛洪算法下减少丢包。EEPR算法通过在典型的AODV 协议中，同时使用其每个节点的剩余能量和ETX度量进行模拟，以此控制节能概率。该模拟实验表明：与典型的AODV协议相比，本文所提算法具有更长的网络寿命，以及每个节点消耗的剩余能量更均匀。
In the future network with Internet of Things(IoT),each of the things communicates with the others and acquires information by itself.In distributed networks for IoT,the energy efficiency of the nodes is a key factor in the network performance.In this paper,we propose energy-efficient probabilistic routing(EEPR)algorithm,which controls the transmission of the routing request packets stochastically in order to increase the network lifetime and decrease the packet loss under the flooding algorithm.The proposed EEPR algorithm adopts energy-efficient probabilistic control by simultaneously using the residual energy of each node and ETX metric in the context of the typical AODV protocol.In the simulations,we verify that the proposed algorithm has longer network lifetime and consumes the residual energy of each node more evenly when compared with the typical AODV protocol.
结论：
本文提出EEPR算法，该算法采用一个节点剩余能量和ETX值作为路由度量，同时。所提算法通过使用的剩余能量和链路路径上的ETX值，来随机控制RREQ包的数量，从而有利于节能路由的建立。仿真结果表明，与典型的AODV协议相比，本文所提算法具有更长的网络生存时间，以及每个节点消耗的剩余能量更均匀。
In this paper,we proposed EEPR algorithm which employs both the residual energy of a node and the ETX value as the routing metrics,at the same time.The proposed EEPR algorithm stochastically controls the number of the RREQ packets using the residual energy and ETX value of a link on the path and thus facilitates energy-efficient route setup.Simulation results show that the proposed EEPR algorithm has longer network lifetime and consumes the residual energy of each node more evenly when compared with the typical AODV protocol while the routing setup delay is slightly increased and the routing success probability is slightly decreased.
2011_Bandyopadhyay&Sen_Internet of Things:Applications and Challenges in Technology and Standardization
[Ref]Bandyopadhyay D,Sen J.Internet of Things:Applications and Challenges in Technology and Standardization[J].Computer Science,2011,58(1):49-69.
[笔记]
摘要：
物联网预示着未来的互联网的一个版本，该版本即连接实质的物体，从纸币到自行车，通过网络将让他们在互联网上积极参与，对自己和周围的环境交换信息。这将直接访问关于物理世界和对象的信息，产生创新服务和提高效率和生产力。本文研究了物联网的最先进的技术，介绍了物联网的关键技术驱动程序、潜在应用、挑战和未来的研究领域。在学术界和工业界对物联网定义从不同的角度进行了讨论和比较。最后对物联网未来研究的几个主要问题进行了简要的定义和讨论。
The phrase Internet of Things(IoT)heralds a vision of the future Internet where connecting physical things,from banknotes to bicycles,through a network will let them take an active part in the Internet,exchanging information about themselves and their surroundings.This will give immediate access to information about the physical world and the objects in it—leading to innovative services and increase in efficiency and productivity.This paper studies the state-of-the-art of IoT and presents the key technological drivers,potential applications,challenges and future research areas in the domain of IoT.IoT definitions from different perspective in academic and industry communities are also discussed and compared.Finally some major issues of future research in IoT are identified and discussed briefly.
介绍：
第2节介绍了物联网的愿景。第3节讨论了在物联网中一个通用的分层架构和在不同层中涉及的各种问题。第4节介绍了物联网的关键技术。5节介绍了物联网在各个行业的一些具体应用。第6节定义一些在现实生活中物联网在部署方面的挑战。第7节介绍了未来在物联网方面的研究领域。
Section2presents the vision of IoT.Section3discusses a generic layered architectural framework for IoT and various issues involved in different layers.Section4presents the key technologies involved in IoT.Section5presents some specific applications of IoT in various industry verticals.Section6identifies some of the challenges in deploying the concept of IoT in the real world.Section7presents future research areas in the domain of IoT.
结论：
本文调查了物联网的一些最重要的方面，特别是专注于正在做什么，什么是需要进一步研究的问题。虽然目前的技术使物联网的概念是可行的，但大量的挑战摆在面前，一个大规模的现实世界的物联网应用部署。在接下来的几年中，解决这些挑战对于在工业和学术实验室的网络和通信研究将是一个强大的驱动力。
This paper surveyed some of the most important aspects of IoT with particular focus on what is being done and what are the issues that require further research.While the current technologies make the concept of IoT feasible,a large number of challenges lie ahead for making the a large-scale real-world deployment of IoT applications.In the next few years,addressing these challenges will be a powerful driving force for networking and communication research in both industrial and academic laboratories.
Chapter13Internet of Things
物体连接到互联网使得有可能访问远程传感器数据，和控制有距离的物理世界。捕获的混合数据将从其他来源的数据中分离，例如，在网页中包含的数据，产生新的协同服务，超越了可以提供一个独立的嵌入式系统的服务，物联网是基于这一愿景。一个智能对象，即物联网的建筑模块，只是连接到互联网嵌入式系统的另一个名称。另一种技术指出在同一方向的射频识别技术，一个扩展的无处不在的光学条码，被发现在每一天许多的产品上，需要一个智能的低成本的电子标签的产品，产品的身份可以从一个距离解码的附件。通过将更多的
智能放入身份标签，标签成为一个智能对象。物联网的新颖性不是新的破坏性技术，而是在智能对象中普遍部署。
The connection of physical things to the Internet makes it possible to access remote sensor data and to control the physical world from a distance.The mash-up of captured data with data retrieved from other sources,e.g.,with data that is contained in the Web,gives rise to new synergistic services that go beyond the services that can be provided by an isolated embedded system.The Internet of Things is based on this vision.A smart object,which is the building block of the Internet of Things,is just another name for an embedded system that is connected to the Internet.There is another technology that points in the same direction-the RFID technology.The RFID technology,an extension of the ubiquitous optical bar codes that are found on many every-day products,requires the attachment of a smart low-cost electronic ID-tag to a product such that the identity of a product can be decoded from a distance.By putting more intelligence into the ID tag,the tagged thing becomes a smart object.The novelty of the Internet-of-Things(IoT)is not in any new disruptive technology,but in the pervasive deployment of smart objects.
在本章的开头，介绍了物联网的愿景。下一节阐述了推动物联网的发展的力量。我们区分技术的推动和技术的推动力量。第13.3节的重点是要解决的技术问题，以使物联网带到大众市场。第13.4节讨论了射频识别技术，它可以被看作是物联网的先行者。无线传感器网络的主题，其中自组织的智能对象建立自组织网络，并从环境中收集数据，将在13.5节中介绍。收集数据和控制物理环境的智能对象，其普遍部署对世界的安全和我们生活的隐私造成了严峻的挑战。
At the beginning of this chapter,the vision of the IoT is introduced.The next section elaborates on the forces that drive the development of the IoT.We distinguish between technology push and technology pull forces.Section13.3focuses on the technology issues that have to be addressed in order to bring the IoT to a mass market.Section13.4discusses the RFID technology, which can be seen as a forerunner of the IoT.The topic of wireless sensor networks,where self-organizing smart objects build ad-hoc networks and collect data from the environment,is covered in Sect.13.5.The pervasive deployment of smart objects that collect data and control the physical environment from a distance poses a severe challenge to the security and safety of the world and the privacy of our lives.