基于区块链技术的物联网信息共享安全机制研究

文章对基于区块链技术的物联网信息共享安全相关理论及信息共享安全框架进行了分析,介绍了信息感知层、数据传输层、技术应用层信息安全的基本情况,从区块链技术应用方面进行了论述,提出了双链模式的物联网信息共享安全防护方法,对双链模式构建策略和物联网超级账本安全架构方法进行了研究。仿真实验证明,该模式能够增强抗攻击能力,提升数据区块链性能和交易区块链性能,达到良好的物联网信息共享安全防护效果,解决了物联网信息共享的安全问题。     

物联网信息共享演示系统的设计与实现

文章针对物联网应用领域数据分散管理、信息共享程度不高等问题,提出一种物联网信息共享演示系统构建方案,演示物联网典型应用背景下的感知、传输、应用等环节,验证物联网服务共享平台对各类服务的注册、发现等功能,并通过开发基于浏览器的交互界面,为用户提供直观的浏览、操控界面。     

物联网的技术思想与应用策略研究

在综合分析物联网的基本概念和关键技术研究进展的基础上,研究提出了关于"多域融合共享和泛在综合服务"的物联网核心技术思想;研究了智慧化综合服务平台的技术体系结构并且建立了相应的实验理论模型;研究建立了实现未来物联网市场应用、融合共享、泛在服务、商业模式和产业结构的商务应用模型,提出了"智慧服务商店"的概念,并研发了实用的"智慧校园"综合服务示范实验系统和实验性"物联网科技园智慧服务商店";研究了以物联网应用为标志、以产业应用和智慧服务为特征的后互联网时代新兴智慧服务产业的应用策略.     

基于物联网的医院管理系统构建及应用

结合医疗行业物联网系统的建设现状,设计一种基于物联网的医院智能医护与综合过程管理系统.本系统采用物联网与云计算融合的方式将现有医疗物联网系统进行信息整合,设计了一套标准的医疗物联网公共平台.并采用面向服务的云计算平台,为其他医疗行业应用系统提供必要的业务信息支撑.物联网技术可广泛应用于医疗行业,建设基于物联网的医院智能医护与综合过程管理系统是医疗系统发展的有力支撑.     

物联网环境下基于公众服务的交通信息整合研究

以存在于公路交通信息资源的"信息孤岛"为切入点,寻找消除这种现象的有效途径,提出信息资源整合,构建物联网环境下基于公众服务的交通信息资源整合的体系结构。重点分析信息共享与交换的机理,全面阐述数据中心的功能,物联网环境下基于公众服务的交通信息的整合所需要的应用系统主要有综合运行分析系统、公路建设整合管理系统、公众出行信息服务系统以及应急处置系统。     

物联网环境下的信息共享机制研究

物联网的应用,给信息世界带来了全新的变革。它最大限度地使用了信息资源,提高了信息共享的效率。为了强化信息资源整合,促进物联网信息协同共享,需要创建良好的物联网信息共享环境,建立完善的物联网信息共享机制。本文提出建立在构建结构化元数据和发现元数据的基础上,创建基于共享空间的信息共享模式,构建面向服务的物联网信息共享平台,通过有效的途径来提高信息共享效率和业务协同处理能力。     

信息时代下物联网服务模式设计及应用

文章旨在做好信息时代下的物联网服务模式的设计和实现过程研究,结合信息聚合的角度,提出信息时代物联网纵向服务模式和横向服务模式的设计,指出跨行业的信息共享难以实现。不同区域行业的信息共享缺乏有效的联系,因为其不仅有着不同的数据格式,传输协议也各不相同。对政府而言,要做好信息环境的法律保证,全面落实政策,注重信息的安全传递和交流。从运营商的角度来看,他们要做好产业链的融合,建立基础物理信息数据库,实现基础信息的供给,做好数据的分发,打造行业物理信息共享平台,加强行业内部的信息交流。在信息时代,物联网服务模式设计应用,不仅推动了物联网服务的可持续发展,同时对于国民经济的增长也有着积极作用。     

关于物联网大型公共服务平台的研究

站在产业的角度来看,尽管目前物联网市场很大,但由于市场碎片化和商业模式不明确,缺乏对各行业各地域物联网需求公共部分的分析、抽象和建设,以致面向中小企业提供的公共服务严重不足,从而难以整合物联网生态产业链的上下游资源。根据信息通信技术的发展趋势和移动互联网的演进方向,从产业推广和平台运营的角度,丰富和完善物联网大型公共服务平台这一关键基础平台的概念、功能和框架,必将促进物联网建设进入集中化、标准化、共享化、服务化的新阶段。     

云计算环境下基于用户体验的成本最优存储策略研究

为了提高大数据文件的存取效率,满足各类用户的需求,通常采用对该文件进行分块、冗余副本等机制进行存储,关于设置块大小、副本个数和块部署等存储机制的研究一直是该领域研究重点.根据用户对内容块兴趣需求,我们定义了数据块的热度并提出了一种满足用户需求的存储数据块的最小服务成本策略(MCSB).在成本矩阵的基础上,通过引入与数据块热度相关的成本矩阵调整因子,使得热度较低的数据块被优先部署,实现了在不改变存储数据块的最小服务总成本的情况下,内容存取服务性能的提高.基于该策略,以Hadoop中的缺省数据块存储策略为控制组,通过在HDFS系统中实现MCSB,并对MCSB进行了较为详细的分析.实验结果显示MCSB策略能够在满足最小服务成本的情况下,具有更短的系统平均响应时间.进一步考虑到数据存储节点由服务器集群承担的事实,对基于不同负载下的数据存储策略进行了深入探讨,在分析现有机制对性能影响的基础上,给出了一种自适应的数据节点内的存储数据块的最小服务成本策略AMCSB,实验表明,本文所提出的AMCSB策略能够在降低服务成本的同时,有利于系统的负载均衡,并提高该系统的服务性能.     

云计算环境下基于用户体验的成本最优存储策略研究

为了提高大数据文件的存取效率,满足各类用户的需求,通常采用对该文件进行分块、冗余副本等机制进行存储,关于设置块大小、副本个数和块部署等存储机制的研究一直是该领域研究重点.根据用户对内容块兴趣需求,我们定义了数据块的热度并提出了一种满足用户需求的存储数据块的最小服务成本策略（MCSB）.在成本矩阵的基础上,通过引入与数据块热度相关的成本矩阵调整因子,使得热度较低的数据块被优先部署,实现了在不改变存储数据块的最小服务总成本的情况下,内容存取服务性能的提高.基于该策略,以Hadoop中的缺省数据块存储策略为控制组,通过在HDFS系统中实现MCSB,并对MCSB进行了较为详细的分析.实验结果显示MCSB策略能够在满足最小服务成本的情况下,具有更短的系统平均响应时间.进一步考虑到数据存储节点由服务器集群承担的事实,对基于不同负载下的数据存储策略进行了深入探讨,在分析现有机制对性能影响的基础上,给出了一种自适应的数据节点内的存储数据块的最小服务成本策略AMCSB,实验表明,本文所提出的AMCSB策略能够在降低服务成本的同时,有利于系统的负载均衡,并提高该系统的服务性能.     

6G oriented blockchain based Internet of things data sharing and storage mechanism

Considering the heterogeneity of various IoT system and the single point failure of centralized data-processing platform,a decentralized IoT data sharing and storage method based on blockchain technology was proposed.The block consensus and decentralized storage of shared data were realized through the PoS consensus mechanism.A block layered propagation mechanism between consensus node and verified node was proposed based on the Gossip protocol.The block propagation delay model and decentralization evaluation model of blockchain networks were derived.The trade-off between the block propagation delay and the decentralization degree of networks was analyzed.The simulation results demonstrate that the block propagation delay and degree of network decentralization decrease with the increase of minimal capabilities of consensus nodes.As an application example,in the trajectory data sharing scenario of confirmed patients,the data sharing smart contract is implemented and tested based on the Ethereum development platform.     

A self‐adaptive load‐dispatching control framework for device data accessing in IoT‐based systems

The Internet of things (IoT) information system plays important roles in disposing of huge volumes of real‐time service requests from heterogeneous devices, targeting for different complex application requirements. Load‐dispatching control (LDC) is a key problem to be solved for devices accessing concurrently in cluster systems. Self‐adaptive LDC optimizes the resource allocation to ensure no overloading node, thus, improving the performance of IoT systems. This paper focuses on adaptive dispatching control problem in IoT information system. First, a device data access platform is proposed for reducing the load imbalance and improving the efficiency of data processing. Then, we propose a processing capability prediction model to evaluate the system performance. On the basis of the model, we present a practical self‐adaptive LDC framework with a self‐adaptive control strategy and a load dispatching method. Finally, a case study is given to verify the framework and the control strategy. Experimental results show that the proposed strategy can meet the requirements of dynamic load balancing with the ability to avoid the load imbalance problem, and the LDC‐based device access platform can process data accessing effectively and ubiquitously.     

A design of public-data platform in digital campus based on web service

The developing of network drive the developing of information systems in campus. More and more business information systems are built in1990's. But most of these systems in campus are developed on different platform without standard. And some data in business information system should be shared between different departments. So the target of this paper is to solve the problem of sharing data in campus the through the web service. Web service is a service-oriented architecture (SOA) to provider service for service consumer. But the traditional model of web service is not suitable in digital campus. This paper designs a new model of web service for digital campus environment. And then a public-data platform is designed to realize the data sharing in heterogeneous systems. Next, the database designing and data processing flow is introduced. Finally, some monitor information of platform is showed.     

构建电信物联网开放数据服务体系的思考

物联网的一个特征是智能处理,面对海量的物联网数据,如何存储、分析和共享使用是一个值得关注和需要解决的问题。基于对电信运营商物联网经营现状和未来发展趋势的分析,本文提出了建设电信物联网开放数据服务体系的构想,并详细设计了物联网数据服务的服务内容和体系框架,针对数据服务体系建设中涉及的关键技术点进行了分析,最后对电信运营商构建物联网开放数据服务体系的策略给出了建议。     

数据链信息分发系统及其服务发现算法研究

针对现有数据链系统与指控系统间以格式化消息的方式进行交互,系统间耦合紧密,采用广播的方式分发信息,效率不高,与异构数据链系统间信息共享困难等问题,设计并给出了一种面向服务的数据链信息分发系统,详细描述了系统各单元的功能及协作方式。针对分布式环境下,数据链信息服务发现问题,结合现有服务发现的研究成果,分类分析了各算法应用时的优点与不足,在此基础上,给出了下一步研究方向。     

Data analytics in wireless systems and IoT issues and challenges

The emergence of data engineering along with the support of Online Social Networks is growing by millions every day due to the introduction of wireless systems and Internet of Things. The rapid growth of usage of smart devices helps to create new generation knowledge sharing platforms. Data Analytics has a major role to play in the growth and success of wireless and IoT applications. The growth of data has become exponential and is difficult to analyze. Many researchers depend on the data available on Wireless Systems and IoT for developing new generation services and applications. With the opportunity of information and communication technologies like heterogeneous networking, cloud computing, web services, crowd sensing and data mining, ubiquitous and asynchronous information sharing is feasible. But this also brings out a lot of provocations with respect to conflicting standards, data portability, data aggregation, data distribution, differential context and communication overhead. The smart information and communication technology has changed many features of human lifestyle: personal and work places.     

军械装备保障模拟训练系统数据集成研究

现行的军械装备保障模拟训练系统的后台数据库多种多样,数据存储的格式和为前台提供的服务方式不尽相同,致使信息在不同部门和系统之间流通困难,分散的系统很难促进军械装备保障能力快速提高。介绍了一种数据集成模式——基于数据仓库的数据集成。采用该数据集成模式,可以屏蔽各种数据库中数据存储的差异,解决模拟训练分系统数据共享和交换的问题,实现分系统数据的互联互通,为实现军械装备保障模拟训练系统集成提供数据保障。     

Multiple layer design for mass data transmission against channel congestion in IoT

Internet of Things (IoT) is well studied from many aspects; however, data transmission in a large‐scale constructed IoT network is still an open topic. In this paper, the problems of channel congestion caused by mass data transmission are discussed respectively from different perspectives. Then, a multiple layer solution is proposed, pointing to each layer including data processing architecture, data dimension reduction, data abandon protocol, and spectrum sharing. In the architecture layer, a combined scheme with cloud computing and sea computing is introduced. Context awareness and granular computing is exploited to implement the data dimension reduction. And cognitive protocol is involved with type of service, which drops certain data to guarantee the entire network connectivity. Then, a principal–agent theory based two‐step game model is proposed with the consideration of cooperation and price coefficient, which affect the secondary user's choice and primary user's profit. Some incomplete information is assumed as random variables so that certainty equivalent is introduced in the model. A simple scenario shows how the data dimension reduction works and how simulations for data abandon protocol and spectrum sharing test the two parts, respectively. Copyright © 2012 John Wiley & Sons, Ltd.     

物联网异构环境中面向服务的中间件

A great number of sensor technologies are applied in the Internet of Things (IoT) currently and more are emerging,which makes the IoT a heterogeneous network. This paper discusses the convergence and integration problem in IoT. A Service-O-riented Middleware for Heterogeneous Environment (SOMHE) in IoT is proposed. The purpose of the middleware is to shield the difference between protocols in the sensor layers such as Radio Frequency Identification (RFID) and ZigBee by defining the data conversion and mapping model. A Web service interface is supplied by this middleware, thus the complexity of high level application development can be reduced greatly. The feasibility and reliability of this middleware is verified by a demonstration system.     

Fairness constraint efficiency optimization for multiresource allocation in a cluster system serving internet of things

Massive, diverse, and high-frequency Internet of Things (IoT) applications pose challenges to the operation of cluster systems that serve it. Fair and efficient multidimensional resource allocation is of great significance to the sustainable operation of these systems. However, most of the existing cluster multiresource allocation optimization researches focus too much on the fairness of resource allocation and ignore the efficiency. The unbalanced use of multidimensional system resources reduces the effective utilization of system resources, which seriously affects the service quality of IoT applications. In this paper, we define the multiresource fair and efficient sharing optimization as a fairness-constrained efficiency optimization problem, which is from dynamics, discrete resources, and heterogeneous perspectives according to the characteristics of cluster system in practical. Moreover, we present a dynamic efficiency-aware multiresource fair allocation algorithm, DEF, which can improve the ability of the cluster system to serve diverse IoT applications. In the algorithm, large jobs schedule to the servers that expect the least remaining resources. Simulations performed using Google cluster-usage traces show that DEF can improve system resource utilization and guarantee the fairness of sharing among users.