服务发现机制的比较与分析

因特网的普及以及网络环境的异构性和动态性要求实现用户设备的自配置连网。为此必须在网络协议的应用层实现服务发现机制。本文介绍了学术界和产业界提出并完善的几种主要的服务发现机制的工作原理。并对它们各方面的特性进行了比较和分析。最后,对服务发现机制的研究现状及发展趋势进行了总结和展望。     

基于移动自组网的服务发现体系结构设计

移动自组网络(MANET)是自治的无基础设施的网络,在此基础上进行的服务发现体系有别于传统的服务发现体系,需要从网络传输、服务注册以及服务发现等方面充分考虑移动无线网络和移动设备的特性。现有的基于有线网络或者单点自组网络协议的相关服务技术标准及协议用于MANET,存在很大的局限性和不足。充分考虑移动自组网中设备的移动性和网络环境的不稳定性后,提出了一个基于分簇的体系架构设计,并在该体系架构中就服务传输协议、面向容错的分簇策略、非集中式的服务注册和服务发现机制等方面提出了针对性的设计方案。仿真结果显示,在移动自组网的特殊网络和设备环境下,这一新的体系架构和相关服务发现策略从服务匹配准确度、反馈时间等方面都优于传统方式的服务描述模式和服务发现机制。     

基于P2P的语义Web服务发现机制

分析集中式语义Web服务发现机制存在的问题,利用P2P和本体技术,提出一种基于P2P的语义Web服务发现机制。将服务的部署与发布无缝地绑定在一起,按应用领域和服务目标将整个P2P网络组织成3层结构,基于该结构建立3阶段服务发现算法,达到优化网络结构、提高服务发现效率的目的。     

语义环境下Web服务注册和发现的研究

在未来的网络中,无论是数据还是服务都将在语义环境中发布.现有的Web服务注册和发现机制需要加以改进以适应新的网络环境,同时支持现有的服务架构.本文描述了一种基于P2P的语义网络的服务发布和发现机制,并在服务的发现中提出了服务聚类的概念.     

元服务发现的分析和应用

元服务发现用来根据不同的环境发现和选择一个适合的服务发现机制(SDM,service Discovery Mechanisms).随着各种服务发现机制在管理域的迅速兴起,移动设备可以根据自己所处的环境需要一种确定和选择合适的机制,如:网络域,位置,协议和应用等.本文首先定义了元服务发现,并阐释了它的作用.其次描述了一个集成了面向广播的元服务发现的分布式哈希表(DHT),并利用此实现一个元服务发现过程中的性能体现和结果.最后,对此过程和结果进行了分析评估.     

效能增强的Ad hoc网络服务发现协议

针对Ad hoc网络中服务发现难度大的问题,分析当前服务发现协议的优缺点,提出一种适用于Ad hoc的服务发现协议ESDP,该协议位于应用层,采用推拉结合的模式,通过缓存、节点合作、随机回退等机制减少数据包传输,从而节省电量消耗,同时考虑设备的异构性和安全机制。网络模拟和分析表明该协议性能良好。     

基于ONVIF标准的设备发现的设计与实现

近年来,基于网络摄像机的视频监控应用得到快速发展,然而传统的视频监控应用必须手动连接配置网络摄像机的服务地址,效率低下。为了解决目前网络视频监控应用不能便捷、高效地自动连接网络摄像机的问题,文中提出了设备自动发现的实现技术,采用基于ONVIF的本地设备发现技术WS-Discovery,使用视窗通信基础WCF4.0和嵌入式万维网服务开发平台gSoap,设计和实现了一个设备发现方法,使得网络视频监控应用系统可以自动发现局域网内的网络摄像机并获取服务地址。实验表明可以有效地发现局域网内的所有网络摄像机。     

基于ONVIF标准的设备发现的设计与实现

近年来,基于网络摄像机的视频监控应用得到快速发展,然而传统的视频监控应用必须手动连接配置网络摄像机的服务地址,效率低下。为了解决目前网络视频监控应用不能便捷、高效地自动连接网络摄像机的问题,文中提出了设备自动发现的实现技术,采用基于ONVIF的本地设备发现技术WS—Discovery,使用视窗通信基础WCF4．0和嵌入式万维网服务开发平台gSoap,设计和实现了一个设备发现方法,使得网络视频监控应用系统可以自动发现局域网内的网络摄像机并获取服务地址。实验表明可以有效地发现局域网内的所有网络摄像机。     

一种普及计算环境中的基础设施：PvCGrid

随着计算机技术的发展，人们希望能方便地享用计算能力和信息服务，但是由于计算设备的多样性和设备之间多传输协议的多样性，资源的描述、发现和使用方式的差异，资源之间协作缺乏统一的标准，造成了使用计算设备的障碍。该文提出了一种在普及计算环境中的基础设施——PvCGrid，实现了多种传输协议的管理、设备和服务的发现，提供了用户可定制的组合服务的功能，使得用户可以发现和使用网络中的资源，并且可以根据发现的资源，定制出更加复杂的应用，该基础设施为普及计算提供了互连互通、资源共享和协同服务的技术支持。     

基于分布式OSGi的动态服务组合算法

物联网近年来得到快速发展和普及,而应用与感知设备的严重耦合使得开发过程变得十分困难和复杂.针对OSGi中间件系统,提出了一种分布式OSGi的轻量级中间件结构,将网络中的节点提供的各种功能虚拟抽象为网络服务,通过面向服务架构(service oriented architecture,SOA)的服务管理对设备节点进行解耦.网络设备提供的服务单一,还存在移动性及续航等限制,为了适应动态变化的网络及应用需求,提出了一种满足服务质量约束的网络服务组合机制DscGOM,包括满足服务质量的组合路径选择机制设计和服务重定向机制设计.实验结果表明,该机制能够很好地适应动态网络需求,快速有效地生成服务组合路径.在网络节点意外退出失效的情况下,能够快速寻找替代组合路径和恢复组合服务的执行.     

物联网服务发现初探:传统SOA的可行性和局限性

基于SOA(service-oriented architecture)的物联网(Internet of things,IoT)把设备的功能服务化,以一种统一和通用的接口向外界提供服务。由于物联网中设备的海量性、移动性和资源高度受限性,以及无线网络自身的不可靠性,设备服务与传统的Web服务相比具有不同的特点,现有的Web服务发现方法不能有效地满足物联网中服务发现的需求。从Web服务发现体系结构和匹配策略两个方面对典型的Web服务发现方法进行了分析;结合物联网中服务提供的特点,从可扩展性、资源有限性、异构性和环境的动态变化性四个方面,分析了将Web服务发现方法应用于物联网服务提供中所面临的问题,并讨论了可能的解决思路;探讨了物联网中服务发现需要解决的问题。     

MobiEureka: an approach for enhancing the discovery of mobile web services

While several service discovery protocols and standards have been proposed for supporting service discovery from mobile devices, this remains a challenging problem. In many cases, mobile clients may discover services which they consider relevant but soon realize that such services are not completely usable on their mobile devices due to compatibility and interoperability issues. Without integrating device capabilities into the discovery process, or a device-aware mobile service discovery, it becomes extremely difficult to determine whether discovered services may or may not function properly within the device’s constraints. This paper introduces a solution known as MobiEureka, a mobile device-aware system for enhancing the discovery of mobile web services from mobile devices. Experimental validation, results, and analysis of the introduced ideas are discussed.     

Toward secure and private service discovery anywhere anytime

With the advances in and convergence of Internet technologies, embedded computers, and wireless communication, computing devices have become part of our daily life. Hand-held devices and sensors with wireless connections create opportunities for many new nomadic applications. Service discovery is an essential component for cognitive science to discover existing network services just-in-time. Unlike many other approaches, we propose a service discovery model supporting nomadic users and services in public environments. Our model emphasizes secure and private service discovery in such environments. Location sensing is integrated for location dependent service discovery and is used to lessen service discovery network infrastructure requirements. We analyze the system performance and show our formal verification of the protocols. Our implementation shows that our model is feasible.     

Toward secure and private service discovery anywhere anytime

With the advances in and convergence of Internet technologies, embedded computers, and wireless communication, computing devices have become part of our daily life. Hand-held devices and sensors with wireless connections create opportunities for many new nomadic applications. Service discovery is an essential component for cognitive science to discover existing network services just-in-time. Unlike many other approaches, we propose a service discovery model supporting nomadic users and services in public environments. Our model emphasizes secure and private service discovery in such environments. Location sensing is integrated for location dependent service discovery and is used to lessen service discovery network infrastructure requirements. We analyze the system performance and show our formal verification of the protocols. Our implementation shows that our model is feasible.     

DaaS: Cloud-based mobile Web service discovery

The proliferation of smartphones and the recent advancement in ubiquitous wireless access have made mobile Web services more possible than ever before. However, finding relevant Web services that can match requests and fit user context remains a major concern. The challenges facing Web service discovery are further magnified by the stringent constraints of mobile devices and the inherit complexity of wireless heterogeneous networks. Cloud computing, with its flexible design and theoretically unlimited computing resources, is a viable approach to bootstrapping Web service discovery. The cloud can build bridges between mobile devices, as a convenient ubiquitous interface, and a backbone infrastructure with abundant computing resources. This paper introduces “Discovery as a service (Daas)”, a novel cloud-based discovery framework that addresses the core components of mobile Web service discovery. The DaaS framework lays the foundation of efficient mobile Web service discovery that takes into consideration user preferences and context. The experimental validation and performance evaluation demonstrate that DaaS can effectively rank relevant services according to the various user context and preferences, in addition to enhancing the precision of the discovered services. The prototype also shows that Web service clustering for discovery significantly improves the overall response time, while the cloud maintains scalability according to prespecified performance criteria.     

Zero Configuration Networking: Implementation, performance, and security

The ubiquitous access to wired and wireless networks is making information access possible from anywhere, anytime, and any device. Today, end-users are also highly mobile, often equipped with a range of portable devices, and they expect service availability when they require it. In addition, they do not want to be burdened by complex configurations before they can discover and use services. The Zero Configuration (Zeroconf) Networking technology promises to alleviate this configuration burden by allowing users to discover services and devices with little end-user intervention. We compare two popular implementations of Zeroconf namely, Avahi and Mono.Zeroconf running on Linux and Windows XP operating systems, respectively. We evaluate their performance using service discovery time as the performance metric. Our empirical results show that Linux Avahi yields almost 99% improvements in service discovery time over Windows Mono.Zeroconf. We also discuss security solutions that can be deployed to enhance the security of Zeroconf networks. We further investigate the performance of the IP Security (IPSec) protocol when used by our Mono.Zeroconf implementation running on the Windows XP platform. With IPSec, service discovery time increases by almost 45% with our prototype implementation.     

服务发现技术中的服务描述和服务匹配技术

普及计算环境中的设备和应用需要通过服务发现来获得其它设备和应用所提供的服务。在服务发现技术中,服务描述、需求描述和服务匹配是迫切需要解决的关键问题。但由于服务和需求的多样性和复杂性,以及普及计算环境的动态性和异构性,使这些问题更加困难和复杂。所以,寻找一种灵活高效而又准确的方式来进行服务描述、需求描述,进而进行服务匹配,具有非常重要的意义。对现有多种服务发现系统中的服务描述需求描述和服务匹配技术进行比较分析,指出了现有解决方案的一些不足,并对未来的研究进行了展望。     

Service-oriented smart home applications: composition, code generation, deployment, and execution

A smart home usually has a variety of devices or home appliance, instead of designing software for a specific home, this paper proposes a service-oriented framework with a set of ontology systems to support service and device publishing, discovery of devices and their services, composition of control software using existing control services that wrap devices, deployment, and execution of the composed service in an computing environment, monitoring the execution, and recovery from device failure. The ontology systems specify semantic information about devices, services, and workflows used in various smart home, and users can compose and recompose services for their specific needs. New devices, workflows, and services can be added into ontology. Most of the steps in this process can be automated including code generation. For example, service composition will be carried out in three steps: abstract workflow design, function construction, and device discovery, and different codes can be generated for different computing platforms such as Java and Open Services Gateway initiative environments. In this way, a variety of smart home can be constructed rapidly using the framework by discovery and composition using existing services and workflows. This paper illustrates this framework using a media control example to illustrate the ontology, discovery, composition, deployment, execution, monitoring, and recovery.