Remote service discovery and binding architecture for soft real-time QoS in indoor location-based service

Indoor location-based service (LBS) is generally distinguished from web services that have no physical location and user context. In particular, various resources have dynamic and frequent mobility in indoor environments. In addition, an indoor LBS includes numerous service lookups being requested concurrently and frequently from several locations, even through a network infrastructure requiring high scalability in indoor environments. The traditional centralized LBS approach needs to maintain a geographical map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor LBS platform with regional cooperation among devices. A service lookup algorithm based on the proposed distributed architecture searches for the shortest physical path to the nearest service resource. A continuous service binding mechanism guarantees a probabilistic real-time QoS regardless of dynamic and frequent mobility in a soft real-time system such as an indoor LBS. Performance evaluation of the proposed algorithm and platform is compared to the traditional centralized architecture in the experimental evaluation of scalability and real test bed environments.     

A semantic service discovery approach for ubiquitous computing

Services in the ubiquitous computing are heterogeneous in nature. To be pervasive, these services should be defined in terms of their functionality and capabilities rather than the meaningless Universally Unique IDentifiers (UUIDs) or types of services. With that, clients can access the proper service based on semantic requests, rather then a pre-configured profile. In this paper, we study the requirements for semantic query to be feasible in service discovery processes. Current discovery protocols and the concept of semantics are brought together to construct a framework to realize the semantic service discovery for ubiquitous computing. Many issues are discussed in relation to service discovery topologies, ontology languages, and semantic query languages.     

A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

基于服务上下文的Web服务发现机制

服务发现成为Web服务组合研究的重点,为解决服务组合过程中服务发现方法存在动态适应能力不足,提出了一种基于服务上下文的Web服务发现机制.该机制将一种服务本体描述语言OWL-S和一种基于服务上下文的服务发现算法相结合,利用语义描述服务的信息,同时定义了服务上下文信息并进行服务上下文匹配来发现所需服务.实验结果表明,基于服务上下文的Web服务发现机制能够提高服务发现的准确性,具有较好地动态适应性.     

基于意图的物联网服务描述与发现

在物联网服务发现过程中,用户通常用自己的意图表达需求,而服务描述是对服务功能的说明,因此两者的不匹配会影响服务发现的准确率。同时随着服务的种类不断增多,服务发现的准确率不断降低。为了解决上述问题,提出在物联网服务描述中引入意图服务本体的方法,并在意图服务本体中扩展服务上下文和QoS。扩展后的意图服务本体存储在语义化服务描述OWL-S文件中,能够以意图的方式表达服务功能,丰富物联网服务描述的语义,提高服务发现的准确率。仿真结果表明,所提服务描述方法以及相应的服务发现算法相对于传统服务发现方法能提升6.7%的准确率。     

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.     

Service discovery for GRID computing using LCAN-mapped hierarchical directories

Hierarchical Directories were introduced to provide Service Address Routing (Scherson, Valencia in: Proceedings of the international symposium on parallel architectures, algorithms and networks (I-SPAN), Las Vegas, USA, 2005) embedded in a class of Hierarchical Interconnection Networks known as Least Common Ancestor Networks (LCANs). The algorithms for service discovery in SAR are shown to extend to the GRID when the LCAN is effectively mapped onto the loosely coupled Internet connected computing cluster. In SAR, nodes (programs) communicate by invoking services from the network itself. It is the network-embedded service discovery and addressing mechanism that provides the physical binding. Even though the SAR concept was conceived for tightly coupled interconnection networks, it can also be applied to an Internet GRID system by mapping the SAR network directory (considered to be LCAN-embedded) onto the loosely coupled GRID. Once the network is successfully mapped to the subjacent network, all scalability, fault-tolerance, functionality, and every other advantage of an LCAN-SAR system are automatically available in the resulting implementation. We present a novel way to perform a completely distributed and dynamic service discovery that not only performs faster lookups by avoiding well known bottlenecks in centralized systems, but has inherent fault tolerance mechanisms.     

S-Club: an overlay-based efficient service discovery mechanism in CROWN Grid

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches. Chunming Hu is a research staff in the Institute of Advanced Computing Technology at the School of Computer Science and Engineering, Beihang University, Beijing, China. He received his B.E. and M.E. in Department of Computer Science and Engineering in Beihang University. He received the Ph.D. degree in School of Computer Science and Engineering of Beihang University, Beijing, China, 2005. His research interests include peer-to-peer and grid computing; distributed systems and software architectures. Yanmin Zhu is a Ph.D. candidate in the Department of Computer Science, Hong Kong University of Science and Technology. He received his B.S. degree in computer science from Xi’an Jiaotong University, Xi’an, China, in 2002. His research interests include grid computing, peer-to-peer networking, pervasive computing and sensor networks. He is a member of the IEEE and the IEEE Computer Society. Jinpeng Huai is a Professor and Vice President of Beihang University. He serves on the Steering Committee for Advanced Computing Technology Subject, the National High-Tech Program (863) as Chief Scientist. He is a member of the Consulting Committee of the Central Government’s Information Office, and Chairman of the Expert Committee in both the National e-Government Engineering Taskforce and the National e-Government Standard office. Dr. Huai and his colleagues are leading the key projects in e-Science of the National Science Foundation of China (NSFC) and Sino-UK. He has authored over 100 papers. His research interests include middleware, peer-to-peer (P2P), grid computing, trustworthiness and security. Yunhao Liu received his B.S. degree in Automation Department from Tsinghua University, China, in 1995, and an M.A. degree in Beijing Foreign Studies University, China, in 1997, and an M.S. and a Ph.D. degree in computer science and engineering at Michigan State University in 2003 and 2004, respectively. He is now an assistant professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include peer-to-peer computing, pervasive computing, distributed systems, network security, grid computing, and high-speed networking. He is a senior member of the IEEE Computer Society. Lionel M. Ni is chair professor and head of the Computer Science and Engineering Department at Hong Kong University of Science and Technology. Lionel M. Ni received the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, Indiana, in 1980. He was a professor of computer science and engineering at Michigan State University from 1981 to 2003, where he received the Distinguished Faculty Award in 1994. His research interests include parallel architectures, distributed systems, high-speed networks, and pervasive computing. A fellow of the IEEE and the IEEE Computer Society, he has chaired many professional conferences and has received a number of awards for authoring outstanding papers.     

面向服务簇的服务体系结构及服务发现

为了缩减服务查找空间,提高服务发现效率,提出服务簇的概念。将具有相似或相同服务功能的Web服务封装为一个服务簇,构建基于服务簇的服务请求/响应模式。给出了服务簇的形式化定义、面向服务簇的服务体系结构以及服务簇模式下的最优服务发现算法。仿真实验以10000个Web服务作为测试源,在服务簇数目不大于1000时,服务簇模式下的服务查找时间以及服务再查找时间均小于600ms,而当前服务响应模式下,上述时间均大于900ms。实验结果表明：基于服务簇的服务请求/响应模式可以显著提高服务发现效率,并能大幅度降低服务再查找的时间。     

Context-based caching and routing for P2P web service discovery

In modern heterogeneous environments, such as mobile, pervasive and ad-hoc networks, architectures based on web services offer an attractive solution for effective communication and inter-operation. In such dynamic and rapidly evolving environments, efficient web service discovery is an important task. Usually this task is based on the input/output parameters or other functional attributes, however this does not guarantee the validity or successful utilization of retrieved web services. Instead, non-functional attributes, such as device power features, computational resources and connectivity status, that characterize the context of both service providers and consumers play an important role to the quality and usability of discovery results. In this paper we introduce context-awareness in web service discovery, enabling the provision of the most appropriate services at the right location and time. We focus on context-based caching and routing for improving web service discovery in a mobile peer-to-peer environment. We conducted a thorough experimental study, using our prototype implementation based on the JXTA framework, while simulations are employed for testing the scalability of the approach. We illustrate the advantages that this approach offers, both by evaluating the context-based cache performance and by comparing the efficiency of location-based routing to broadcast-based approaches. Recommended by: Zakaria Maamar     

基于WSMO服务质量的语义Web服务发现框架

当前对Web服务进行语义描述最流行的两个框架是OWL-S和WSMO,但它们主要都是从服务功能的角度对服务进行描述,缺乏对服务质量的明确刻画,导致服务请求者难以得到最佳服务.针对此问题,对WSMO规范进行了扩展,定义了一个服务质量(QoS)的元模型--WSMO-QoS,给出了QoS的本体词汇.在此基础上提出了基于QoS的语义Web服务发现框架,并给出一个从基本描述、IOPE、QoS三个层次实现服务匹配的算法.最后,实验结果验证了该服务匹配算法的有效性.     

基于语义的Web服务发现核心技术研究

在研究Web服务本体描述语言OWL S缺乏对服务质量的明确刻画的基础上,引入服务质量本体QoSOn对OWL S规范进行扩展。其次,提出了“两阶段”匹配模型,该算法首先经过基于服务分类的匹配剔除不相关的服务,然后引入服务相似度来度量候选广告服务和请求服务之间的相似程度;候选服务和请求服务之间的相似度是通过OWL S Profile的功能相似度和QoSOn本体的服务质量相似度两个方面进行综合评估的。最后,通过对比实验证明了该匹配算法的可行性和有效性。     

基于历史用户QoS感知的Web服务发现方法

目前的Web服务发现方法,由于没有充分利用用户情境信息,导致在服务发现时间和结果准确率方面存在不足。首先对包括当前用户在内的情境相似的用户进行了聚类,缩小了服务发现的范围;然后,在此基础上利用当前用户偏好信息及情境相似的历史用户感知到的候选服务的QoS数据,给出了一种基于历史用户QoS感知的Web服务发现方法,包括候选服务的QoS数据获取和综合权重计算;最后,结合实验并与其他Web服务发现方法进行比较,证明了该方法在服务发现结果的准确率和时间效率方面均有了一定的提升。     

一种基于扩展ONS的链式发现服务方法

总结了目前最新的EPC网络发现服务方法,在此基础上,提出了一种基于扩展ONS的链式发现服务方法。该方法通过扩展ONS静态信息,解决了EPC物品的当前位置的存储问题,并通过在企业EPCIS中维护指针数据库,从而实现了链式发现服务。详细介绍了链式发现服务的工作过程,对其可靠性和安全性等关键点做了细致讨论,并提出了相应的应对策略。最后,从多个方面出发,将该方法与其他方法进行比较,论证了该方法的优越性。     

Self-scaling cooperative discovery of service compositions in unstructured P2P networks

We propose an efficient technique for improving the performance of automatic and cooperative compositions in unstructured Peer-to-Peer networks during service discovery. The technique exploits a probabilistic forwarding algorithm that uses different sources of knowledge, such as network density and service grouping, to reduce the amount of messages exchanged in the network. The technique, analysed in several network configurations by using a simulator to observe resolution time, recall and message overhead, presents good performance especially in dense and large-scale service networks.     

WSB: a broker‐centric framework for quality‐driven web service discovery

Web service interfaces can be discovered through several means, including service registries, search engines, service portals, and peer‐to‐peer networks. But discovering Web services in such heterogeneous environments is becoming a challenging task and raises several concerns, such as performance, reliability, and robustness. In this paper, we introduce the Web Service Broker (WSB) framework that provides a universal access point for discovering Web services. WSB uses a crawler to collect the plurality of Web services disseminated throughout the Web, continuously monitor the behavior of Web services in delivering the expected functionality, and enable clients to articulate service queries tailored to their needs. The framework features ranking algorithms we have developed which are capable of ranking services according to Quality of Web Service parameters. WSB can be seamlessly integrated into the existing service‐oriented architectures. Copyright © 2010 John Wiley & Sons, Ltd.     

服务发现机制研究进展

以现有服务发现机制发展过程为主线,重点分析了独立服务发现平台和集成式服务发现平台的主要工作机制和优缺点,在归纳和总结现有服务发现机制普遍采用烟囱式、一视同仁以及叠加式策略等问题的同时,提出了未来服务发现机制的研究方向。