EASY: Efficient semAntic Service discoverY in pervasive computing environments with QoS and context support

Pervasive computing environments are populated with networked software and hardware resources providing various functionalities that are abstracted, thanks to the Service Oriented Architecture paradigm, as services. Within these environments, service discovery enabled by service discovery protocols (SDPs) is a critical functionality for establishing ad hoc associations between service providers and service requesters. Furthermore, the dynamics, the openness and the user-centric vision aimed at by the pervasive computing paradigm call for solutions that enable rich, semantic, context- and QoS-aware service discovery. Although the semantic Web paradigm envisions to achieve such support, current solutions are hardly deployable in the pervasive environment due to the costly underlying semantic reasoning with ontologies. In this article, we present EASY to support efficient, semantic, context- and QoS-aware service discovery on top of existing SDPs. EASY provides EASY-L, a language for semantic specification of functional and non-functional service properties, as well as EASY-M, a corresponding set of conformance relations. Furthermore, EASY provides solutions to efficiently assess conformance between service capabilities. These solutions are based on an efficient encoding technique, as well as on an efficient organization of service repositories (caches), which enables both fast service advertising and discovery. Experimental results show that the deployment of EASY on top of an existing SDP, namely Ariadne, enhancing it only with slight changes to EASY-Ariadne, enables rich semantic, context- and QoS-aware service discovery, which furthermore performs better than the classical, rigid, syntactic matching, and improves the scalability of Ariadne.     

面向服务计算中QoS参考矩阵研究

全面讨论了QoS的定义,提出了面向服务计算中的QoS参考矩阵,给出了面向服务计算中的QoS特性,详细介绍了通用QoS模型及QoS的4个视图等问题.参考矩阵的提出,方便了服务提供者及服务使用者的QoS相关情况的调整,并可以快速便捷地评估一项服务(单用户)的性能好坏.     

Ubiquitous computing: connecting Pervasive computing through Semantic Web

Ubiquitous computing refers to building a global computing environment where seamless and invisible access to computing resources is provided to the user. Pervasive computing deals with acquiring context knowledge from the environment and providing dynamic, proactive and context-aware services to the user. A Ubiquitous computing environment is created by sharing knowledge and information between Pervasive computing environments. In this paper we propose a framework that uses the potential of the Semantic Web to weave Pervasive computing environments into a Ubiquitous computing environment. We discuss how the collaboration of these Pervasive environments can create an effective Ubiquitous computing environment referred herein as the Integrated Global Pervasive Computing Framework (IGPF). We test the effectiveness of the Ubiquitous environment through a small scenario from a prototype system that we have implemented over this framework to handle medical emergency scenario.     

Semantic-based automatic service composition with functional and non-functional requirements in design time: A genetic algorithm approach

ContextIn recent years, the composition of ready-made and loosely coupled services into desired systems is a common industrial approach and a widely followed research topic in academia. In the field, the current research trend is to automate this composition; however, each of the existing efforts automates only a component of the entire problem. Therefore, a real automation process that addresses all composition concerns is lacking.ObjectiveThe objective is to first identify the present composition concerns and subsequently to devise a compositional approach that covers all concerns. Ultimately, we conduct a number of experiments to investigate the proposed approach.MethodWe identify the current composition concerns by surveying and briefly describing the existing approaches. To include all of the identified concerns, the solution space that must be searched is highly dimensioned. Thus, we adopt a genetic algorithm (GA) due to its ability to solve problems with such characteristics. Proposed GA-based approach is designed with four unusual independent fitness functions. Additionally, experiments are carried out and discussions are presented for verification of the design, including the necessity for and correctness of the independence and priority of the four fitness functions.ResultsThe case studies demonstrate that our approach can automatically generate the required composite services and considers all identified concerns simultaneously. The results confirm the need for the independence of the fitness function and also identify a more efficient priority for these functions.ConclusionsIn this study, we present an all-inclusive automatic composer that does not require human intervention and effort during the composition process and is designed for users who must address multiple composition concerns simultaneously, including requirements for overall functionality, internally workable dataflow, and non-functional transaction and quality-of-service considerations. Such multiple and complex composition requirements cannot be satisfied by any of the previous single-concern composition approaches.     

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.     

Iterative selection algorithm for service composition in distributed environments

In service oriented architecture （SOA）, service composition is a promising way to create new services. However, some technical challenges are hindering the application of service composition. One of the greatest challenges for composite service provider is to select a set of services to instantiate composite service with end- to-end quality of service （QoS） assurance across different autonomous networks and business regions. This paper presents an iterative service selection algorithm for quality driven service composition. The algorithm runs on a peer-to-peer （P2P） service execution environment--distributed intelligent service execution （DISE）, which provides scalable QoS registry, dynamic service selection and service execution services. The most significant feature of our iterative service selection algorithm is that it can work on a centralized QoS registry as well as cross decentralized ones. Network status is an optional factor in our QoS model and selection algorithm. The algorithm iteratively selects services following service execution order, so it can be applied either before service execution or at service run-time without any modification. We test our algorithm with a series of experiments on DISE. Experimental results illustrated its excellent selection and outstanding performance.     

Trust force-based service selection in pervasive computing environments

Trust is an important aspect of decision making for pervasive applications and it is important to choose and use services efficiently in pervasive computing environments. Trust force is presented to specify trust relationships among interactive entities in a pervasive computing environment by using experience and knowledge in a social network and the coulomb＇s law in real word. Based on trust force, a Trust Management and Service Selection model are presented, named TMSS. TMSS was tested and the experimental results show that our method for selecting service is not only more efficient than traditional and heuristic methods, but also can identify good services from bad ones.     

A hierarchical, agent-based service oriented architecture for smart environments

Service Oriented Architectures, which allow for the integration of different subsystems and of applications running on different devices and platforms, may be very suitable to solve the problem of service personalization in large smart environments like cities, where the number of potential users and potentially available services is rapidly growing. Taking this into account, we have designed an agent-based service oriented architecture for smart spaces. Two of the greatest challenges in the design of such a solution are providing effective device, service and context federation and composition mechanisms and handling user mobility. For the first challenge, we have designed a hierarchical architecture and developed a set of inheritance, aggregation and access mechanisms for devices, services and context. To handle user mobility, we have followed three different strategies, using stationary, mobile or nomadic agents. In this paper, we describe the main aspects of our architecture and perform an experimental evaluation to determine the advantages and drawbacks of the different strategies.     

保证服务质量的Web服务优化选取

快速、准确地发现满足用户需求的Web服务是目前Web服务发现的一个研究重点。文中提出了一个基于服务质量的语义Web服务发现框架。首先采用遗传算法来实现服务的聚类预处理,以此来降低服务的查找空间,提高服务的查询效率。进一步,针对服务请求者对服务质量的需求,实现了基于WSMO-QoS的服务匹配策略。最后,实验结果表明了所提方法的有效性。     

基于Agent的Web服务QoS协商研究

协商机制是协调Web服务使用者和提供者的不同QoS(quality of service)需求的一种重要方法,通过扩展的协商代理中介角色完成双方的协商.扩展了Web服务的描述,增加了关于QoS的信息,将协商双方的偏好和协商策略参数化,使得双方可以通过简单设置参数来指定,从而Agent可以根据这些信息代表协商双方进行自动协商,并将协商结果转化为合同,更好地约束服务的交付.     

Cloud computing service composition: A systematic literature review

The increasing tendency of network service users to use cloud computing encourages web service vendors to supply services that have different functional and nonfunctional (quality of service) features and provide them in a service pool. Based on supply and demand rules and because of the exuberant growth of the services that are offered, cloud service brokers face tough competition against each other in providing quality of service enhancements. Such competition leads to a difficult and complicated process to provide simple service selection and composition in supplying composite services in the cloud, which should be considered an NP-hard problem. How to select appropriate services from the service pool, overcome composition restrictions, determine the importance of different quality of service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research.     

A probabilistic approach to modeling and estimating the QoS of web-services-based workflows

Web services promise to become a key enabling technology for B2B e-commerce. One of the most-touted features of Web services is their capability to recursively construct a Web service as a workflow of other existing Web services. The quality of service (QoS) of Web-services-based workflows may be an essential determinant when selecting constituent Web services and determining the service-level agreement with users. To make such a selection possible, it is essential to estimate the QoS of a WS workflow based on the QoSs of its constituent WSs. In the context of WS workflow, this estimation can be made by a method called QoS aggregation. While most of the existing work on QoS aggregation treats the QoS as a deterministic value, we argue that due to some uncertainty related to a WS, it is more realistic to model its QoS as a random variable, and estimate the QoS of a WS workflow probabilistically. In this paper, we identify a set of QoS metrics in the context of WS workflows, and propose a unified probabilistic model for describing QoS values of a broader spectrum of atomic and composite Web services. Emulation data are used to demonstrate the efficiency and accuracy of the proposed approach.     

Activity-based computing: support for mobility and collaboration in ubiquitous computing

This paper presents the design philosophy of activity-based computing (ABC), which addresses mobility and cooperation in human work activities. Furthermore, it presents the ABC framework, which is a ubiquitous computing infrastructure supporting ABC. The idea of ABC and the aim of the ABC framework is to: (1) support human activity by managing its collection of work tasks on a computer, (2) support mobility by distributing activities across heterogeneous computing environments, (3) support asynchronous collaboration by allowing several people to participate in an activity, and (4) support synchronous, real-time collaboration by enabling desktop conferencing by sharing the activity across several clients. During a period of two years, the ABC framework has been co-designed and evaluated in close cooperation with a range of clinicians in a hospital.

Semantic web service composition testbed

A huge amount of web services are deployed on the Web, nowadays. These services can be used to fulfill online requests. Requests are getting more and more complicated over time. So, there exists a lot of frequent request that cannot be fulfilled using just one web service. For using web services, composing individual services to create the added-value composite web service to fulfill the user request is necessary in most cases. Web services can be composed manually but it is a too tedious and time consuming task. The ability of automatic web service composition to create a new composite web service is one of the key enabling features for the future for the semantic web. There are some successful methods for automatic web service composition, but the lack of standard, open, and lightweight test environment makes the comparison and evaluation of these composition methods impossible. In this paper we propose an architecture for a light weight and scalable testbed to execute, test and evaluate automatic web service composition algorithms. The architecture provides mandatory components for implementing and evaluation of automatic web service composition algorithms. Also, this architecture provides some extension mechanisms to extend its default functionalities. We have also given reference implementations for web service matchmaking and composition. Also, some scenarios for testing and evaluating the testbed are given. We have found that the performance of the composition method will dramatically decrease as the number of web services increases.     

Affective e-Learning in residential and pervasive computing environments

This article examines how emerging pervasive computing and affective computing technologies might enhance the adoption of ICT in e-Learning which takes place in the home and wider city environment. In support of this vision we describe two cutting edge ICT environments which combine to form a holistic connected future learning environment. The first is the iSpace, a specialized digital-home test-bed that represents the kind of high-tech, context aware home-based learning environment we envisage future learners using, the second a sophisticated pervasive e-Learning platform that typifies the educational delivery platform our research is targeting. After describing these environments we then present our research that explores how emotion evolves during the learning process and how to leverage emotion feedback to provide adaptive e-Learning system. The motivation driving this work is our desire to improve the performance of the educational experience by developing learning systems that recognize and respond appropriately to emotions exhibited by learners. Finally we report on the results about the emotion recognition from physiological signals which achieved a best-case accuracy rate of 86.5% for four types of learning emotion. To the best of our knowledge, this is the first report on emotion detection by data collected from close-to-real-world learning sessions. We also report some finding about emotion evolution during learning, which are still not enough to validate Kort’s learning spiral model.

Design of a service oriented architecture for efficient resource allocation in media environments

In many business domains, Grids and Service Oriented Architectures are considered to improve application design, integration and execution. In the audiovisual industry, applications are very data-intensive, time-constrained and computationally demanding, and design of a Service Oriented Architecture in this domain is no straightforward task. Efficient resource allocation-especially in terms of network usage-is paramount to meet users’ requirements in terms of deadlines and responsiveness, and offer high scalability at the same time. We present a resource- and network-aware management architecture addressing the issues in media environments, incorporating a number of scheduling algorithms and advance reservation systems to ensure efficient resource usage.     

Context reasoning using extended evidence theory in pervasive computing environments

Most existing context reasoning approaches implicitly assume that contexts are precise and complete. This assumption cannot be held in pervasive computing environments, where contexts are often imprecise and incomplete due to unreliable connectivity, user mobility and resource constraints. To this end, we propose an approach called CRET: Context Reasoning using extended Evidence Theory. CRET applies the evidence theory to context reasoning in pervasive computing environments. Because evidence theory is limited by two fundamental problems–computation-intensiveness and Zadeh paradox, CRET presents evidence selection and conflict resolution strategies. Empirical study shows that CRET is desirable for pervasive applications.     

CERA: a collaborative environment reference architecture for interoperable CWE systems

In this paper, we present the collaborative environment reference architecture (CERA) with the aim of supporting collaborative work environment (CWE) interoperability. The vision of CERA is to support users who are engaged in common collaborative spaces with similar work processes to work and collaborate seamlessly together, despite their use of proprietary CWE tools and systems. The underlying CERA concepts, design principles, and models are discussed, as well as the architectural decisions made as a result of the extended requirements analysis exercise. Furthermore, we present results from the Ecospace () project as an example of a CERA instantiation which focuses on facilitating users collaborating across different CWE systems, namely BSCW, NetWeaver, and BC. We conclude with future research and implementation directions.