Demand driven web services

Web services are playing a pivotal role in e-business, service intelligence, and service science. Demand-driven web services are becoming important for web services and service computing. However, many fundamental issues are still ignored to some extent. For example, what is the demand theory for web services, what is a demand-driven architecture for web services and what is a demand-driven web service lifecycle remain open. This chapter addresses these issues by examining fundamentals for demand analysis in web services, and proposing a demand-driven architecture for web services. It also proposes a demand-driven web service lifecycle for the main players in web services: Service providers, service requestors and service brokers, respectively. It then provides a unified perspective on demand-driven web service lifecycles. The proposed approaches will facilitate research and development of web services, e-services, service intelligence, service science and service computing

A Framework for Grid-Enabling Scientific Workflow Systems. Architecture and application case studies on interoperability and heterogeneity in support for Grid workflow automation.

Since the early 2000s, Service Oriented Architectures (SOAs) have played a key role in the development of complex applications within a virtual organization (VO) context. Grids and workflows have emerged as vital technologies for addressing the (SOA) paradigm. Given the variety of Grid middleware, scientific workflow systems and Grid workflows available, bringing the two technologies together in a flexible, reusable and generalized way has been largely overlooked, particularly from a scientific end user perspective. The lack of domain focus in this area has led to a slow uptake of Grid technologies. This thesis aims to design a framework for Grid-enabling workflows, which identifies the essential technological components, how these components fit together in layered architecture and the interactions between them. To produce such a framework, this thesis first investigates the definition of a Grid-workflow architecture and mapping Grid functionality to workflow nodes, focusing on striking a balance between performance, usability and the Grid functionality supported. Next, it presents an examination of framework extensions for supporting various forms of Grid heterogeneity, essential for ii VO based collaboration. Given the complex nature of Grid technologies, the work presented here investigates abstracting Grid based workflows through high-level definitions and resolution using semantic technologies. Finally, this thesis presents a way to resolves abstract Grid workflows using semantic technologies and intelligent, autonomous agents. The frameworks presented in this thesis are tested and evaluated within the context of domain-based case studies defined in the SIMDAT, BRIDGE and ARGUGRID EU funded research projects

Quality of service management in service-oriented grids

Grid computing provides a robust paradigm for aggregating disparate resources in a secure and controlled environment. The emerging grid infrastructure gives rise to a class of scientific applications and services in support of collaborative and distributed resource-sharing requirements, as part of teleimmersion, visualization and simulation services. Because such applications operate in a collaborative mode, data must be stored, processed and delivered in a timely manner. Such classes of applications have collaborative and distributed resource-sharing requirements, and have stringent real-time constraints and quality-of-service (QoS) requirements. A QoS management approach is therefore essential to orchestrate and guarantee the interaction among such applications in a distributed computing environment. Grid architectures require an underpinning of QoS support to manage complex computation-intensive and data-intensive applications, as current grid middleware solutions lack QoS provision. QoS guarantees in the grid context have, however, not been given the importance they merit. To enhance its functionality, a computational grid must be overlaid with an advanced QoS architecture to best execute those applications with real-time constraints. This thesis reports on the design and implementation of a software framework, called Grid QoS Management (G-QoSm). G-QoSm incorporates a new QoS management model and provides a service-oriented QoS management approach that supports the Open Grid Service Architecture. Its novel features include grid-service discovery based on QoS attributes, immediate and advance resource reservation, service execution with QoS constraints, and techniques for QoS adaptation to compensate for resource degradation, and to optimise resource allocation while maintaining a service level agreement. The benefits of G-QoSm are demonstrated by prototype test-beds that integrate scientific grid applications and simulate grid data-transfer applications. Results show that the grid application and the data-transfer simulation have better performance when used with the proposed QoS approach. QoS abstractions are presented for building QoS-aware applications, in the context of service-oriented grids. These abstractions are application programming interfaces to facilitate application developers utilising the proposed QoS management solution.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Enterprise 2.0: Collaboration and Knowledge Emergence as a Business Web Strategy Enabler

The Web is becoming in many respects a powerful tool for supporting business strategy as companies are quickly becoming more and more reliant on new Web-based technologies to capitalize on new business opportunities. However, this introduces additional managerial problems and risks that have to be taken into consideration, if they are not to be left behind. In this chapter we explore the Web’s present and future potential in relation to information sharing, knowledge management, innovation management, and the automation of cross-organizational business transactions. The suggested approach will provide entrepreneurs, managers, and IT leaders with guidance on how to adopt the latest Web 2.0-based technologies in their everyday work with a view to setting up a business Web strategy. Specifically, Enterprise 2.0 is presented as a key enabler for businesses to expand their ecosystems and partnerships. Enterprise 2.0 also acts as a catalyst for improving innovation processes and knowledge work

Quality of service management in service-oriented grids

Grid computing provides a robust paradigm for aggregating disparate resources in a secure and controlled environment. The emerging grid infrastructure gives rise to a class of scientific applications and services in support of collaborative and distributed resource-sharing requirements, as part of teleimmersion, visualization and simulation services. Because such applications operate in a collaborative mode, data must be stored, processed and delivered in a timely manner. Such classes of applications have collaborative and distributed resource-sharing requirements, and have stringent real-time constraints and quality-of-service (QoS) requirements. A QoS management approach is therefore essential to orchestrate and guarantee the interaction among such applications in a distributed computing environment. Grid architectures require an underpinning of QoS support to manage complex computation-intensive and data-intensive applications, as current grid middleware solutions lack QoS provision. QoS guarantees in the grid context have, however, not been given the importance they merit. To enhance its functionality, a computational grid must be overlaid with an advanced QoS architecture to best execute those applications with real-time constraints. This thesis reports on the design and implementation of a software framework, called Grid QoS Management (G-QoSm). G-QoSm incorporates a new QoS management model and provides a service-oriented QoS management approach that supports the Open Grid Service Architecture. Its novel features include grid-service discovery based on QoS attributes, immediate and advance resource reservation, service execution with QoS constraints, and techniques for QoS adaptation to compensate for resource degradation, and to optimise resource allocation while maintaining a service level agreement. The benefits of G-QoSm are demonstrated by prototype test-beds that integrate scientific grid applications and simulate grid data-transfer applications. Results show that the grid application and the data-transfer simulation have better performance when used with the proposed QoS approach. QoS abstractions are presented for building QoS-aware applications, in the context of service-oriented grids. These abstractions are application programming interfaces to facilitate application developers utilising the proposed QoS management solution

A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE

L’Ambient Intelligence (AmI) è caratterizzata dall’uso di sistemi pervasivi per monitorare l’ambiente e modificarlo secondo le esigenze degli utenti e rispettando vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti come la scalabilità e la trasparenza per l’utente. Una tecnologia che consente di raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN), caratterizzate da bassi costi e bassa intrusività. Tuttavia, sebbene in grado di effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacità di elaborazione necessarie a supportare un sistema intelligente; d’altra parte senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente sopraffare un sistema centralizzato con un’eccessiva quantità di dettagli superflui. Questo lavoro presenta un’architettura cognitiva in grado di percepire e controllare l’ambiente di cui fa parte, basata su un nuovo approccio per l’estrazione di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione. Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacità computazionali vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire ad un sistema centralizzato intelligente di effettuare ragionamenti di alto livello. L’architettura proposta è stata utilizzata per sviluppare un testbed dotato degli strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo esterno in maniera affidabile, per richiedere servizi ad agenti esterni, l’architettura è stata arricchita con un protocollo di gestione distribuita della reputazione. È stata inoltre sviluppata un’applicazione di esempio che sfrutta le caratteristiche del testbed, con l’obiettivo di controllare la temperatura in un ambiente lavorativo. Quest’applicazione rileva la presenza dell’utente attraverso un modulo per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla base delle preferenze dell’utente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive equipments for monitoring and modifying the environment according to users’ needs, and to globally defined constraints. Furthermore, such systems cannot ignore requirements about ubiquity, scalability, and transparency to the user. An enabling technology capable of accomplishing these goals is represented by Wireless Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However, although provided of in-network processing capabilities, WSNs do not exhibit processing features able to support comprehensive intelligent systems; on the other hand, without this pre-processing activities the wealth of sensory data may easily overwhelm a centralized AmI system, clogging it with superfluous details. This work proposes a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part, based on a new approach to knowledge extraction from raw data, that addresses this issue at different abstraction levels. WSNs are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts in order to carry on symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that will lead the environment to a state as close as possible to the users’ desires, taking into account both implicit and explicit feedbacks from the users, while considering global system-driven goals, such as energy saving. The proposed conceptual architecture was exploited to develop a testbed providing the hardware and software tools for the development and management of AmI applications based on WSNs, whose main goal is energy saving for global sustainability. In order to make the AmI system able to communicate with the external world in a reliable way, when some services are required to external agents, the architecture was enriched with a distributed reputation management protocol. A sample application exploiting the testbed features was implemented for addressing temperature control in a work environment. Knowledge about the user’s presence is obtained through a multi-sensor data fusion module based on Bayesian networks, and this information is exploited by a multi-objective fuzzy controller that operates on actuators taking into account users’ preference and energy consumption constraints

Service Quality and Profit Control in Utility Computing Service Life Cycles

Utility Computing is one of the most discussed business models in the context of Cloud Computing. Service providers are more and more pushed into the role of utilities by their customer's expectations. Subsequently, the demand for predictable service availability and pay-per-use pricing models increases. Furthermore, for providers, a new opportunity to optimise resource usage offers arises, resulting from new virtualisation techniques. In this context, the control of service quality and profit depends on a deep understanding of the representation of the relationship between business and technique. This research analyses the relationship between the business model of Utility Computing and Service-oriented Computing architectures hosted in Cloud environments. The relations are clarified in detail for the entire service life cycle and throughout all architectural layers. Based on the elaborated relations, an approach to a delivery framework is evolved, in order to enable the optimisation of the relation attributes, while the service implementation passes through business planning, development, and operations. Related work from academic literature does not cover the collected requirements on service offers in this context. This finding is revealed by a critical review of approaches in the fields of Cloud Computing, Grid Computing, and Application Clusters. The related work is analysed regarding appropriate provision architectures and quality assurance approaches. The main concepts of the delivery framework are evaluated based on a simulation model. To demonstrate the ability of the framework to model complex pay-per-use service cascades in Cloud environments, several experiments have been conducted. First outcomes proof that the contributions of this research undoubtedly enable the optimisation of service quality and profit in Cloud-based Service-oriented Computing architectures