The Cross-border Electricity Business Cloud Services Platform Based On A Combination Of Cloud Computing Services Composition

Nowadays cloud computing industry has turned to the stage of small-scale application from the stage of import and preparation, so business model has become an integral part in cloud computing. According to the existing problem of commercial operation in cloud computing, by analyzing and forecasting the service composition effects, this paper proposes the theoretical thought of synthetic prediction of risk management for cloud computing services composition systems, gives a synthetic prediction model of services composition, namely multi-layer recurrent model, and analyzes it properties. Then based on multi-layer recurrent model, the construction and application prospect of the cloud service platform based on cloud computing service portfolio is discussed

Facilitating dynamic web service composition with fine-granularity context management

Context is an important factor for the success of dynamic service composition. Although many contextbased AI or workflow approaches have been proposed to support dynamic service composition, there is still an unaddressed issue of the support of fine-granularity context management. In this paper, we propose a granularity-based context model together with an approach to supporting the intelligent context-aware service composing problem. The corresponding case study is provided to show the validity of our approach.<br /

A First Approach on Modelling Staff Proactiveness in Retail Simulation Models

There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most simulation models for investigating service systems are still built in the same way as manufacturing simulation models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as abstract \'actors\' that are goal directed and can behave proactively. In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based simulation modelling to investigate the impact of people management practices on retail productivity. In this paper, we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practices.Retail Performance, Management Practices, Proactive Behaviour, Service Experience, Agent-Based Modelling, Simulation

An ontology-based model management architecture for service innovation

Organizations have indicated renewed interest in service innovation, design and management, given the growth of service sector. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as data and models. Given the global nature of service value chains, there have been ever increasing demands on managing, sharing, and reusing these heterogeneous and distributed resources, both within and across organizational boundaries, through DSS consisting of database management systems (DBMS) and model management systems (MMS). Analogous to DBMS, model management systems focus on the management of decision models, dealing with representation, storage, and retrieval of models as well as a variety of applications such as analysis, reuse, sharing, and composition of models. Recent developments in the areas of semantic web and ontologies have provided a rich tool set for computational reasoning about these resources in an intelligent manner. In this chapter, we leverage these advances and apply service-oriented design principles to propose an ontology-based model management architecture supporting service innovation. The architecture is illustrated with case study scenarios and current state of implementation. The role of potential information technologies in supporting the architecture is also discussed. We then provide a roadmap to make advancements in research in this direction

Ontology based contextualization and context constraints management in web service processes

The flexibility and dynamism of service-based applications impose shifting the validation process to runtime; therefore, runtime monitoring of dynamic features attached to service-based systems is becoming an important direction of research that motivated the definition of our work. We propose an ontology based contextualization and a framework and techniques for managing context constraints in a Web service process for dynamic requirements validation monitoring at process runtime. Firstly, we propose an approach to define and model dynamic service context attached to composition and execution of services in a service process at run-time. Secondly, managing context constraints are defined in a framework, which has three main processes for context manipulation and reasoning, context constraints generation, and dynamic instrumentation and validation monitoring of context constraints. The dynamic requirements attached to service composition and execution are generated as context constraints. The dynamic service context modeling is investigated based on empirical analysis of application scenarios in the classical business domain and analysing previous models in the literature. The orientation of context aspects in a general context taxonomy is considered important. The Ontology Web Language (OWL) has many merits on formalising dynamic service context such as shared conceptualization, logical language support for composition and reasoning, XML based interoperability, etc. XML-based constraint representation is compatible with Web service technologies. The analysis of complementary case study scenarios and expert opinions through a survey illustrate the validity and completeness of our context model. The proposed techniques for context manipulation, context constraints generation, instrumentation and validation monitoring are investigated through a set of experiments from an empirical evaluation. The analytical evaluation is also used to evaluate algorithms. Our contributions and evaluation results provide a further step towards developing a highly automated dynamic requirements management system for service processes at process run-time

Aspect oriented service composition for telecommunication applications

This PhD dissertation investigates how to overcome the negative effects of cross cutting concerns in the development of composite service applications. It proposes a combination of dynamic aspect oriented programming with a rules driven service composition mechanism. This combination allows very flexible utilization of aspects based on run-time data. The thesis contributes a join-point model and it integrates techniques for weaving and advice definition into the underlying composition language and execution engine. A particular focus of the thesis is telecommunication applications with their unique model for utilizing heterogeneous constituent services and their severe real-time requirements. Next to its primary use for modular implementation and flexible deployment of concerns in telecommunication applications, the dissertation discusses AOP as a feature for automated management and customization of service applications. The verification of the proposed solution contributes a detailed assessment of run-time performance, including a theoretical model of the AOP implementation. It allows predicting the performance of various alternative solutions. The proposed solution for combined AOP and service composition provides properties, which directly address challenges in pervasive computing and the Internet of things. Thus, this dissertation advances beyond the telecommunication domain with results applicable to various highly relevant technical developments

A cloud resource management model for the creation and orchestration of social communities

Managing resources, context and data in mobile clouds is a challenging task. Specific aspects of spontaneity, large interaction space and dynamic interaction share a metaphorical resemblance to chemistry, chemical reactions and solutions. In this paper, it is argued that by adopting a nature-inspired chemical computing model, a mobile cloud resource management model can be evolved to serve as the basis for novel service modelling and social computing in mobile clouds. To support the argument, a chemistry inspired computation model, Chemistry for Context Awareness (C2A), is extended with Higher Order Chemical Language (HOCL) and High Level Petri-net Graph (HLPNG) formalisms. A scenario and simulation-based evaluation of the proposed model, focusing on two applications dynamic service composition and social communities identification, is also presented in this paper. The formal encoding of C2A validates its assumptions, enabling formal execution and analysis of context-based interactions that are derived using C2A principles

An intelligent framework for dynamic web services composition in the semantic web

As Web services are being increasingly adopted as the distributed computing technology of choice to securely publish application services beyond the firewall, the importance of composing them to create new, value-added service, is increasing. Thus far, the most successful practical approach to Web services composition, largely endorsed by the industry falls under the static composition category where the service selection and flow management are done a priori and manually. The second approach to web-services composition aspires to achieve more dynamic composition by semantically describing the process model of Web services and thus making it comprehensible to reasoning engines or software agents. The practical implementation of the dynamic composition approach is still in its infancy and many complex problems need to be resolved before it can be adopted outside the research communities. The investigation of automatic discovery and composition of Web services in this thesis resulted in the development of the eXtended Semantic Case Based Reasoner (XSCBR), which utilizes semantic web and AI methodology of Case Based Reasoning (CBR). Our framework uses OWL semantic descriptions extensively for implementing both the matchmaking profiles of the Web services and the components of the CBR engine. In this research, we have introduced the concept of runtime behaviour of services and consideration of that in Web services selection. The runtime behaviour of a service is a result of service execution and how the service will behave under different circumstances, which is difficult to presume prior to service execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. Our XSCBR framework allows annotating such runtime experiences in terms of storing execution values of non-functional Web services parameters such as availability and response time into a case library. The XSCBR algorithm for matchmaking and discovery considers such stored Web services execution experiences to determine the adequacy of services for a particular task. We further extended our fundamental discovery and matchmaking algorithm to cater for web services composition. An intensive knowledge-based substitution approach was proposed to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on Constraint Satisfaction Problem (CSP). From the outset, we adopted a pragmatic approach that focused on delivering an automated Web services discovery and composition solution with the minimum possible involvement of all composition participants: the service provider, the requestor and the service composer. The qualitative evaluation of the framework and the composition tools, together with the performance study of the XSCBR framework has verified that we were successful in achieving our goal

Fiscal policy, public expenditure composition, and growth theory and empirics

This paper responds to the development policy debate involving the World Bank and the IMF on the use of fiscal policy not only for economic stabilization but also to promote economic growth and increase per capita income. A key issue in this debate relates to the effect of the composition of public expenditure on economic growth. Policy makers and some researchers have argued that expenditure on growth-enhancing functions could enhance future revenue and justify the provision of"fiscal space"in the budget. But there are no simple ways to identify the growth-maximizing composition of public expenditure. The current paper lays out a research strategy to explore the effects of fiscal policy, including the composition of public expenditure, on economic growth, using a time series approach. Based on the modeling strategy of Greiner, Semmler and Gong (2005) we develop a general model that features a government that undertakes public expenditure on (a) education and health facilities which enhance human capital, (b) public infrastructure such as roads and bridges necessary for market activity, (c) public administration to support government functions, (d) transfers and public consumption facilities, and (e) debt service. The proposed model is numerically solved, calibrated and the impact of the composition of public expenditure on the long-run per capita income explored for low-, lower-middle- and upper-middle-income countries. Policy implications and practical policy rules are spelled out, the extension to an estimable model indicated, a debt sustainability test proposed, and the out-of-steady-state dynamics studied.Economic Theory&Research,Debt Markets,,Public Sector Expenditure Analysis&Management,Access to Finance