75,004 research outputs found

    Designing and managing Organizational Interoperability with organizational capabilities and roadmaps

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    This paper discusses organizational interoperability issues in through the study of two cases. Then it presents a framework which can help to design and manage this interoperability, by driving the development of “organizational capabilities”.Organization learning, Functional interoperability

    Addressing the Challenges in Federating Edge Resources

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    This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

    Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

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    Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

    Designing community care systems with AUML

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    This paper describes an approach to developing an appropriate agent environment appropriate for use in community care applications. Key to its success is that software designers collaborate with environment builders to provide the levels of cooperation and support required within an integrated agent–oriented community system. Agent-oriented Unified Modeling Language (AUML) is a practical approach to the analysis, design, implementation and management of such an agent-based system, whilst providing the power and expressiveness necessary to support the specification, design and organization of a health care service. The background of an agent-based community care application to support the elderly is described. Our approach to building agent–oriented software development solutions emphasizes the importance of AUML as a fundamental initial step in producing more general agent–based architectures. This approach aims to present an effective methodology for an agent software development process using a service oriented approach, by addressing the agent decomposition, abstraction, and organization characteristics, whilst reducing its complexity by exploiting AUML’s productivity potential. </p

    Simulation of the Long-Term Effects of Decentralized and Adaptive Investments in Cross-Agency Interoperable and Standard IT Systems

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    Governments have come under increasing pressure to promote horizontal flows of information across agencies, but investment in cross-agency interoperable and standard systems have been minimally made since it seems to require government agencies to give up the autonomies in managing own systems and its outcomes may be subject to many external and interaction risks. By producing an agent-based model using 'Blanche' software, this study provides policy-makers with a simulation-based demonstration illustrating how government agencies can autonomously and interactively build, standardize, and operate interoperable IT systems in a decentralized environment. This simulation designs an illustrative body of 20 federal agencies and their missions. A multiplicative production function is adopted to model the interdependent effects of heterogeneous systems on joint mission capabilities, and six social network drivers (similarity, reciprocity, centrality, mission priority, interdependencies, and transitivity) are assumed to jointly determine inter-agency system utilization. This exercise simulates five policy alternatives derived from joint implementation of three policy levers (IT investment portfolio, standardization, and inter-agency operation). The simulation results show that modest investments in standard systems improve interoperability remarkably, but that a wide range of untargeted interoperability with lagging operational capabilities improves mission capability less remarkably. Nonetheless, exploratory modeling against the varying parameters for technology, interdependency, and social capital demonstrates that the wide range of untargeted interoperability responds better to uncertain future states and hence reduces the variances of joint mission capabilities. In sum, decentralized and adaptive investments in interoperable and standard systems can enhance joint mission capabilities substantially and robustly without requiring radical changes toward centralized IT management.Public IT Investment, Interoperability, Standardization, Social Network, Agent-Based Modeling, Exploratory Modeling
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