The phrase Internet of Things (IoT) heralds a vision of the future Internet where connecting physical things, from banknotes to bicycles, through a network will let them take an active part in the Internet, exchanging information about themselves and their surroundings. This will give immediate access to information about the physical world and the objects in it--leading to innovative services and increase in efficiency and productivity. This paper studies the state-of-the-art of IoT and presents the key technological drivers, potential applications, challenges and future research areas in the domain of IoT. IoT definitions from different perspective in academic and industry communities are also discussed and compared. Finally some major issues of future research in IoT are identified and discussed briefly.

pdf/internet-of-things-applications-and-challenges-in-technology-3sw4m7dkqc.pdf

Internet of Things: Applications and Challenges in Technology and Standardization

Hawaii International Conference on System Sciences

CArtAgO is a platform and infrastructure providing ageneral-purpose programming model for building shared computational worlds – referred here as work environments – that agents, possibly belonging to heterogeneous agent platforms, can exploit to work together inside a Multi-Agent System. Being based on the A&A (Agents and Artifacts) conceptual model, CArtAgO work environments are modelled and engineered interms of set of artifacts programmed by MAS designers, collected in workspaces. From the agent view point, artifacts are first-class entities representing resources and tools that agents can dynamically instantiate, share and use to support their individual and collective activities. After describing the basic motivations behind the approach, the chapter provides an overview of the programming model promoted by CArtAgO for the definition of artifacts (MAS designer’s viewpoint)and for the use of artifacts(agent’s viewpoint), using Jason as reference platform for MAS programming.

Environment Programming in CArtAgO

An engineering framework for Service-Oriented Intelligent Manufacturing Systems

Autonomic computing is the solution proposed to cope with the complexity of today's computing environments. Self-management, an important element of autonomic computing, is also characteristic of single and multiagent systems, as well as systems based on service-oriented architectures. Combining these technologies can be profitable for all - in particular, for the development of autonomic computing systems.

/pdf/agents-and-service-oriented-computing-for-autonomic-3w0mijegqk.pdf

Agents and Service-Oriented Computing for Autonomic Computing: A Research Agenda

Today's service-oriented systems realize many ideas from the research conducted a decade or so ago in multiagent systems. Because these two fields are so deeply connected, further advances in multiagent systems could feed into tomorrow's successful service-oriented computing approaches. This article describes a 15-year roadmap for service-oriented multiagent system research.

/pdf/research-directions-for-service-oriented-multiagent-systems-m2j6hmx3w9.pdf

Research directions for service-oriented multiagent systems

This paper describes the current state of the OmniSeer system. OmniSeer supports intelligence analysts in the handling of massive amounts of data, the construction of scenarios, and the management of hypotheses. OmniSeer models analysts with dynamic user models that capture an analyst's context, interests, and preferences, thus enabling more efficient and effective information retrieval. OmniSeer explicitly represents the prior and tacit knowledge of analysts, thus enabling transfer and reuse of such knowledge. Both the user and cognitive models employ a Bayesian network fragment representation, which supports principled probabilistic reasoning and analysis. An independent evaluation of OmniSeer was carried out at NIST and will be used to guide further development.

/pdf/omniseer-a-cognitive-framework-for-user-modeling-reuse-of-1bdymki9dv.pdf

OmniSeer: A Cognitive Framework for User Modeling, Reuse of Prior and Tacit Knowledge, and Collaborative Knowledge Services

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Research directions for service-oriented multiagent systems

OmniSeer: A Cognitive Framework for User Modeling, Reuse of Prior and Tacit Knowledge, and Collaborative Knowledge Services