SPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from high-level descriptions of distributed algorithms to detailed code for controlling telephone exchanges. The paper gives an overview of the design and structure of the verifier, reviews its theoretical foundation, and gives an overview of significant practical applications.

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The model checker SPIN

Explanation in artificial intelligence: Insights from the social sciences

http://emamispnu.persiangig.com/Projects/Cloud%20Computing/science_2.pdf

Review: A survey on security issues in service delivery models of cloud computing

Our goal in this paper is to introduce and motivate a methodology, called Tropos,1 for building agent oriented software systems. Tropos is based on two key ideas. First, the notion of agent and all related mentalistic notions (for instance goals and plans) are used in all phases of software development, from early analysis down to the actual implementation. Second, Tropos covers also the very early phases of requirements analysis, thus allowing for a deeper understanding of the environment where the software must operate, and of the kind of interactions that should occur between software and human agents. The methodology is illustrated with the help of a case study. The Tropos language for conceptual modeling is formalized in a metamodel described with a set of UML class diagrams.

/pdf/tropos-an-agent-oriented-software-development-methodology-4cfpp4zfvj.pdf

Tropos: An Agent-Oriented Software Development Methodology

Over the Internet today, computing and communications environments are significantly more complex and chaotic than classical distributed systems, lacking any centralized organization or hierarchical control. There has been much interest in emerging Peer-to-Peer (P2P) network overlays because they provide a good substrate for creating large-scale data sharing, content distribution, and application-level multicast applications. These P2P overlay networks attempt to provide a long list of features, such as: selection of nearby peers, redundant storage, efficient search/location of data items, data permanence or guarantees, hierarchical naming, trust and authentication, and anonymity. P2P networks potentially offer an efficient routing architecture that is self-organizing, massively scalable, and robust in the wide-area, combining fault tolerance, load balancing, and explicit notion of locality. In this article we present a survey and comparison of various Structured and Unstructured P2P overlay networks. We categorize the various schemes into these two groups in the design spectrum, and discuss the application-level network performance of each group.

/pdf/a-survey-and-comparison-of-peer-to-peer-overlay-network-cpcv2ij1hk.pdf

A survey and comparison of peer-to-peer overlay network schemes

Service-oriented computing promotes the idea of assembling application components into a network of services that can be loosely coupled to create flexible, dynamic business processes and agile applications that span organizations and computing platforms An SOC research road map provides a context for exploring ongoing research activities

/pdf/service-oriented-computing-state-of-the-art-and-research-2qrewh4ft0.pdf

Service-Oriented Computing: State of the Art and Research Challenges

1 Introduction and Overview I Classical Planning 2 Representations for Classical Planning*3 Complexity of Classical Planning*4 State-Space Planning*5 Plan-Space Planning II Neoclassical Planning 6 Planning-Graph Techniques*7 Propositional Satisfiability Techniques*8 Constraint Satisfaction Techniques III Heuristics and Control Strategies 9 Heuristics in Planning*10 Control Rules in Planning*11 Hierarchical Task Network Planning*12 Control Strategies in Deductive Planning IV Planning with Time and Resources 13 Time for Planning*14 Temporal Planning*15 Planning and Resource Scheduling V Planning under Uncertainty 16 Planning based on Markov Decision Processes*17 Planning based on Model Checking*18 Uncertainty with Neo-Classical Techniques VI Case Studies and Applications 19 Space Applications*20 Planning in Robotics*21 Planning for Manufacturability Analysis*22 Emergency Evacuation Planning *23 Planning in the Game of Bridge VII Conclusion 24 Conclusion and Other Topics VIII Appendices A Search Procedures and Computational Complexity*B First Order Logic*C Model Checking

/pdf/automated-planning-theory-and-practice-2pv1zr0abd.pdf

Automated Planning, Theory And Practice

Automated Planning: Theory & Practice

Service-Oriented Computing (SOC) is a new computing paradigm that utilizes services as the basic constructs to support the development of rapid, low-cost and easy composition of distributed applications even in heterogeneous environments. The promise of Service-Oriented Computing is a world of cooperating services where application components are assembled with little effort into a network of services that can be loosely coupled to create flexible dynamic business processes and agile applications that may span organizations and computing platforms. The subject of Service-Oriented Computing is vast and enormously complex, spanning many concepts and technologies that find their origins in diverse disciplines that are woven together in an intricate manner. In addition, there is a need to merge technology with an understanding of business processes and organizational structures, a combination of recognizing an enterprise's pain points and the potential solutions that can be applied to correct them. The materi...

/pdf/service-oriented-computing-a-research-roadmap-iuym80iybz.pdf

Service-oriented computing: a research roadmap

Different planning techniques have been applied to the problem of automated composition of web services. However, in realistic cases, this planning problem is far from trivial: the planner needs to deal with the nondeterministic behavior of web services, the partial observability of their internal status, and with complex goals expressing temporal conditions and preference requirements. We propose a planning technique for the automated composition of web services described in OWLS process models, which can deal effectively with nondeterminism, partial observability, and complex goals. The technique allows for the synthesis of plans that encode compositions of web services with the usual programming constructs, like conditionals and iterations. The generated plans can thus be translated into executable processes, e.g., BPEL4WS programs. We implement our solution in a planner and do some preliminary experimental evaluations that show the potentialities of our approach, and the gain in performance of automating the composition at the semantic level w.r.t. the automated composition at the level of executable processes.

Paolo Traverso

Papers

Service-Oriented Computing: State of the Art and Research Challenges

Automated Planning, Theory And Practice

Automated Planning: Theory & Practice

Service-oriented computing: a research roadmap

Automated composition of semantic web services into executable processes