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.

/pdf/the-model-checker-spin-1bgo4jtefp.pdf

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

Web services are rapidly emerging as the reference paradigm for the interaction and coordination of distributed business processes. In several research papers we have shown how advanced automated planning techniques can be exploited to automatically compose web services, and to synthesize monitoring components that control their execution. In this demo we show how these techniques have been implemented in the ASTRO toolset (http://www.astroproject.org), a set of tools that extend existing platforms for web service design and execution with automated composition and execution monitoring functionalities.

ASTRO : Supporting composition and execution of web services

The importance of the problems of contingent planning with actions that have non-deterministic effects and of planning with goal preferences has been widely recognized, and several works address these two problems separately. However, combining conditional planning with goal preferences adds some new difficulties to the problem. Indeed, even the notion of optimal plan is far from trivial, since plans in nondeterministic domains can result in several different behaviors satisfying conditions with different preferences. Planning for optimal conditional plans must therefore take into account the different behaviors, and conditionally search for the highest preference that can be achieved. In this paper, we address this problem. We formalize the notion of optimal conditional plan, and we describe a correct and complete planning algorithm that is guaranteed to find optimal solutions. We implement the algorithm using BDD-based techniques, and show the practical potentialities of our approach through a preliminary experimental evaluation.

/pdf/contingent-planning-with-goal-preferences-5b3u18ls61.pdf

Contingent planning with goal preferences

Several real world applications require planners that deal with  non-deterministic domains and with temporally extended goals. Recent  research is addressing this planning problem. However, the ability  of dealing in practice with large state spaces is still an open  problem. In this paper we describe a planning algorithm for extended goals  that makes use of BDD-based symbolic model checking  techniques. We implement the algorithm in the MBP planner,  evaluate its applicability experimentally, and compare it with  existing tools and algorithms. The results show that, in spite of the difficulty of the problem, MBP deals in practice with domains of large size and with  goals of a certain complexity.

/pdf/symbolic-techniques-for-planning-with-extended-goals-in-non-3c9kknzjhy.pdf

Symbolic Techniques for Planning with Extended Goals in Non-Deterministic Domains

Many real world applications require systems with both reasoning and sensing/acting capabilities. However, most often, these systems do not work properly, i.e. they fail to execute actions and rarely perceive the external world correctly. No action, even if apparently simple, is guaranteed to succeed and, therefore, no planning can be "sound" (with respect to the real world) without taking into account failure. In this paper, we present a theory of planning that provides (1) a language that allows us to express failure; (2) a declarative formal semantics for this language; (3) a logic for reasoning about (possibly failing) plans.

/pdf/planning-with-failure-4eewppkpna.pdf

Planning with failure

In this paper we compare two different approaches to specify data-flow requirements in Web service composition problems, i.e., requirements on data that are exchanged among component services. Implicit data-flow requirements are a set of rules that specify how the functions computed by the component services are to be combined by the composite service. They implicitly define the required constraints among exchanged data. Explicit data-flow requirements are a set of explicit specifications on how the composition should manipulate messages and route them from/to components. In the paper, we compare these two approaches through an experimental evaluation, both from the point of view of efficiency and scalability and from that of practical usability.

/pdf/implicit-vs-explicit-data-flow-requirements-in-web-service-25b8bhqywc.pdf

Paolo Traverso

Papers

ASTRO : Supporting composition and execution of web services

Contingent planning with goal preferences

Symbolic Techniques for Planning with Extended Goals in Non-Deterministic Domains

Planning with failure

Implicit vs. explicit data-flow requirements in web service composition goals