Luca Panziera

A framework for self-descriptive RESTful services

REST principles define services as resources that can be manipulated by a set of well-known methods. The same approach is suitable to define service descriptions as resources. In this paper, we try to unify the two concepts (services and their descriptions) by proposing a set of best practices to build self-descriptive RESTful services accessible by both humans and machines. Moreover, to make those practices usable with little manual effort, we provide a software framework that extracts compliant descriptions from documents published on the Web, and makes them available to clients as resources.

Distributed matchmaking and ranking of Web APIs exploiting descriptions from Web sources

Semantic Web service (SWS) technology promotes the definition of Web service descriptions with semantic annotations to better support Web service selection. Unfortunately, SWS descriptions tend to be huge and complex and their evaluation is characterized by limited scalability. The result is that very few descriptions exist in reality. Web service providers prefer to publish functional and non-functional properties (NFPs) of their RESTful services, also called Web APIs, by means of structured data (e.g., XML, JSON) or textual descriptions. In this paper we define an effective and efficient distributed matchmaking for Web API ranking based on: (i) techniques for the extraction of property descriptions from heterogeneous, dynamic and distributed information on the Web and (ii) a distributed architecture to improve the performance of the Web API matchmaking processes.

On Identifying and Reducing Irrelevant Information in Service Composition and Execution

The increasing availability of massive information on the Web causes the need for information aggregation by filtering and ranking according to users goals. In the last years both industrial and academic researchers have investigated the way in which quality of services can be described, matched, composed and monitored for service selection and composition. However, very few of them have considered the problem of evaluating and certifying the quality of the provided service information to reduce irrelevant information for service consumers, which is crucial to improve the efficiency and correctness of service composition and execution. This paper discusses several problems due to the lack of appropriate way to manage quality and context in service composition and execution, and proposes a research roadmap for reducing irrelevant service information based on context and quality aspects. We present a novel solution for dealing with irrelevant information about Web services by developing information quality metrics and by discussing experimental evaluations.

servIoTicy and iServe: A Scalable Platform for Mining the IoT☆

Abstract In the last years, Internet of Things (IoT) and Big Data platforms are clearly converging in terms of technologies, problems and approaches. IoT ecosystems generate a vast amount of data that needs to be stored and processed, becoming a Big Data problem. In this paper we present a platform that is specifically designed for mining the information associated to the IoT, including both sensors data and meta-data. The platform is composed of two major components: servIoTicy for storing and processing data, and iServe for the publication and discovery of sensors meta-data. The former provides capabilities to ingest, transform on real time and query data generated by sensors; the latter provides capabilities to publish, discover and use sensors based on semantic information associated to them. Both components are clearly designed for scalability, as any IoT cloud deployment requires. Both servIoTicy and iServe are available as an open source projects.

PoliMaR-Web: multi-source semantic matchmaking of web APIs

PoliMaR-Web provides experts and ordinary Web users with a tool to discover suitable Web APIs among the ones published in repositories. Given a set of constraints, either soft or hard, semantic descriptions are extracted from repositories and heterogeneous sources available on the Web, and then matchmade to deliver a personalized ranked list of APIs. PoliMaR-Web performs at run time to ensure up-to-date answers.

Web Service Contracts: Specification and Matchmaking

Web services promise universal interoperability through integration of services developed by independent providers. The coming of the Cloud Computing paradigm extends the need to share resources (e.g., platform, infrastructure, data) that are accessible as Web services. This means that a key factor to build complex and valuable business processes among cooperating organizations relies on the efficiency of automate the discovering of appropriate Web services. The increasing availability of Web services that offer similar functionalities requires mechanisms to go beyond the pure functional discovery. This chapter proposes the evaluation of Web service contracts, which define non-functional properties (NFPs) and applicability conditions associated with Web services, as a solution to automate process composition and enactment. Today, there is a lack of tools and algorithms that fully support this solution due to several open issues. First, existing languages don’t provide the right constructs for the specification of Web service contracts. Second, the lack of standard languages determines heterogeneity in Web service contract specifications raising interoperability issues. Third, Web service contract evaluation is only partially supported by existing discovery engines and composition tools when combining different services from different providers. This chapter proposes some research efforts on addressing these open issues.

A Solution to the Logistics Management Scenario with the Glue2 Web Service Discovery Engine

In this chapter, we describe a solution to the Logistics Management Scenario based on the Web service discovery engine Glue2, which provides support for both functional and non functional discovery components. The solution addresses the two main aspects this scenario focuses on: (a) the radically different perspectives adopted by the final users to describe their goals and the service providers to describe the services; (b) the evaluation of soft constraints to rank a set of Web services that satisfy the hard constraints expressed in the goal. The solution is based on an extension of the WSMO conceptual model that (1) manages classes and instances of services and goals in a different way, and (2) supports a richer specification of the services non functional properties in Web Service and Goal descriptions. The point (a) is solved by adopting a rule-based mediator-centric approach. The point (b) is solved by modeling some properties of the services and the soft constraints in the goals as Non Functional Properties adopting the Policy-Centered Meta-model (PCM); there properties are used by a Glue2 ranking component to rank the set of discovered services.