Gabriella Castelli , Marco Mamei, Franco Zambonelli

1. The Changing Role of Pervasive Middleware: from Discovery and Orchestration to Recommendation and Planning Gabriella Castelli, Marco Mamei, Franco Zambonelli Universityof Modena and Reggio Emilia 03/12/2010 Cesena, UNIMORE-UNIBOmeeting

2. Emerging Pervasive Scenario • A new pervasive scenario is emerging as a result of two trend: • Conceptofgeneralized service, include physicalresoucerces • Involvingofhuman via participatorysensing Self-aware Pervasive Service Ecosystems

3. The changing role of middleware • Traditional Pervasive middleware focus on supporting: • Discovery service • Context-awareness • Service orchestration and composition • To tackle the challenges risen by this scenario the new pervasive middleware should focus on: • Recommending • Planning Self-aware Pervasive Service Ecosystems

4. Limitation and changing requirements • Discovery the mw should evolve into a sort of recommendation engine. • Situation awareness  the mw should recommend and make available to services compact views about the context • Orchestration  the mw should be able to dynamically plan the most proper service composition based on what he knows about the application goals and its current context. • Security and Privacy  the middleware should take care of privacy issues, e.g., acting a mediator. Self-aware Pervasive Service Ecosystems

5. Case study scenarios We analyzed two show that the identified requirements have been faced by some other proposals as application-specific issues (and not as general middleware features, as we think they should): • E-mobility - In particular, the the research and reservation of available parking spaces. • Participatory sensing campaign - include the exploitation of human specific sensing, actuating, and computing capabilities. Self-aware Pervasive Service Ecosystems

6. E-mobility • Discovery E.g., “I want a parking in downtown area” • Situation Awareness “What are the situations happening in the urban environment?” • Orchestration A number of activities to be triggered (e.g. traffic actuators) and the global situation to be considered (other drivers, traffic congestion, pollution, etc.) • Privacy E.g., privacy should be guaranteed in order to have users to share their privately owned parking when not used Self-aware Pervasive Service Ecosystems

7. Participatory sensing campaigns • Discovery Recruitment of that are likely to be fulfill the application requirements • Situation Awareness to understand the situations in which the users are involved and their ability/willingness to participate • Orchestration Campaigns requires the involvement of a large number of users • Privacy Users may be willing to participate only being guaranteed anonymity Self-aware Pervasive Service Ecosystems

8. ResearchChallenges • A common model for representing generalized services and data. • Algorithms for distributed recommendation. • Algorithms for planning and orchestration. • Algorithms for reasoning and learning from the context. • Privacy-aware strategies for resource management and planning. • Incentive programs for boosting participation. Self-aware Pervasive Service Ecosystems

9. The SAPERE middleware rationale and underlying model The SAPERE middleware should consider modeling and architecting a pervasive service environment where the different kinds of resources interact and are combined with each other. Self-aware Pervasive Service Ecosystems

10. The SAPERE middleware rationale and underlying model (2) • The middleware should be lightweight and distributed in the pervasive environment, and applications access it via a simple API. • Inside the middleware, but transparently to external applications and users, many algorithms to perform situation reasoning and inference, resource recommendation and effective planning should be instantiated. • The middleware should rely on flexible semantic descriptions combine services, resources and humans to fulfill application needs (LSA). Self-aware Pervasive Service Ecosystems

11. Main design challenges for WP4 • Underlying geographic abstraction, maybe based on geographic p2p. • Simple interaction API, based on tuple spaces organized in a p2p network. • Which tuple spaces tools? • Which operations? • Semantic generalized service description (LSA), to represent resources, services, data. • Whatisan LSA content? • Whatis the realization? (xml, ontologies, etc.) • Eco-laws, drive the reactionsamongresources, services, data. • Are the eco-laws in chargeofenabling other actions in the environment • Is the self-organization meant only at the LSAs level? and how accommodates with the planning idea • Support to algorithms flexibly embedded in the middleware Self-aware Pervasive Service Ecosystems

12. Main design challenges for WP4 • Underlying geographic abstraction, maybe based on geographic p2p. • Simple interaction API, based on tuple spaces organized in a p2p network. • Which tuple spaces tools? • Which operations? • Semantic generalized service description (LSA), to represent resources, services, data. • Whatisan LSA content? • Whatis the realization? (xml, ontologies, etc.) • Eco-laws, drive the reactionsamongresources, services, data. • Are the eco-laws in chargeofenabling other actions in the environment • Is the self-organization meant only at the LSAs level? and how accommodates with the planning idea • Support to algorithms flexibly embedded in the middleware.