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Tiles

A Tile-based Approach for Self-assembling Service Compositions L. Cavallaro, E. Di Nitto, C. Furia, M. Pradella. Tiles. Bio-inspired model good for self-assembly Wang proposed tile model A tile is modeled in terms of its “border”

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Tiles

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  1. A Tile-based Approach for Self-assembling Service Compositions L. Cavallaro, E. Di Nitto, C. Furia, M. Pradella

  2. Tiles • Bio-inspired model good for self-assembly • Wang proposed tile model • A tile is modeled in terms of its “border” • Border carries information about which tiles can be put together with a given tile • Example: think about a jigsaw puzzle • Pieces that can be matched are put together to assemble the system • Winfree modeled dna self-assembly with tiles

  3. Service-tiles • Each service is represented in terms of: • Offered operations • Required operations • We represent offered (and requested) operations syntactically, with symbols (i.e., strings) from a finite alphabet • Intuitively a tile can offer its operations only if its requests have been fulfilled

  4. Example: Commuter Buddy

  5. Service-tiles • Selection is performed as constraint programming • Each tile is modeled as a multiset • Context constraints are respected • For instance • CommuterBuddy= [+commtuer_info –RoutePlanning –MobilityInformation(location) –TicketBooking] • MobilityInformation center Milan= [+MobilityInformation[CM] –Weather forecasts(location)–VehicleInformation(location) ]

  6. Context modeling • Context is modeled as a constraint that modifies some of a tile’s requirements • For instance MobilityInformation in Commuter buddy has a “location” parameter • Example: " [CM]“, “[SM]”,… • Constraints can be set by the user or inferred by the environment

  7. Context modeling example

  8. Advantages of the approach • Design by specifying local properties • Move part of design decision to runtime • E.g. context • Dynamic recomputing of solution • No assumption about the interface or interaction • Distributed fault tolerance

  9. Questions time

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