2. Middies: Passive middleware abstractions for pervasive computing environments Daniel Cutting, Adam Hudson, Aaron Quigley University of Sydney Daniel Cutting, Adam Hudson, Aaron Quigley University of Sydney

3. Pervasive computing Middies Data distribution Pervasive computing Middies Data distribution

4. Pervasive computing  Small mobile devices + large fixed servers  Wireline and wireless communication  Application collaboration  chat, file store, video+audio  matchmaking, games  museum+gallery tours  Small mobile devices + large fixed servers  Wireline and wireless communication  Application collaboration  chat, file store, video+audio  matchmaking, games  museum+gallery tours

5. Art gallery scenario Edward Bob Cynthia Gillian Sunflowers, Van Gogh Bob was here. Bob was here.

6. Middleware  Publish- subscribe: good for events  Tuple spaces: good for data persistence  Abstract sockets: good for streaming data  Publish- subscribe: good for events  Tuple spaces: good for data persistence  Abstract sockets: good for streaming data

7. Pervasive computing Middies Data distribution Pervasive computing Middies Data distribution

8. Middies  Generalised middleware abstractions  Features of tuple spaces and pub-sub  Store persistent data, publish events and handle streaming data  Generalised middleware abstractions  Features of tuple spaces and pub-sub  Store persistent data, publish events and handle streaming data

9. Spaces  Logically centralised shared structures like a tuple space  Physically distributed over several devices  Logically centralised shared structures like a tuple space  Physically distributed over several devices

10. Blocks  Data chunks like tuples, events, objects  Stored by spaces permanently (like tuples) or forwarded to interested devices (like events)  Data chunks like tuples, events, objects  Stored by spaces permanently (like tuples) or forwarded to interested devices (like events)

11. Matchers  Compare two blocks  Application-defined  Can implement tuple matchers, publish-subscribe subscription languages, etc.  Compare two blocks  Application-defined  Can implement tuple matchers, publish-subscribe subscription languages, etc.

12. Reactors  Callbacks fired by spaces under certain conditions  Can implement events + abstract sockets  Useful for pub-sub and streaming data  Callbacks fired by spaces under certain conditions  Can implement events + abstract sockets  Useful for pub-sub and streaming data

13. Pervasive computing Middies Data distribution Pervasive computing Middies Data distribution

14.  How do we distribute blocks around the network?  Server?  Single device stores all blocks  Redundant?  Each device stores replicas of all blocks  Or…?  How do we distribute blocks around the network?  Server?  Single device stores all blocks  Redundant?  Each device stores replicas of all blocks  Or…?

15. Context-aided distribution Edward Bob Cynthia Gillian Unimportant (0.2) Long-lived (0.7) Large size (0.9) Group photo at Sunflowers Group photo at Sunflowers Group photo at Sunflowers Nearest situation vector is photo photo  digest

16. Pervasive computing Middies Data distribution Pervasive computing Middies Data distribution

17. Chat, file store, video+audio  Needs  events (chat message added)  data persistence (file store)  data streaming (video+audio)  Tedious and error-prone development  file store would need special protocols for requesting/transmitting files from devices + way of handling unexpected disconnections  Needs  events (chat message added)  data persistence (file store)  data streaming (video+audio)  Tedious and error-prone development  file store would need special protocols for requesting/transmitting files from devices + way of handling unexpected disconnections