Middleware & Applications for Mobile Collaboration Prof. Markus Endler Laboratory for Advanced Collaboration (LAC) PUC-Rio

2 State of the Art Traditional groupware tools are not suited for wireless networks. There exist some (few) collaboration tools for wireless networks but they: –don’t handle well intermittent connectivity and migration between networks –are dedicated tools, restricted to a single or few forms of interaction (usually messaging) –don’t consider the fact that the mobile user’s interaction needs depend on her current context.

3 Our Vision Stationary collaboration  Mobile collaboration The fact that users are mobile (change their location) opens a range of new and yet unexplored forms of collaboration.

4 Two Simple Examples Geo-messaging: Synchronous: discover and establish connection with users at a certain place (e.g. conference room) Asynchronous: attach a note to a place (e.g. at a bus stop, in vicinity of a machine) Task Force Coordination: Knowing location and viewpoint of each group member of task force, a manager can remotely coordinate the actions (e.g. military, rescue action, firemen)

5 Context-awareness Context-awareness is a key feature of current and future collaboration tools for mobile users. Context information is needed for: transparent adaptation, for reacting to changes in the devices’ execution environment (e.g. disconnections, drop in QoS, low energy, etc.) Enabling an extended notion of collaboration- awareness (e.g. user is driving) Allowing for new forms of interaction (e.g. co- location, geo-messaging)

6 Concrete Research Goals Build a middleware infra-structure, with services for collecting, enabling application-level access and inference of context Using this middleware, develop new collaboration tools & applications that are context-aware and adaptive

7 MoCA MObile Collaboration Architecture M Client Appl. Server MOCA Services Appl. Proxy subscribenotify Context info

8 Main Components of MoCA Core Services: Monitor Configuration Service Context Information Service Discovery Service Indoor Location Inference Additional Services: User Profile Matching Proximity Service...

9 The Monitor A daemon executing on the mobile device; Periodically collects & sends to the Context Information Service (CIS) state information about the mobile devices, e.g.: –Strength of signal received from all Access Points (through scan); –CPU utilization, available memory and energy; –MAC Address, IP and currently used Access Point; –Quality of current connection; In addition to the periodic sending, the Monitor also reports to the CIS any change of the current IP address or Access Point of the device (i.e. a migration)

10 Example of a MOCA service ALI: Approximate Location Inference (Indoor Positioning) compares the RF signal strength obtained from several Access Points on a map, several reference points are marked (logical positions) for each point, the signal pattern is measured (several directions and conditions), and this data is recorded in a database Approximate position of the device is inferred through similarity analysis of the signal patterns (using a statistical method) Main advantage: requires only network

11 ALI: Example door door room room XY Proxy is notified of Access Point Reference Point 0.4 RF Signal Intensity

12 Proxy Framework MOCA provides a white-box OO Framework for developing & customizing the Proxy to specific needs of the application. Frozen-Spots –Handover Management; –Service Discovery; –Protocol Translation. Hot-Spots –Context Management & Inference –Adaptation; –User Profile Management & Matching; Stores user profiles and searches for other users with similar interests; –Caching & Session State Management: –Authentication; –Message Filtering;

13 Case Study First Case Study: A Wireless Chat (W-Chat) which disseminates the (wireless) connectivity status of the participants in a chat room;

14 Current Status Monitor for WinXP, Linux & WinCE (iPAQs) which is independent of chipset Client and Server APIs for synchronous, synchronous and event-based communication All core services (DS, CS, CIS) Prototype Indoor Positioning Service oProxy Framework oOther Applications

15 Research Labs Computer Science Department Almost all of the 26 faculty also do applied research in one of the following Labs of the Software Technology Institute (ITS): –LES (Software Engineering) – –TecGraf (Computer Graphics) – –LAC (Mobility, Collaboration) – –TecBD (Databases) – –Telemídia (Networks and Hypermidia) – –LEARN (Neural Networks and Machine Learning) – –SERG (HCI) – –ICAD (Intelligent CAD) – –TecMF (Formal Methods) – –LabPar (Parallel Computing) – –TecWeb (Web Engineering) –

16 Q/A Contact: