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Lecture 14 Pervasive Computing Applications

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1 Lecture 14 Pervasive Computing Applications
Wireless Networks and Mobile Systems Lecture 14 Pervasive Computing Applications

2 Lecture Objectives Understand characteristics and technical challenges of pervasive computing applications Understand system middleware and support for context-aware ubiquitous computing Exemplify pervasive computing applications Pervasive Computing Applications 2

3 Sources T. Kindberg and A. Fox, “System software for ubiquitous computing,” IEEE Pervasive Computing, Vol. 1, No. 1, 2002, pp A. Smailagic and D. Kogan, “Location sensing and privacy in a context-aware computing environment,” IEEE Wireless Communications, Vol. 9, No. 5, Oct. 2002, pp S.S. Yau, et al., “Reconfigurable context-sensitive middleware for pervasive computing,’’ IEEE Pervasive Computing, Vol. 1, No. 3, 2002, pp M. Roman, et al., “A middleware infrastructure for active spaces”, IEEE Pervasive Computing, Vol. 1, No. 4, 2003, pp B. Johanson, et al., “The interactive workspaces project: experiences with ubiquitous computing rooms,” IEEE Pervasive Computing, Vol. 1, No. 2, 2002, pp Pervasive Computing Applications 3

4 Agenda Characteristics of pervasive computing
System support to enable pervasive computing Middleware for context-aware pervasive computing applications Examples of pervasive computing applications Smart homes/rooms UI’s Gaia-enabled Active Spaces Stanford’s Interactive Workspaces project Experimentation SLP-based pervasive Pocket TV application Pervasive Computing Applications 4

5 Pervasive Computing Characteristics (1)
Pervasive computing is: An environment in which people interact with embedded (and mostly invisible) computers and in which networked devices are aware of their surroundings and peers and are able to provide services or use services from peers effectively The creation of environments saturated with computing and wireless communication, yet gracefully integrated with human users Pervasive Computing Applications 5

6 Pervasive Computing Characteristics (2)
A pervasive (ubiquitous) system is characterized by: Physical integration: integration between computing nodes and the physical world, e.g., a whiteboard that records what’s on Instantaneous Interoperation: devices interoperate spontaneously in changing environments, e.g., a device changes its partners as it moves or as the context changes Pervasive Computing Applications 6

7 Non-Examples of Pervasive Applications
Accessing over a phone line from a laptop Neither physical integration nor spontaneous interoperations The laptop maintains the same association with a fixed mail server A collection of wirelessly connected laptops based on IEEE at a conference Discovery of the local network can be considered as physical integration of laptops with a access point The physical integration in pervasive computing, however, should involve a part of the environment that has a non-electronic function (e.g., a white board, a cup, etc.) No spontaneous interoperation is possible without considerable human manual intervention Pervasive Computing Applications 7

8 Borderline Examples of Pervasive Applications (1)
A smart coffee cup and saucer Physical integration: The cup is a regular cup (a non-electronic function) that contains sensing, processing and networking elements that let it communicate with the saucer of its state (full or empty, held or putdown, hot or cold) Instantaneous interoperation: Not satisfied if a specialized protocol is used between the cup and saucer as the owner would not be able to use the coffee cup without the saucer Pervasive Computing Applications 8

9 Borderline Examples of Pervasive Applications (2)
P2P games Physical integration: client devices can have sensors that allow physical integration Instantaneous interoperation: not satisfied if preconfigured components are used in the game A more convincing example would involve players with generic game playing pieces that let them spontaneously join local games not encountered before Pervasive Computing Applications 9

10 Borderline Examples of Pervasive Applications (3)
A Web-based object discovery system Devices (e.g., laptops) have small, embedded web servers that allow objects to be accessed by physical hyperlinks The user is presented with a web page when it senses an identifier of the object Physical integration smart devices can use web functionality to allow advertised objects to be integrated into the physical world as web pages without the need to reconfigure browsers Instantaneous interoperation not exactly satisfied since the system requires human intervention to keep it going. The human in the loop changes the browser’s associations to advertised web services Pervasive Computing Applications 10

11 Examples of Pervasive Applications (1)
A magic mirror that shows personal data and actions of those users who face it in a meeting Physical integration: the mirror can sense the presence of users in a meeting and can record their actions, in addition to its normal physical function Instantaneous interoperation: the mirror would interact with the room’s other components the moment you switch it on and would make spontaneous association with all relevant local sources of information about users …. Pervasive Computing Applications 11

12 Examples of Pervasive Applications (2)
A visitor brings his/her laptop into a meeting room and without manually configuring it in any way uses it to send his presentation to the room’s projector Physical integration: the projector can be activated from any laptop in the room Instantaneous interoperation: A laptop can spontaneously interact with the projector and control the presentation with a proper UI Can be made context-sensitive, e.g., allowing only a particular visitor to do so Pervasive Computing Applications 12

13 Other examples: Miró display
Cornell experiment: reflections on collective experience Pervasive Computing Applications 13

14 Other examples: Gust of Presence
Delft Univ. of Technology: Gust of Presence project Pervasive Computing Applications 14

15 The Semantic Rubicon Little evidence exists to suggest that software
alone can meet ubiquitous computing challenges, although it is desirable to have minimum or no intervention Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 1, 2002. The semantic Rubicon is the division between system and human for high-level decision-making or physical world semantics processing The division should be exposed in system design and the criteria and mechanisms for crossing it should be clearly indicated Pervasive Computing Applications 15

16 System Support Discovery
Requiring a common “syntax and vocabulary” model for specifying services Service Type Mismatched ServiceType=“photoPrint” ServiceType=“printing” Missed opportunity ServiceType=“digitalFrame” Pervasive Computing Applications 16

17 A tuple space or an event service ServiceType=“digitalFrame”
System Support (2) Interaction Requiring a “common” interoperation model for components to interact Event systems – publish, subscribe, and handle events Tuple space – add, read, and remove tuples in a tuple space (Standardized) Data Oriented Interaction Service ServiceType=“Print” DataType=“JPEG” ServiceType=“print” DataType=“JPEG” A common service: A tuple space or an event service ServiceType=“digitalFrame” DataType = “JPEG” Pervasive Computing Applications 17

18 System Support (3) Adaptation
Without human intervention for achieving “calm computing” as well as spontaneous interaction Being able to display or manipulate data or UI from other devices in a heterogeneous environment Possible solutions include: Dynamic downloading of mobile code to handle UI and communication (as in Jini) – requiring JVM Dynamic UI generation/transformation (as in Stanford’s Interactive Workspaces) – requiring a common UI description language to describe UI elements, e.g., “This control is a Boolean toggle” Another example is to use XML for specifying UI for web services Pervasive Computing Applications 18

19 Human Interface Adaptation
Use the same high-level UI description language to generate device-specific UIs to control lights and displays in a smart room for (a) a desktop HTML browser, (b) a Java-equipped device, and (c) a Palm device Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 1, 2002. Pervasive Computing Applications 19

20 System Support (4) Physical Integration Examples: Context aware
Context-awareness support is required to allow an application to access different types of contexts (e.g., locations, identities, QoS conditions) while hiding how the information was sensed or collected Examples: “Show me the agenda!” - can be made context-sensitive “Show me related Web pages for museum exhibits!” – can be based on the location and ids of exhibits sensed through barcode or Infrared beacon I know who I am photographing I know you provide photo printing services tag tag Pervasive Computing Applications 20

21 Positioning for Location-aware Computing
Outdoor – GPS (Global Position Sensing) normally to within 1-5 m accuracy with differential correction Indoor Active Bat (shown below) developed by AT&T Lab Cambridge based on ultrasonic sensors (to within 3 cm accuracy) CMU-TMI (shown next) developed by CMU based on for location tracking (to within 1-5 m accuracy) Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 1, 2002. Pervasive Computing Applications 21

22 System Support – Location Tracking in Smart Spaces
CMU has developed and deployed a Triangulation, Mapping and Interpolation (CMU-TMI) algorithm based on for location tracking: Physical locations of access points are known in advance A mobile device scans all access points (at least 3) within range to determine their signal and noise strengths The signal strengths are used to infer the distance between the device and the access points using an approximate relation obtained a priori Triangulation technique is applied to calculate the physical location Pervasive Computing Applications 22

23 System Support (5) Programming Framework
A programming framework for pervasive computing can be placed at the application or middleware level: Application level Providing only application-level coordination mechanisms, e.g., through a “tuple-space” API Middleware level Providing more tightly integrated facilities for achieving context awareness, QoS resource management, and adaptive control. Determining the user’s task and intention, and facilitating associations between components to assist the user in these activities Pervasive Computing Applications 23

24 System Support (6) Robustness
Failure is a common case in mobile and pervasive computing Recovering from failures  always prepared to reacquire lost resources Expiration-based schemes and soft states Periodic service advertisement and lease in the “common” data-oriented interaction service Separating failure-free (logic) from failure-prone (e.g., accessing a service or file while moving) application code More effective failure handling can be done implicitly by the middleware, e.g., retrying an idempotent operation (binding to a remote file) for a number of times Security – trust between devices, access control Pervasive Computing Applications 24

25 Middleware for Pervasive Computing
Context-Aware middleware for pervasive computing must address two “broad” characteristics: Tradeoff between awareness and transparency For pervasive applications, environment awareness is key to their effectiveness Cooperation between development support and run time services Let developers focus on application logic Pervasive Computing Applications 25

26 RCSM: A Reconfigurable Context Sensitive Middleware
ASU’s RCSM addresses the following “specific” characteristics: Uniform development support providing a uniform way to express context awareness without restricting to a specific language, OS, or environment Application-specific context acquisition, analysis and detection allowing developers to express the need for context data in a platform-independent way without knowing “how” data are obtained Context-triggered actions transparently invoking actions whenever the specified contexts are valid Transparent support for ad hoc communication abstracting the details of ad hoc communication from applications including proactively discovering new devices, establishing new communication links and notifying the application when a device is found Pervasive Computing Applications 26

27 RCSM: A Reconfigurable Context Sensitive Middleware (2)
ASU’s RCSM provides a context-aware interface description language (CA-IDL) API for an application to Define contexts used by the application Specify actions taken based on context values Compilers are provided to build adaptive object containers (ADCs) based on CA-IDL Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 3, 2002. Pervasive Computing Applications 27

28 Pervasive Computing Example 1: UI’s Gaia-enabled Active Spaces (1)
Gaia is a distributed middleware infrastructure that coordinates software entities and heterogeneous network devices contained in a physical space The physical space is extended into an “active space” by adding coordination via a context-based software infrastructure Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 4, 2002. Pervasive Computing Applications 28

29 Pervasive Computing Example 1: UI’s Gaia-enabled Active Spaces (2)
Event manager service: for event channel registration/notification Context service: for querying/registering context information such as people’s locations Presence service: for maintaining soft states of resources including digital entities (applications and services using heartbeats) and physical entities (devices and people using sensors) Space repository: for displaying/retrieving information about all entities in the active space Context file system: associating data with context and format info to allow context-sensitive data retrieval presented with the right UI format, e.g., make personal data available to applications conditioned on presence Example: Presentation Manager Application Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 4, 2002. Pervasive Computing Applications 29

30 Pervasive Computing Example 1: UI’s Gaia-enabled Active Spaces (3)
EX: Presentation Manager Application Speaker X with an RF active badge and a handheld walks into a Gaia-enabled room Presence service detects the badge and sends a “X is here” event with the user profile info of X contained Space repository receives the event and displays the user info. Context file system obtains the speaker’s mount point and mounts the speaker’s presentation file ready for access The handheld (controller) detects the directory server and then sends a heartbeat event to the heartbeat channel Presence service detects and sends a “new device” found event Space repository receives the event and displays the handheld info Both speaker X and handheld are now entities of the active space A prototype of Gaia-enabled active space Context: Speaker X enters the room Action: start the presentation manager application Read the presentation file Allowing X to control presentation by control events generated from the touch screen or handheld Pervasive Computing Applications 30

31 Pervasive Computing Example 2: Stanford’s Interactive Workspaces (1)
Stanford’s Interactive Workspaces is based on a tuple space data model Event Heap: Allowing name-type-value events (with expiration times) to be posted and retrieved Data Heap: Allowing data with attributes (e.g., format) posted iCrafter: Providing service advertisement/invocation and a UI generator that returns the best interface for the device Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 2, 2002. Pervasive Computing Applications 31

32 Pervasive Computing Example 2: Stanford’s Interactive Workspaces (2)
Room-based cross-platform interfaces The room-control system stores the geometric arrangement of screens and lights in the room in a configuration file and will automatically provide controllers on any device supporting a UI format available through iCrafter Java Swing Palm html Image extracted from IEEE Pervasive Computing Magazine, Vol. 1, No. 2, 2002. Pervasive Computing Applications 32

33 Experimentation: SLP-based Pervasive Pocket TV
SLP (RFC 2608) is an IETF standard that provides a scalable framework for automatic resource discovery on IP networks. Three entities are defined in a SLP system: User agent (UA) Server agent (SA) Directory agent (DA) A UA initiates service discovery on behalf of one or more applications. It can send queries to all SAs via multicast if a DA does not exist or to a DA to discover services via unicast. A SA works on behalf of one or more services. It responds directly to UA queries via unicast. If a DA exists, a SA can register its services with the DA to expose its services. Pervasive Computing Applications 33

34 Experimentation: Pervasive Pocket TV (2)
A DA serves as a centralized information repository. It accepts SA registrations and answers UA directory service queries. The DA support is optional and is introduced for performance and scalability considerations. Application Service query UA SA reply directory service query service registration DA directory service reply acknowledgment Pervasive Computing Applications 34

35 Experimentation: Pervasive Pocket TV (3)
DA Discovery: Passive versus Active Multicast SrvRqst (service:directory-agent) UA/SA DA Unicast DAAdvert Multicast DAAdvert UA/SA DA Pervasive Computing Applications 35

36 Experimentation: Pervasive Pocket TV (4)
Three configurations Small: No DA Multicast SrvRqst Multicast SrvRqst SA UA SA Unicast SrvRply Unicast SrvRply Medium: 1 DA Unicast SrvReg SA Unicast SrvAck Unicast SrvRqst UA DA Unicast SrvRply Unicast SrvAck SA Unicast SrvReg Large: Multiple DA’s SA UA DA SA SA DA UA SA Pervasive Computing Applications 36

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