Lecture 14 Pervasive Computing Applications Wireless Networks and Mobile Systems.
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Transcript of Lecture 14 Pervasive Computing Applications Wireless Networks and Mobile Systems.
Lecture 14Pervasive Computing Applications
Wireless Networks and Mobile Systems
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 3
Sources
● T. Kindberg and A. Fox, “System software for ubiquitous computing,” IEEE Pervasive Computing, Vol. 1, No. 1, 2002, pp. 70-81.
● 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. 10-17.
● S.S. Yau, et al., “Reconfigurable context-sensitive middleware for pervasive computing,’’ IEEE Pervasive Computing, Vol. 1, No. 3, 2002, pp. 33-40.
● M. Roman, et al., “A middleware infrastructure for active spaces”, IEEE Pervasive Computing, Vol. 1, No. 4, 2003, pp. 74-83.
● B. Johanson, et al., “The interactive workspaces project: experiences with ubiquitous computing rooms,” IEEE Pervasive Computing, Vol. 1, No. 2, 2002, pp. 67-75.
Pervasive Computing Applications 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 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 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 7
Non-Examples of Pervasive Applications
● Accessing email 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 802.11 at a conference■ Discovery of the local network can be considered as physical
integration of laptops with a 802.11 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 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 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 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 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 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 13
Other examples: Miró display
Cornell experiment: reflections on collective experience
Pervasive Computing Applications 14
Other examples: Gust of Presence
Delft Univ. of Technology: Gust of Presence project
Pervasive Computing Applications 15
The Semantic Rubicon
The semantic Rubicon is the division between system and humanfor high-level decision-making or physical world semantics processing
The division should be exposed in system design and the criteria andmechanisms for crossing it should be clearly indicated
Little evidence existsto suggest that software
alone can meet ubiquitous computing challenges,
although it is desirable tohave minimum or no
interventionImage extracted fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 1, 2002.
Pervasive Computing Applications 16
System Support
● Discovery■ Requiring a common “syntax and vocabulary” model for
specifying services
ServiceType=“photoPrint”
ServiceType=“printing”
ServiceType=“digitalFrame”
Missedopportunity
ServiceType
Mismatched
Pervasive Computing Applications 17
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
ServiceType=“Print”DataType=“JPEG”
ServiceType=“print”DataType=“JPEG”
ServiceType=“digitalFrame”DataType = “JPEG”
(Standardized)Data Oriented
Interaction Service
A common service:A tuple space or an event service
Pervasive Computing Applications 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 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 fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 1, 2002.
Pervasive Computing Applications 20
System Support (4)
● Physical Integration■ 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
Context aware
tag tag
I know who I am
photographing
I know you provide
photo printingservices
Pervasive Computing Applications 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 802.11 for location tracking(to within 1-5 m accuracy)
Image extracted fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 1, 2002.
Pervasive Computing Applications 22
System Support – Location Tracking in Smart Spaces
● CMU has developed and deployed a Triangulation, Mapping and Interpolation (CMU-TMI) algorithm based on 802.11 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 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 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 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 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 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 fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 3, 2002.
Pervasive Computing Applications 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 fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 4, 2002.
Pervasive Computing Applications 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
Image extracted fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 4, 2002.
Example: Presentation Manager Application
Pervasive Computing Applications 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 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 fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 2, 2002.
Pervasive Computing Applications 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 SwingPalm
html
Image extracted fromIEEE Pervasive ComputingMagazine, Vol. 1, No. 2, 2002.
Pervasive Computing Applications 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 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
UA SA
DA
Service
query
reply
service registrationdirectory service query
directory service reply acknowledgment
Pervasive Computing Applications 35
Experimentation: Pervasive Pocket TV (3)
● DA Discovery: Passive versus Active
UA/SA DA
Multicast SrvRqst (service:directory-agent)
Unicast DAAdvert
UA/SA DAMulticast DAAdvert
Pervasive Computing Applications 36
Experimentation: Pervasive Pocket TV (4)
● Three configurations
SA UA SAMulticast SrvRqst Multicast SrvRqst
Unicast SrvRply Unicast SrvRply
UA DA
SA
SA
Unicast SrvRqst
Unicast SrvRply
Unicast SrvReg
Unicast SrvAck
Unicast SrvAck
Unicast SrvReg
Small: No DA
Medium: 1 DA
Large: Multiple DA’s
UA
UA
SA
SA SA
SA
DA
DA