Communication Networks II Seamless Context-Aware Communication - - PowerPoint PPT Presentation

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Communication Networks II Seamless Context-Aware Communication - - PowerPoint PPT Presentation

Sep 05, 2023 426 likes •688 views

www.kom.tu-darmstadt.de www.httc.de Communication Networks II Seamless Context-Aware Communication Services - Overall Issues Prof. Dr.-Ing. Ralf Steinmetz TU Darmstadt Technical University of Darmstadt Dept. of Electrical Engineering and

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  • Prof. Dr.-Ing. Ralf Steinmetz

TU Darmstadt – Technical University of Darmstadt

  • Dept. of Electrical Engineering and Information Technology, Dept. of Computer Science

KOM - Multimedia Communications Lab

  • Merckstr. 25, D-64283 Darmstadt, Germany,

Ralf.Steinmetz@KOM.tu-darmstadt.de Tel.+49 6151 166151, Fax. +49 6151 166152 httc - Hessian Telemedia Technology Competence-Center e.V

  • Merckstr. 25, D-64283 Darmstadt, Ralf.Steinmetz@httc.de

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Communication Networks II

Seamless Context-Aware Communication Services - Overall Issues

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Overview

1 Motivation 1.1 What is Context? 1.2 Context in Computing 1.3 Design Principles 2 Context Phases 2.1 Context Acquisition 2.2 Context Synthesis 2.3 Context Dissemination 2.4 Context Use 3 Communication Services 3.1 Context-aware Communication Services 4 Context-aware Communication System 4.1 Innovative Communication Services

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Scope

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1 Motivation

Philosophical Excurse Aristotle, Greek philosopher (384 – 322 b.c.)

  • formal logic system
  • the Me is making statements about objects of the world (Not-Me)
  • statements are true or false (dualistic construction)
  • “tertium non datur” axiom
  • ne view on the world
  • still valid?

Hegel, German philosopher (1770 – 1831)

  • multiple ontologies

Günther, German philosopher (1900 – 1984)

  • combines polycontextual ontologies and multileveled logic

calculus

  • each observer may live in different context
  • communication with other observers forms shared context

everything is viewed and valid in a certain context

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1.1 What is Context?

Dictionary Definitions

  • “set of facts or circumstances that surround a situation
  • r event”
  • “the interrelated conditions in which something exists
  • r occurs”
  • “sourround text of a unit which gives means to it”

context (definition) is domain specific Context in Ubiquitious Computing [adapted from Dey]

  • “Context is any information that can be used to

characterize the situation of a subject and its interaction with optional objects. Objects are persons, places, or applications that are considered relevant to the subject.”

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1.2 Context in Computing

Areas

  • Human-Computer-Interaction (HCI)
  • User Interfaces (UIs)

part of ubiquitous computing Applications

  • context menus in software
  • tourist guides
  • health care
  • intelligent house automation
  • seamless communication
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1.3 Design Principles

Context-aware systems

  • invisibility
  • technology disappears from user’s perception
  • use as ordinary “things”
  • manual override
  • user keeps control
  • intervention has priority
  • feedback
  • decisions must be clear
  • system states must be trackable

Development

  • separation of
  • context acquisition
  • program logic
  • re-use of context sources
  • discovery of context-sources
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2 Context Phases

Spiral Context Model

  • acquisition
  • sensors
  • data fusion
  • synthesis
  • feature extraction
  • information fusion
  • dissemination
  • subscribe/notify
  • storage
  • use
  • adaptation
  • controlling

time context acquisition context use context dissemination context synthesis

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2.1 Context Acquisition

How to get a context?

  • usually no direct measuring of a context
  • indirect acquisition measuring the characteristic

features

  • often only a partly description of a context by context features

possible

Sensors

  • physical sensors
  • light, capacity, velocity, …
  • logical sensors
  • user id, symbolic location, time

Input

  • implicit input
  • automatically sensing
  • explicit input
  • user enters information
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Sensors

Definition

  • A Sensor is a device that perceives a physical
  • property. It transmits the result as a measurement.

A sensor maps the value of some environmental attribute to a quantitative measurement. Disadvantages

  • Sensor Deprivation
  • Limited spatial coverage
  • Limited temporal coverage
  • Imprecision
  • Uncertainty

measurand

Measurement Unit Control Unit Measuring Section

  • utput

disturbance input control variable

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Sensor Fusion

Definition

  • Sensor Fusion is the combining of sensory data or data derived

from sensory data such that the resulting information is in some sense better than would be possible when these source were used individually. Advantages:

  • Robustness and reliability
  • Extended spatial and temporal coverage
  • Increased confidence
  • Reduced ambiguity and uncertainty
  • Robustness against interference
  • Improved resolution

Fusion Configuration

  • competitive
  • complementary
  • cooperative
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Location Sensors

Location is often used as “primary” context source

  • location used as only context in first context-aware

applications

  • Categories of location sensing
  • indoor / outdoor usage
  • symbolic / physical position
  • Measuring distances
  • trilateration / triangulation / beacons / Cell of origin / proximity

System Usage area Method Accuracy GPS Outdoor Trilateration Trilateration Badge Trilateration < 25m Mobile phone Outdoor/indoor < 125m Badges Indoor room Radar/WLAN Indoor < 10 m

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Trilateration / Triangulation Trilateration

  • Distance meassurement to

at least 3 reference points

  • Meassurement methods
  • Time-of-Flight
  • Distance = Signalspeed * duration
  • Signal decay
  • Signal intensity decreases with distance

Triangulation

  • Angle instead of distance
  • 2 values needed for

location determination

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2.2 Context Synthesis

Degree of Abstraction

  • sensor value
  • electric value e.g in V, A
  • sensor data
  • normalized value e.g. in lux, candela
  • (context) information
  • meaningful information e.g. dark, light
  • context
  • complex information
  • combined from context information

Generation techniques

  • fusion process
  • rules, algorithms
  • soft computing concepts
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Inference methods

  • Definition
  • Inference is the act of passing from one proposition, statement,
  • r judgment considered as true to another whose truth is

believed to follow from that of the former. Multiple inference methods are used:

  • Statistical operations
  • min, max, avg, etc.
  • voting methods
  • Filtering
  • smoothing, prediction
  • Kalman Filter
  • Inference Methods
  • Hypothesis tests (classical inference)
  • Bayesian inference
  • Dempster-Shafer Theory of Evidence
  • Soft Computing Methods
  • Fuzzy Logic Rules Systems
  • Neural Nets
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Context Representation

Categories of context

  • entities whose context is assed
  • places, people, things, …
  • context information
  • identity, location, status, time

Modelling of context very complex task. Not solved. Representation of real world

  • methods
  • ontologies
  • rule based systems
  • modelling
  • notation and model analogue to human perception
  • very complex.
  • notation and model for specific domain
  • simple model
  • only needed context is represented
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2.3 Context Dissemination

Context acquisition entity ≠ entity using context context dissemination network

  • broadcast
  • messages:
  • routing:
  • m = #messages, n= #nodes
  • simple routing
  • subscription
  • messages:
  • routing:
  • j = #(joins+leaves), s = #subscriptions
  • stateful operations

Conclusion

  • choice depends on
  • dynamic of nodes
  • computational power and storage capacity of nodes

M m = v m n m r ⋅ = ⋅ =

M s j m + ⋅ = M s j r + ⋅ =

s j n m ⋅ < − ⋅ ) 1 (

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2.4 Context Use

Usage of context

  • reduction
  • limit input possibilities
  • display only relevant information to user
  • examples
  • software context menus
  • input in navigation systems
  • filtering incoming calls
  • adaptation
  • change program execution to suit current context
  • examples
  • novice/expert mode
  • triggering
  • branch depending on context
  • start new actions
  • examples
  • Call Processing Language execution
  • start wipers in car
  • share context with others
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3 Communication Services

Evolution of communication services

  • POTS
  • Basic Call
  • ringing
  • off/on hook
  • ISDN/IN
  • Supplementary Services
  • caller id
  • service on/off
  • Mobile Telephony
  • Multimedia Services
  • caller groups/ring tones
  • profiles

manual and explicit actions/switching only few control functionalities

Service Execution

media signaling media signaling

Service Execution

media signaling media signaling Service Description

Service Execution

media signaling media signaling Service Description Service Enforcement

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Daily Communication

Observation of Daily Communication

  • irrelevant communications
  • tele-marketing, surveys, out-of-office announcements
  • annoying disruptions
  • meetings, dinner, movie, theater, tennis match, etc.
  • caller unaware – not knowing the availability of the callee
  • lack of coordination leads to phone tag, missed opportunities, etc.
  • interaction overload - decreasing latency increases “junk”
  • bombarded by irrelevant communications versus noticing timely

communications (like flight changes)

  • device overload — e-mail, fax, phone, cell phone, IMS, chats
  • overwhelmed by managing and choosing the right channel
  • different media = different device = different address

communication becomes easier with every additional device?

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3.1 Context-aware Communication Services

New era of communication services

  • context used for parameterization of service
  • user-centric services

Communication service properties

  • implicit input
  • invisible helper
  • must disappear from users perception

Service Execution

media signaling media signaling Service Description Service Enforcement

Context as Parameter

Context Acquisition Context Synthesis

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4 Context-aware Communication System

Putting it all together

  • Context Server
  • storing contexts
  • central integration entity
  • SIP Feature Server
  • Call Processing Language
  • Rule editor
  • allows user to

create services

  • eXtended User Agents
  • able to display &

user context

Network of Sensors

CPL

Feature Server

Proxy User Agent User Agent SIP Signaling SIP Signaling User Agent

Rules

Context Server

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Aggregation Architecture

VS VS VS

Agg Agg propriety WSDL WSDL XML/PIDF XML/PIDF XML/PIDF XML/PIDF WSDL propriety propriety XML/PIDF WSDL WSDL

S1 S2 S3 S4 S5 S6

Agg: Aggregation S: Sensor VS: Virtual Sensor PIDF: Presence Information Data Format

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4.1 Innovative Communication Services

2 selected scenarios

  • filtering: callee avoids disturbing calls

Meeting Room Callee

Caller Colleague Boss

  • context sharing: caller can avoid unnecessary

calls

Meeting Room Callee

Caller call setup context=Meeting remark=do not disturb

the use of context information allows a more efficient communication for both –

caller and callee