Cse494 598 mobile computing systems and applications fa2011
1 / 54

CSE494/598 Mobile Computing Systems and Applications (Fa2011) - PowerPoint PPT Presentation

  • Uploaded on

CSE494/598 Mobile Computing Systems and Applications (Fa2011). Class 2. Announcements. Assignment 1 due on September 7 th Group formation (groups of 3) Check the website for files related to assignment. Agenda. Survey Review Mobile and Adaptive Computing Context Aware Computing

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' CSE494/598 Mobile Computing Systems and Applications (Fa2011)' - dee

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Announcements (Fa2011)

Assignment 1 due on September 7 th

Group formation (groups of 3)

Check the website for files related to assignment

Agenda (Fa2011)

Survey Review

Mobile and Adaptive Computing

Context Aware Computing

Wireless Communication and Networks

Wireless Sensor Networks

Survey review

Survey Review (Fa2011)

Let’s see what you said…

I am expecting to learn in this course
I am expecting to learn in this course (Fa2011)

Mobile services

Future of mobile computing

Developing mobile applications

Fundamentals of mobile computing

Ubiquitous computing

Context aware computing

Networking issues

Resource efficient implementation – power and memory

Android programming

Embedded software and hardware knowledge

Mobile device protocols

Small screen UI development

Data acquisition and processing in mobile devices

Human computer interaction

My concerns about this course are
My concerns about this course are (Fa2011)

What’s more than what I already know

Language limitations

Too much workload (x2)

Too much or too advanced programming required and too little learning (x2)

Not adequate background (x2)

A lot of theory

Too easy for me

Therefore my wishes for this course are
Therefore… (Fa2011)my wishes for this course are

Teach me more than what I already know

Be easy to understand

Count toward my degree requirements

Have reasonable workload

Require not too much theory

Require little background knowledge

Be practical and application-oriented

I learn through the following methods
I learn through the following methods (Fa2011)

none=0, limited=1, somewhat=2, a lot=3, extremely=4

I am interested in those mobile computing domains
I am interested in those mobile computing domains (Fa2011)

none=0, limited=1, somewhat=2, a lot=3, extremely=4

Mobile and adaptive computing

Mobile (Fa2011)(and adaptive) Computing

What is mobile computing
What is Mobile Computing (Fa2011)

  • Mobile computing?

    • Distributed system

    • Wireless communications

    • Mobility of communications devices

  • Difference between mobile computing and mobile communications?

    • Ex. “Italian restaurant” through search engine.

    • Ex. Video streaming over the Internet

    • Limitations of mobile computing devices: energy, screen, …

    • Security or privacy

    • Middleware layer

Adaptability the key to mobile computing
Adaptability – The key to Mobile Computing (Fa2011)

  • The vision of mobile computing

    • Roam seamlessly with your computing devices while continuing to perform computing and communication tasks uninterrupted.

    • Global information services at any time from any location

    • Mobile users as integrated consumers and producers of data and information

    • Ubiquitous computing where mobile computers become an integral part of daily activities

  • Transparency

    • The ability of a system to hide some characteristics of its underlying implementation from users

    • Access transparency

    • Location transparency: name transparency, user mobility

    • Failure transparency

    • Mobile computing: mobility transparency

  • Constraints of mobile computing environments (Fa2011)

    • Mobile computers can be expected to be more resource-poor than their static counterparts: e.g., battery

    • Mobile computers are less secure and reliable.

    • Mobile connectivity can be highly variable in terms of its performance (bandwidth and latency) and reliability.

  • Fig 1.1

  • Application-aware adaptation (Fa2011)

    • Application-transparent (the system is fully responsible for adaptation)

    • Laissez-faire (the system provides no support at all)

    • E.g., bandwidth, battery

    • Fig 1.2

Mechanisms for adaptation
Mechanisms for Adaptation (Fa2011)

  • What can be adapted?

    • The functionality and the data

  • How to adapt?

    • Client-server (CS) model

  • Adapting functionality

    • CS model

    • A server with soft or hard state about the clients

    • Coda File servers (Saty 1996a)

      • A few trusted servers act as the permanent safe haven of the data.

      • A large number of un-trusted clients can efficiently and securely access the data.

      • Good performance is achieved by using techniques such as caching and prefetching.

      • Security of data is ensured by employing end-to-end authentication and encrypted transmissions.

  • Adapting data

    • Fidelity: the degree to which a copy of data presented for use at the client matches the reference copy at the server.

      • Video data – frame rate and image quality

      • Spatial data – minimum feature size

      • Telemetry data – sampling rate and timeliness

    • QoS requirements

      • Information quality

      • Performance

    • Agility: the speed and accuracy with which an adaptive application detects and responds to changes in its computing environments, e.g., change in resource availability.

  • Incorporating adaptations in applications
    Incorporating adaptations in applications client = thin clients

    • Detection of changes

      • software sensors, e.g. for connectivity, monitor the quality of link

    • Detection-driven behavior

      • State-based approach, i.e. chose an operating state according what is sensed.

    • Employment of compensating mechanisms

      • Profiling, Caching, Prefetching

    • Examples:

      • TCP & congestion control

        • Detection: Use of timers/timeouts. States: governed by window size

      • Coda (continued data availability) distributed file system

        • Hoarding (prefetching), Emulating (local reads and writes), Write-disconnected (mixed mode), Reintegration (incorporate backlog of changes to original remote files)

    Mobility characteristics

    Application client = thin clients


    (re) negotitation


    Dynamic Adaptation

    Mobility Characteristics

    • Location changes

      • location management - cost to locate is added to communication

    • Heterogeneity in services

      • bandwidth restrictions and variability

    • Dynamic replication of data

      • data and services follow users

    • Querying data - location-based responses

    • Security and authentication

    • System configuration is no longer static

    Adaptivity to mobility what is affected
    Adaptivity to mobility: client = thin clientsWhat is affected?

    Operating systems

    File systems

    Database systems

    Programming Languages

    Communication architecture and protocols

    Hardware and architecture

    Real-Time, multimedia, QoS


    Application requirements and design

    Context aware computing

    Context-Aware client = thin clientsComputing

    Context awareness adaptability
    Context awareness: client = thin clientsadaptability

    • Context awareness

      • Resource awareness

        • Adapt to available resources (connectivity, nearby devices

      • Situation awareness

        • Adapt to the situation (mode, location, time, event)

      • Intention awareness (?)

        • Adapt to what the user wants to do

    Defining context
    Defining Context client = thin clients

    • Dictionary definition: “the interrelated conditions in which something exists or occurs”

    • One definition [Schilit]:

      • Computing context: connectivity, communication cost, bandwidth, nearby resources (printers, displays, PCs)…

      • User context: user profile, location, nearby people, social situation, activity, mood …

      • Physical context: temperature, lighting, noise, traffic conditions …

    • also:

      • Time context (time of day, week, month, year…)

      • Context historycan also be useful

    Context cont d
    Context (cont’d) client = thin clients

    • Is all this information necessary?

    • “Context is the set of environmental states and settings that either determines an application’s behavior or in which an application event occurs and is interesting to the user”

      • Active context: influences the behavior of the application

        • Location in a call forwarding application

      • Passive context: context that is relevant but not critical

        • Active map application: display location name and other people in the room

    • Is all this information measurable?

      • Temperature? Location? People around? Social situation? Mood?

    Context aware computing1
    Context-Aware computing client = thin clients

    • How to take advantage of this context information?

    • Schilit’s classification of CA applications:

      • Proximate selection: user interface where nearby objects are emphasized/made easier to choose

      • Automatic contextual reconfiguration: a process of adding/removing components or changing relationships between components based on context change

      • Contextual information and commands: produce different results according to the context in which they are issued

      • Context-triggered actions: rules to specify how the system should adapt

    • Are these fundamental/inclusive?

    Location based services
    Location-Based Services client = thin clients


    • Geocoder (convert street addresses to latitude / longitude), Reverse geocoder

    • Address Helper (many addresses inaccurate or incomplete)

    • Map data

    • Points of Interest data e.g. pubs, restaurants, cinemas

    • Business Directory (doctors, plumbers etc by location)

    • Connection to Telco or satellite


    • Content providers – Telcos jealously guarding own domain

    • Proprietary software e.g. Windows Live

    • Price of map data varies widely, very expensive in some countries e.g. Australia

    • Integration into customer’s web sites (API’s)

    • Cognitive Routing – routing / directions using terminology relevant to user (e.g. resident c/f tourist)

    LBS + Social Networking: client = thin clientsBuddyFinder App

    Mobile social networking meets location based services

    Mobile friend tracking & directory services

    Proprietary internal messaging connectable to any messaging service

    Friends become closer than ever because you know where they are

    Location from GPS+map service

    Mobile computing applications
    Mobile Computing Applications client = thin clients


    Vertical: vehicle dispatching, tracking, point of sale, information service (yellow pages), Law enforcement

    Horizontal: mail enabled applications, filtered information provision, collaborative computing…

    Excercise client = thin clients

    • Name a smartphone app and identify its adaptability and context awareness

      • Handling variable resources

        • Connection, battery

      • Handling variable context

        • Location, time

    Wireless communications and networks

    Wireless Communications client = thin clientsand Networks

    Wireless networks
    Wireless Networks client = thin clients




    100 km



    10 km

    1 km

    100 m



    10 m



    1 m

    10 kbps

    100 kbps




    Wireless networks1
    Wireless Networks client = thin clients

    Cellular - GSM (Europe+), TDMA & CDMA (US)

    FM: 1.2-9.6 Kbps; Digital: 9.6-14.4 Kbps (ISDN-like services)

    Cellular Subscribers in the United States:

    90,000 in 1984 (<0.1%); 4.4 million in 1990 (2.1%);13 million in 1994; 120 million in 2000; 187.6 million by 2004 (Cahner In-State Group Report).

    Handheld computer market will grow to $1.77 billion by 2002

    Public Packet Radio - Proprietary

    19.2 Kbps (raw), 9.6 Kbps (effective)

    Private and Share Mobile Radio

    Paging Networks – typically one-way communication

    low receiving power consumption

    Satellites – wide-area coverage (GEOS, MEOS, LEOS)

    LEOS: 2.4 Kbps (uplink), 4.8Kbps (downlink)

    Wireless networks cont
    Wireless Networks (Cont.) client = thin clients

    Wireless Local Area Networks

    IEEE 802.11 Wireless LAN Standard based systems, e.g., Lucent WaveLan.

    Radio or Infrared frequencies: 1.2 Kbps-15 Mbps

    Wireless Metropolitan Area Networks

    IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX)

    Microwave frequencies (2.5-66GHz), broadband (<70MBps), metropolitan coverage (1 to 30 miles)

    Packet Data Networks



    Cellular Digital Packet Data (CDPD)

    Private Networks

    Public safety, UPS.

    Wireless local area network
    Wireless Local Area Network client = thin clients

    • Data services: IP packets

    • Coverage Area: Offices, buildings, campuses

    • Roaming: Within deployed systems

    • Internet access: via LAN.

    • Type of services: Data at near LAN speed.

    • Variant Connectivity

      • Low bandwidth and reliability

    • Frequent disconnections

      • predictable or sudden

    • Asymmetric Communication

      • Broadcast medium

    • Monetarily expensive

      • Charges per connection or per message/packet

    • Connectivity may be weak, intermittent and expensive

    Portability characteristics
    Portability Characteristics client = thin clients

    • Battery power restrictions

      • transmit/receive, disk spinning, display, CPUs, memory consume power

    • Battery lifetime will see very small increase

      • need energy efficient hardware (CPUs, memory) and system software

      • planned disconnections - doze mode

    • Power consumption vs. resource utilization

    • Resource constraints

      • Mobile computers are resource poor

      • Reduce program size – interpret script languages (Mobile Java?)

      • Computation and communication load cannot be distributed equally

    • Small screen sizes

    • Asymmetry between static and mobile computers

    Wireless sensor networking applications and challenges

    Wireless Sensor Networking: Applications and Challenges client = thin clients

    Based on Slides by Prof. Loren Schwiebert, CS, Wayne State University

    What is a wireless sensor network
    What is a Wireless Sensor Network? client = thin clients

    • Wireless Sensor Node = Sensor + Actuator + ADC + Microprocessor + Powering Unit + Communication Unit (RF Transceiver)

    • An ad hoc network of self-powered and self-configuring sensor nodes for collectively sensing environmental data and performing data aggregation and actuation functions reliably, efficiently, and accurately.

    GPS Sensor Node

    Limitations of wireless sensors
    Limitations of Wireless Sensors client = thin clients

    • Wireless sensor nodes have many limitations:

      • Modest processing power – 8 MHz

      • Very little storage – a few hundred kilobits

      • Short communication range – consumes a lot of power

      • Small form factor – several mm3

      • Minimal energy – constrains protocols

        • Batteries have a finite lifetime

        • Passive devices provide little energy

    Some sample applications
    Some Sample Applications client = thin clients

    • Industrial and Commercial Uses

      • Inventory Tracking – RFID

      • Automated Machinery Monitoring

    • Smart Home or Smart Office

      • Energy Conservation

      • Automated Lighting

    • Military Surveillance and Troop Support

      • Chemical or Biological Weapons Detection

      • Enemy Troop Tracking

    • Traffic Management and Monitoring

    Sensor based visual prostheses
    Sensor-Based Visual Prostheses client = thin clients

    Retinal Implant

    Cortical Implant

    Typical sensor node features
    Typical Sensor Node Features client = thin clients

    • A sensor node has:

      • Sensing Material

        • Physical – Magnetic, Light, Sound

        • Chemical – CO, Chemical Weapons

        • Biological – Bacteria, Viruses, Proteins

      • Integrated Circuitry (VLSI)

        • A-to-D converter from sensor to circuitry

      • Packaging for environmental safety

      • Power Supply

        • Passive – Solar, Vibration

        • Active – Battery power, RF Inductance

    Traffic management monitoring
    Traffic Management & Monitoring client = thin clients

    • Future cars could use wireless sensors to:

      • Handle Accidents

      • Handle Thefts

    • Sensors embedded in the roads to:

      • Monitor traffic flows

      • Provide real-time route updates

    Ayus hman a pervasive healthcare system
    Ayus client = thin clientshman*: A Pervasive Healthcare System

    * Sanskrit for long life


    Sensors (Temperature etc)

    • Project @ IMPACT Lab, Arizona State University

    • To provide a dependable, non-intrusive, secure, real-time automated health monitoring.

    • Should be scalable and flexible enough to be used in diverse scenarios from home based monitoring to disaster relief, with minimal customization.




    External Gateway

    Central Server

    Medical Sensors

    (EKG, BP) controlled

    By Mica2 motes



    Home/Ward Based


    Body Based


    Medical Facility Based



    • To provide a realistic environment (test-bed) for testing communication

    • protocols and systems for medical applications. 

    K. Venkatasubramanian, G. Deng, T. Mukherjee, J. Quintero, V Annamalai and S. K. S. Gupta,

    "Ayushman: A Wireless Sensor Network Based Health Monitoring Infrastructure and

    Testbed", In Proc. of IEEE DCOSS June 2005

    Ayus hman current setup
    Ayus client = thin clientshman: Current Setup








    Central Server

    Blood Pressure


    Data (accelerometer,

    Temperature, humidity,




    Body Area Network

    • Properties

    • Hardware and software based architecture

    • Multi-tiered organization

    • Real-time, continuous data collection

    • Query support (past, current data)

    • Remote monitoring capability through the Internet

    • Simple alarm generation

    Remote Clients

    Enabling technologies
    Enabling Technologies client = thin clients


    TOS v.1.x-2.0









    Commercially available sensor boards

    Open source OS with support for ad hoc networking

    Phone to wsn interface
    Phone to WSN Interface client = thin clients

    • Design Principles:

      • To minimize the changes to the existing WSN architecture (required to maintain backward compatibility with previous apps.)

      • To leverage COTS hardware and existing software solutions (to minimize the development time).

    • Issues to address:

      • Phone to sensors interface

      • Data handling on the cell phone

    Monitoring and Control Software

    Context generation
    Context Generation client = thin clients

    • Medical Context

    • Is an aggregate of 4 base contexts.

    • Each physiological event has to be characterized by all 4 base contexts for accurate understanding of patient’s

    • health.

    • A contextual template can be created for specific physiological events for future reference.


    (EKG, Perspiration,

    Heart Rate)




    (Home, Gym, Office,

    Hospital, Park)





    (Morning, Evening,


    Sensor Network

    • Challenges

    • How to determine the aggregate medical context from the four base contexts?

    • How to create a contextual template for a patient?


    (Humidity, Temp)

    Base Context

    Security in pervasive healthcare
    Security in Pervasive Healthcare client = thin clients


    Patient data is transmitted wirelessly by low capability sensors

    Patient data is therefore easy to eavesdrop on

    Security schemes utilized may not be strong enough for cryptanalysis

    Patient data is stored in electronic format and is available through the Internet

    Makes it easy to access from around the world and easy to copy

    Data can be moved across administrative boundaries easily bypassing legal issues.

    Electronic health records store more and more sensitive information such as psych reports and HIV status

    Preserving patient’s privacy is a legal requirement (HIPAA)

    Excruciating Factors

    Wireless connectivity is always on

    No clear understanding of:

    Trusted parties

    Security policies for medical environment

    Devices are heterogeneous with limitedcapabilities

    Traditional schemes too expensive for long term usage

    Security related issues
    Security Related Issues client = thin clients

    New Attacks

    Fake emergency warnings.

    Legitimate emergency warningsprevented from being reported in times.

    Unnecessary communication by malicious entity with sensors can cause:

    Battery power depletion

    Tissue heating


    • Efficientcryptographic primitives

      • Cheaper encryption, hash functions

    • Better sensorhardware design

      • Cheap, tamper-resistant sensor hardware

    • Better communication protocol design

    • Better techniques for controlling access to patient EHR


    • Health Information Privacy and Accountability Act (HIPAA)

      • Passed in 1995

      • Provides necessary privacy protection for health data

      • Developed in response to public concern over abuse of privacy in health information

      • Establishes categories of health information which may be used or disclosed


    • Integrity - Ensure that information is accurate, complete, and has not been altered in any way.

    • Confidentiality - Ensure that information is only disclosed to those who are authorized to see it.

    • Authentication – Ensure correctness of claimed identity.

    • Authorization – Ensure permissions granted for actions performed by entity.

    Energy efficiency
    Energy Efficiency client = thin clients


    Sensors have very small battery source.

    Sensors need to be active for long time durations.

    For implantable sensors, it is not possible to replace battery at short intervals.


    Battery power not increasing at same rate as processing power.

    Small size (hence less energy) of the batteries in sensors.


    Better Battery

    Solar Energy


    Body Thermal Power

    End of class
    End of class client = thin clients

    • Follow-up question in on-line discussion

    • Next class

      • Topic: Pervasive Location-based services

      • Review material: Chapters 2 & 4 of the textbook

    Extra slides

    Extra Slides client = thin clients

    Mobile computing applications vertical applications
    Mobile Computing Applications: client = thin clientsVertical Applications

    Serve a narrow, niche application domain

    – Services dispatch (taxi, fire, police, trucking)

    – Sales tracking (point of sale, market trends)

    – Mail and package tracking (courier, postal)

    Relatively easy to implement due to

    restrictions and assumptions

    – homogeneous MUs

    – limited numbers of users

    Mobile computing applications horizontal applications
    Mobile Computing Applications: client = thin clientsHorizontal Applications

    Broad, domain-independent applications serving a mass-market

    – Electronic Mail and News

    – Yellow Pages Directory Services

    – Multimedia Merchant Catalogs

    – Digital Libraries

    – Location-based Information Filtering

    Driving force of mobile computing research