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The principles and concepts behind Smartphones. Embedded and pervasive computing platform Does not run general-purpose programs have conventional interface Persistent and ubiquitous device – must be pervasive Mobile Computing platform Operates on the go Adapts to available resources

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today s talk the triple nature of a smartphone
Embedded and pervasive computing platform

Does not

run general-purpose programs

have conventional interface

Persistent and ubiquitous device – must be pervasive

Mobile Computing platform

Operates on the go

Adapts to available resources

Wireless sensor platform

It contains an array of sensors







Today’s talk:The triple nature of a smartphone
what is mobile computing
What is Mobile Computing
  • 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
  • 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
    • 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
    • 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
  • 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.
Impact of mobility on the CS model: a resource-poor mobile client = thin clients
  • 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
  • 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
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



(re) negotitation


Dynamic Adaptation

Mobility Characteristics
adaptivity to mobility what is affected
Adaptivity to mobility:What 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 awareness adaptability
Context awareness: adaptability
  • 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
  • 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)
  • 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 computing17
Context-Aware computing
  • 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

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)

Location-Based Services

LBS + Social Networking:BuddyFinder 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


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

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

  • Name a smartphone app and identify its adaptability and context awareness
    • Handling variable resources
      • Connection, battery
    • Handling variable context
      • Location, time
wireless networks
Wireless Networks




100 km



10 km

1 km

100 m



10 m



1 m

10 kbps

100 kbps




wireless networks24
Wireless Networks

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.)

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
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

Wireless Local Area Network
  • Connectivity may be weak, intermittent and expensive
portability characteristics
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

Portability Characteristics
wireless sensor networking applications and challenges

Wireless Sensor Networking: Applications and Challenges

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

what is a wireless sensor network
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.

What is a Wireless Sensor Network?

GPS Sensor Node

limitations of wireless sensors
Limitations of Wireless Sensors
  • 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
  • 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

Retinal Implant

Cortical Implant

typical sensor node features
Typical Sensor Node Features
  • 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
  • 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
Ayushman*: 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
Ayushman: 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


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
  • 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
  • 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


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

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


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
  • Follow-up question in on-line discussion
  • Next class (January 27th)
    • Topic: Pervasive Location-based services
    • Review material: Chapters 2 & 4 of the textbook
mobile computing applications vertical applications
Mobile Computing Applications:Vertical 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:Horizontal 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