Adaptive Applications for Wireless Information Technology

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Adaptive Applications for Wireless Information
Technology

• Sujit Dey
• ECE Department
• University of California, San Diego
• dey_at_ece.ucsd.edu
• http//esdat.ucsd.edu

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Ubiquitous Mobile Information Technology
Heterogeneous Network Configurations, Access
Technologies, Data Services, and Network
Appliances

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Applications Data Services for the
Communication Era

• Computing Era
• Primary Resource Computing
• Paradox Computing resources increased over
  years, but so did problem complexity
• Solution Efficient computing algorithms
  minimize computation ops
• Metrics Runtime, space complexity

• Communication Era
• Primary Resource Bandwidth
• Paradox As bandwidth capabilities increase, so
  will new data-intense wireless services and
  number of users
• Solution Adaptive Applications minimize data
  traffic
• Metrics Quality of data Quality of service

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Our Approach Adaptive Wireless Data
Wireless Gateway Server
The Internet
Base Station
Access Profile
Application Shaper
Browser
Network Conditions
Application Requirements
Configurable Handheld Client
Client Characteristics
Client Characteristics
Web Servers
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Energy-Constrained Wireless Application Design
Motivation
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Wireless Application Design Energy Optimization
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Wireless Applications Energy Modeling
Optimization

• Goal
• Develop energy modeling methodology for wireless
  application design exploration and optimize
  energy consumption
• Steps
• Develop an energy model for handheld clients
  (PalmVII) using measurement based methodology
• Develop a generic energy estimation methodology
  for wireless applications

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Energy Model
Time
R
T
Encryption
Decompression
T Enc
R / Comp
Connection Setup
Decryption
R Enc / Comp
Transmission
Reception
Idling
Time
L
C0
E(R,T,C,L,Enc,Comp)
CidleL
Ct(TEnc)
Cr(CREnc/Comp)
CencT CcompR
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Validation of Energy Model

• Comparison of measured energy consumption with
  energy estimation using the proposed model
• Based on average energy consumption over 10
  accesses

Energy Model Sufficiently Accurate to drive
application level energy optimization
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Energy Aware Application Optimizations
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Exploration Methodology for Energy-Efficient Web
Application Design
N1
N2
N3
N4
Web Page (b_tran, b_recv, priority)
Access Probability
N6
N5
Usage Profile
Energy Estimator
Probabilistic Web Flow Graph
Transaction Generator
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Future Efforts
Wireless Gateway Server
The Internet
Base Station
Access Profile
WLAN WCDMA
Application Shaper
Browser
Network Conditions
Application Requirements
Configurable Handheld Client
Client Characteristics
Web Servers
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Network Aware Application Adaptation

• Factors influencing network environment
• Different network technologies (WLAN,WCDMA,HDR)
• Time varying bandwidth inside a network
  technology
• Example Rate Adaptation in WCDMA/HDR
• User Mobility
• Network Load
• Effect of the above factors on applications
• Energy
• Latency
• Error Quality
• Objective Adapt applications according to the
  current network environment to minimize energy
  consumption, latency of communication, and error
  quality.

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Considering Network Effects on Energy

• Extend energy model to incorporate network
  effects
• simulation based
• Network Parameters
• Signal Strength
• determines transmission power level
• no of re-transmissions
• Network Load
• idle period
• Energy Model

Energy TT(SS) ( E(R,T,C,L,Enc,Comp) TR(SS)
) I(Network Load)
TT(SS) TR(SS) Table lookups based on signal
strength I (Network Load) Table lookup based on
network load
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Test-bed Environment
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Conclusion

• We developed an energy model and optimization
  techniques to adapt application to conserve
  energy
• We are currently working to develop network
  aware adaptation techniques
• We want to develop a test-bed environment to
  demonstrate and validate our ideas

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Network-Aware Application Adaptation

• Idea To deliver information to users
  transparent of network conditions
• Means
• Server Re-organization of content
• Techniques Filtering, Splitting, Clustering
• Step 1 Filter out information which may not be
  useful
• Step 2 Split Information into atoms of
  information
• Step 3 Combine the atoms of information based
  on history information
• Issues
• Temporary Storage of transformation
• Maintenance of connection state information
• Client Pre-fetching Presentation