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Adaptive Applications for Wireless Information Technology. Sujit Dey ECE Department University of California, San Diego [email protected] http://esdat.ucsd.edu. Ubiquitous Mobile Information Technology. - PowerPoint PPT Presentation
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Sujit Dey
Adaptive Applications for Wireless Information Technology
Adaptive Applications for Wireless Information Technology
Sujit DeySujit Dey
ECE Department
University of California, San Diego
http://esdat.ucsd.edu
Sujit Dey
Ubiquitous Mobile Information TechnologyUbiquitous Mobile Information Technology
In-home Network
MSC
BS
The Internet
OpticalNetworking
Ad-hoc SensorNetworks
On-bodynetworking
Heterogeneous Network Configurations, Access Technologies, Data Services, and Network Appliances
Sujit Dey
Applications & Data Services for the Communication Era
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
Sujit Dey
Our Approach: Adaptive Wireless DataOur Approach: Adaptive Wireless Data
The Internet
Base Station
Wireless GatewayServer
Web Servers
ConfigurableHandheld Client
BrowserApplication
ShaperApplication
Shaper Network ConditionsNetwork
Conditions
ApplicationRequirementsApplication
Requirements
Access Profile
Access Profile
Client Characteristics
Client Characteristics
Client Characteristics
Client Characteristics
Sujit Dey
Energy-Constrained Wireless Application Design : Motivation
Energy-Constrained Wireless Application Design : Motivation
Start
BreakingNews
Politics Sports Enter. Finance
BNHeadlines
PoliticsHeadlines
FootballHeadline
s
BasketballHeadlines
Science
Fin.Headlines
Enter.Headlines
ScienceHeadlines
BNSummary
PoliticsFull Story
PoliticsSummary
ScienceSummary
Weather
ScienceFull Story
FootballSummary
FootballFull Story
BasketballSummary
BasketballFull Story
Enter.Full Story
Enter.Summary
Fin.Summary
Fin.Full Story
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Sujit Dey
Wireless Application Design : Energy OptimizationWireless Application Design : Energy Optimization
Politics Sports Enter. Finance
PoliticsHeadlines
FootballHeadline
s
BasketballHeadlines
Science
Enter.Headlines
PoliticsFull Story
ScienceFull Story
FootballSummary
FootballFull Story
BasketballSummary
BasketballFull Story
Enter.Full Story
Enter.Summary
Fin.Full Story
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BreakingNewswithSummary
Start &Weather
Fin.Headlines&Summary
0.5
PoliticsHeadlines
PoliticsFull Story
Headlines
Sujit Dey
Wireless Applications : Energy Modeling & Optimization
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
Sujit Dey
Energy ModelEnergy Model
EncryptionEncryption
Connection Setup
Connection Setup
TransmissionTransmission
DecompressionDecompression
DecryptionDecryption
ReceptionReceptionIdlingIdling
TimeTime
TimeTime
T
T * Enc
L
R
R / Comp
R * Enc / Comp
E(R,T,C,L,Enc,Comp) = C0
+ Cidle*L
+ Cr*(C*R*Enc/Comp)+
+ Ct*(T*Enc)
+ Cenc*T + Ccomp*R
Sujit Dey
Validation of Energy ModelValidation 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
Application Measured Energy (J) Estimated Energy (J) % Error
News
Travel
Personal
2.983
2.219
0.735
2.800
2.200
0.730
6.0
5.0
0.5
Sujit Dey
Energy Aware Application OptimizationsEnergy Aware Application Optimizations
Start
BreakingNews
Politics Sports Enter. Finance
BNHeadlines
PoliticsHeadlines
CricketHeadline
s
BasketballHeadlines
Science
Fin.Headlines
Enter.Headlines
ScienceHeadlines
BNSummary
PoliticsFull Story
PoliticsSummary
ScienceSummary
Weather
ScienceFull Story
CricketSummary
CricketFull Story
BasketballSummary
BasketballFull Story
Enter.Full Story
Enter.Summary
Fin.Summary
Fin.Full Story
0.30.1 0.1 0.2 0.05
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END
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Fin.Headlines&Summary
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BreakingNewswithSummary
Aggregation
Headlines
Deletion
Start &Weather
Migration
PoliticsHeadlines
PoliticsFull Story
Splitting
Sujit Dey
Exploration Methodology for Energy-Efficient Web Application Design
Exploration Methodology for Energy-Efficient Web Application Design
Probabilistic Web Flow Graph
TransactionGenerator
ClientEnergy Model
EnergyEstimator
Usage Profile Web Design
N1
N2 N3 N4
N6N5Access Probability
Web Page(b_tran, b_recv, priority)
Sujit Dey
Future EffortsFuture Efforts
The Internet
Base Station
Wireless GatewayServer
Web Servers
ConfigurableHandheld Client
BrowserApplication
ShaperApplication
Shaper Network ConditionsNetwork
Conditions
ApplicationRequirementsApplication
Requirements
Access Profile
Access Profile
Client Characteristics
Client Characteristics
WLANWCDMA
Sujit Dey
Network Aware Application Adaptation 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.
Sujit Dey
Considering Network Effects on EnergyConsidering 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 strengthI (Network Load) : Table lookup based on network load
Sujit Dey
Test-bed EnvironmentTest-bed Environment
Needs Measurement (PalmVII,iPaq)
Simulation (OPNET)
Different access technologies
Realistic Network Environment
Ability to Instrument System Parameters
Accurate Measurement of Energy & Latency
Sujit Dey
ConclusionConclusion
• 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
Sujit Dey
Network-Aware Application AdaptationNetwork-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