Net-Centric Software and
Systems I/UCRC
A Framework for
QoS and Power Management for
Mobile Devices in Service Clouds
Project Lead: I-Ling Yen, Farokh Bastani, Krishna Kavi
Date: April 1, 2010
Copyright © 2010 NSF Net-Centric I/UCRC. All rights reserved.
2009/Current Project Overview
A Framework for QoS and Power Management for
Mobile Devices in Service Clouds
Project Scope:
Image
capturing
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capturing
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Personal
Info DB
Facial
Image DB
Translation
Service
Project Schedule:
4: Preliminary evaluation
Service Cloud
3: Design QPM framework
Personal
Info DB
Translation
Service
2: Evaluate service cloud benefit
Local Info
Service
Video
DB
Facial
Image DB
Select the services in the cloud
To save power on the handheld device
Tasks:
1. Develop experimentation environment,
including the power measurement, power
parameter settings, application suite, etc.
2. Evaluate the potential benefit of delegating
service execution to service cloud in order to
save power for mobile devices
3. Design QPM (QoS and power management)
framework to realize the proposed idea
4. Preliminary evaluation of the QPM framework
1: Enable power measurement
and management
A M J J A S O N D J F M A
09
10
Deliverables:
• Experimental results showing the benefit of
using service cloud in saving power for
mobile devices
• Design of power optimization algorithms
Success Criteria:
• This project will demonstrate a significant
improvement in reducing power consumption
on mobile devices
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Significant Finding/Accomplishment!
Complete
Partially Complete
2009 Project Results
TASK
1: Develop power measurement
and management capability on
Linux laptop using ACPI
Not Started
STAT
PROGRESS and ACCOMPLISHMENT

Only able to read power consumption every 10
seconds. Only able to get overall power
consumption from battery.
2: Evaluate the potential benefit of
delegating service execution to
service cloud on power saving for
mobile devices

3: Design the QPM framework

Completed the first version of the design.
4: Preliminary evaluation of the
QPM framework

Prototype demonstrated with contrived data
only.

Intermediate results submitted to IEEE SOSE
conference. Waiting for IAB approval.
5: Publish results
Completed two sample case studies. Results
show significant reduction in power
consumption on the mobile device.
This research illustrates the potential effectiveness of using service cloud
for power conservation on mobile devices
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Major Accomplishments, Discoveries
and Surprises
1. Evaluated the potential benefit of executing services in the cloud for
saving power on the mobile device
Image
Size
Platform
Selection
100x90
pixels
Cloud
50x50
pixels
Cloud
Latency (Seconds)
Comput.
36.80
Comm.
0.07
Local
Local
17.80
0.057
Total
Local power
(watt*sec)
36.87
659.97 (17.9w)
82.70
2315.60 (28.0w)
17.86
289.28 (16.2w)
44.50
1152.55 (25.9w)
2. Designed the QPM (QoS and power management) framework,
focusing on two major features
• Better prediction. Predicting the workloads and execution patterns
of the next time periods
• Collaborative. Service cloud performs analysis on historical
information and defines parameterized policies. Mobile device
makes on-the-fly decisions accordingly
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New Problems
•
Whether to execute a service in the cloud or on the mobile device?
•
•
When it can access service cloud directly
When it must access service cloud through other mobile devices
•
Which services should be allocated on the mobile device?
•
Minimize the communication cost by bringing services closer to the
users
Existing works
• None consider the same
problem
•
•
Existing prediction models are
generally simplistic. Hence,
QoS and power management
decisions can be improved
None consider service
migration/replication
Image
capturing
Audio
capturing
…
Personal
Info DB
Facial
Image DB
Translation
Service
Service Cloud
Personal
Info DB
Translation
Service
Local Info
Service
Video
DB
Facial
Image DB
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Our Solution
•
Better prediction is the key to better power and QoS management
• What to predict:
• Applications to be executed next
• Execution patterns of these applications
• How to predict:
• For each application, for each specific input, gather their history
of events and obtain execution patterns
• Consider current and potential future tasks, aggregate their
historical execution patterns
•
Decision process
• Offline analysis in the service cloud
to determine the best QoS and
power management parameters
 Derive rules accordingly
• Mobile device makes on-the-fly
decisions based on the rules
QPMMD
SPESD
QPM
SADM
QoS-PM
Service Profile
SPESD
QoS-PM
SADM
SMI
CAM-AM
User Profile
Power Manager
Service
Profile
User
Profile
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Resource
Profile
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2010/New Project Summary
A Framework for QoS and Power Management for
Mobile Devices in Service Clouds
Tasks:
1. Build the experimental environment on
Android mobile phone (G1) and PlanetLab
2. Develop the prediction algorithms to predict
execution patterns of future time periods
3. Develop the execution decision algorithms
4. Develop the service migration infrastructure
5. Develop the service allocation decision
algorithms
6. Validate the framework design
Project Schedule:
Task 6: Evaluation
Tasks 2,3: Simple data
collection + coordinated
prediction & decision
Task 1
Task 6: New
Evaluation
A M J J A S O N D J F M A
10
Research Goals:
1. Making use of service cloud to improve
power saving on mobile devices while
satisfying QoS goals
 Increase the accessibility of the users to
complete their critical tasks
 Increase the situation-awareness and
agility of users in special environment
(trapped or war fighting)
2. Extend the research to a cloud of mobile
devices and Internet-based service cloud
Tasks 1-3,6: Enhanced
data collection,
prediction & decision
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Benefits to Industry Partners:
1. Significantly improved techniques in QoS
and power management
2. Advanced design and prototype framework
implementation
3. Experimental results to understand the
promising and insignificant factors in QoS
and power management
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