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: October 21, 2010 Copyright © 2010 NSF Net-Centric I/UCRC. All rights reserved.

Page 26/4/2016 Project Scope: Deliverables: Experimental results showing the benefit of using service cloud in saving power for mobile devices Design of power optimization algorithms 2010/Current Project Overview A Framework for QoS and Power Management for Mobile Devices in Service Clouds Success Criteria: This project will demonstrate a significant improvement in reducing power consumption on mobile devices by delegating tasks to service cloud Project Schedule: Execute the services in Cloud or mobile device? Save power & satisfy QoS req. QPM framework Tasks: 1.Build the experimental environment 2.Develop the prediction algorithms to predict QoS and power behavior for each service and for a service chain 3.Develop the execution decision algorithms 4.Develop the service migration infrastructure 5.Develop the service allocation decision algorithms 6.Validate the framework design A M J J A S O N D J F M A 1011 Task 1 Tasks 2,3: Simple data collection + coordinated prediction & decision Task 6: Evaluation Tasks 1-3,6: Enhanced data collection, prediction & decision Task 6: New Evaluation

Page 36/4/ Project Results TASK STAT PROGRESS and ACCOMPLISHMENT 1. Build the experimental environment Set up laptop and PC as the mobile device and the service cloud. Setup PowerTop for mobile device power measurement. 2. Develop the prediction algorithms to predict QoS and power behavior for each service and for a service chain Collected data and used them as historical information for prediction. Developing neural network to make QoS and power predictions for unexplored configurations. 3. Develop the execution decision algorithms Completed a decision algorithm for the mobile device to determine whether to execute the services in a task on the mobile device or in the service cloud. 6. Validate the framework design Established 3 scenarios, developed the involved services, used them to validate the framework design and obtained some results. Complete Partially Complete Not Started Significant Finding/Accomplishment! This research leverages service clouds for significantly reduced power consumption & latency on mobile devices

Page 46/4/2016 Our Solution Use service cloud to help power management in mobile devices E.g., computation intensive services can be delegated to cloud E.g., communication intensive services can be migrated to MD Decision process Service execution platform selection decision (SEPSD) Service allocation decision module (SADM) Service migration infrastructure (SMI) in the cloud Offline analysis in the service cloud to determine the best QoS and power management parameters  Derive parameterized rules Mobile device makes on-the-fly decisions based on the rules 6/4/2016

Page 56/4/2016 Major Accomplishments, Discoveries and Surprises 1. Evaluation results (power saving by QPM) Template holder, new results will be added for presentation 2. Developed a QPM pattern to be submitted to NCOIC Include a complete design of the system with major components that can be implemented using different technologies 6/4/2016

Page 66/4/2016 New Problems Based on the experimental results, Improve the QoS and power prediction accuracy by using better prediction models Consider more parameters that may affect QoS Train the prediction model with service profiles collected preliminary experimental studies Optimize SEPSDM decision process to reduce its power & latency For each service, make pre-analysis for mobile device and user specific predictions before downloading the service For frequently used service chain, pre-compute the tradeoff in QoS and power and maintain them in a table to facilitate quick run time search of best decisions Develop the data migration decision techniques in SADM Currently we use static decision on which data migration policy to use for each specific application (provided in the service profile) Will consider dynamic approach and implement prototypes 6/4/2016