FUTUR ET RUPTURES RESTITUTION DAY. Presented by: AMAL ELLOUZE February 2, 2017

Transcription

1 FUTUR ET RUPTURES RESTITUTION DAY Presented by: AMAL ELLOUZE February 2, 2017

2 Applications offloading in Mobile Cloud Computing environment

3 OUTLINE 1. Motivation and Objectives 2. Mobile Applications Offloading (MAO) Algorithm for LTE Environment 3. Application Servers Placement in Digital Radio Over Fiber (DRoF)- Based Infrastructure 4. Experimental Setup of MAO and Results (done in a collaboration with IMPACT Lab in Arizona, US) 5. Conclusion

4 CHAPTER 1 Motivation and Objectives

5 CHAPTER 1 : MOTIVATION AND OBJECTIVES 5 Problem Statement Solution: Remote execution Extend Battery autonomy; Enrich user s Quality of Experience (QoE). Two key Objectives : An offloading algorithm for mobile applications (MAO); Reduce power consumption on mobile terminals by executing jobs remotely; An admissible QoE. Where to place the remote applications servers in the mobile backhaul?

6 CHAPTER 2 MAO for LTE Environment

7 CHAPTER 2 : MAO for LTE Environment 2.1 Design Goals and Architecture 7 Smartphone Mobile Application Cloud Offloading System Cloud Server Offloaded Application Cloud Offloading System Offloaded Application Transmission Channel Decision Engine Decision Algorithm Context Profiler App Profiler Store context Store execution costs Context Database Figure: Schematic block diagram of the MAO algorithm

8 CHAPTER 2 : MAO for LTE Environment 2.1 Design Goals and Architecture 8 Main contributions: QoE Satisfaction; Network conditions considered; User Position within the Cell Considered CPU considered; State of Charge of the battery considered;

9 CHAPTER 2: MAO for LTE Environment 2.2 Implementation 9 Range of applications: Chess game: processing inherent to the execution of one move on the chess-board; Speech recognition: conversion of an analog speech to a text and vice Versa; Virus scanning: a program able to detect the presence of virus, and if possible, to kill it; Application CPU Interactivity Chess game High High Speech recognition Virus scanning Low High High Low

10 CHAPTER 2 : MAO for LTE Environment 2.3 Performance Evaluation 10 At high loads, applications with both high interactivity and CPU computation are prone to be offloaded. (Chess game case). At low loads, applications with high CPU demanding and low interactivity are those to be migrated. (Virus Scanning case)

11 CHAPTER 2 : MAO for LTE Environment 2.3 Fitting Functions 11 Fitting formulas could be potentially exploited by Cloud providers whenever they decide to deploy applications servers.

12 CHAPTER 3 Application Servers Placement in Digital Radio Over Fiber (DRoF)- Based Infrastructure

13 CHAPTER 3 : Servers Placement in DROF-Based WDM-PONs 3.1 Network Architecture and Servers Placement 13

14 CHAPTER 4 Experimental Set-up and Results

15 CHAPTER 4 : Experimental Set-up and Results 4.1 Experimental Set-up 15 Experiments done in a collaboration with the IMPACT Lab in Arizona, US Nexus-5,32 GB, Quad core 2.3 GHz Quiet Gaming PC Z77 to host our Cloud server, dual core i5/i7 at GHz Sample Application: Speech recognition PocketSphinx Free source code MAO Java code integration into the mobile application

16 CHAPTER 4 : Experimental Set-up and Results 4.2 Results 16 Runtime enhancement; Energy savings.

17 CHAPTER 5 Conclusion

18 CHAPTER 5 : Conclusion 18 Designed offloading algorithm (MAO) tweaking on energy efficiency and QoE; Used realistic applications to simulate; Evaluated model through numerical and experimental results; Applications servers placement over a real network infrastructure configuration.

19 PUBLICATIONS 19 A. Ellouze, M. Gagnaire and A. Haddad, A Mobile Application Offloading Algorithm for Mobile Cloud Computing, in Mobile Cloud Computing, Services, and Engineering (MobileCloud), rd IEEE International Conference, Mar. 2015, San Francisco, CA, pp A. Ellouze, M. Gagnaire, A Mobile Application Offloading: An opportunity towards Mobile Cloud Computing, in 3rd International IBM Cloud Academy Conference, (ICACON), May. 2015, Budapest, Hungary. A. Ellouze, M. Gagnaire, Toward an Optimized Servers Placement for Mobile Applications Offloading, in IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB), Oct. 2015, Montreal, QC, pp A. Ellouze, M. Gagnaire, A Novel Application Offloading Algorithm and an Optimized Application Servers Placement for Mobile Cloud Computing, in International Journal of Handheld Computing Research (IJHCR), 6(4), Oct-Dec. 2015, pp

20 20 Thank you