1. Nguyen Thi Thanh Nha HMCL by Ying Zhang, Gang Huang, Xuanzhe Liu, Wei Zhang, Hong Mei, and Shunxiang Yang Refactoring Android Java Code for On-Demand Computation Offloading

2. Nguyen Thi Thanh Nha - HMCL  Android is open source  More than 59% of smartphone market  Limits  Battery Power  Size  Processing Power Refactoring Android Java Code for On-Demand Computation Offloading 2

3. Nguyen Thi Thanh Nha - HMCL  Some code can only run in a mobile device  GPS  Accelerometer  Sensors -> Have to identify which parts of the app cannot be offloaded  The reduced execution time must be greater than the network delay caused by computation offloading -> Have to calculate which parts are worth offloading  Changes of user requirements and runtime environments -> Have to consider such changes in computation offloading Refactoring Android Java Code for On-Demand Computation Offloading 3

4. Nguyen Thi Thanh Nha - HMCL 4  Present a tool, named DPartner, that automatically refactors Android applications to be the ones with computation offloading capability Refactoring Android Java Code for On-Demand Computation Offloading Refactoring restructure the given code without altering the external functionality Refactoring restructure the given code without altering the external functionality

5. Nguyen Thi Thanh Nha - HMCL  Offloading computations can be implemented as remotely deploying and invoking classes performing the computation  Refactoring is characterized by three aspects  Source Structure  Local invocation  Remote invocation  Target Structure  On-demand Remote Invocation  Refactoring Steps Refactoring Android Java Code for On-Demand Computation Offloading 5

6. Nguyen Thi Thanh Nha - HMCL  Programs run on local processor  Not support offloading any computation in class N Refactoring Android Java Code for On-Demand Computation Offloading 6

7. Nguyen Thi Thanh Nha - HMCL  Class X invoke the methods of a remote class N.  Support offloading computation in class N  Problem: time and energy consuming if N and X are in the same VM Refactoring Android Java Code for On-Demand Computation Offloading 7

8. Nguyen Thi Thanh Nha - HMCL Refactoring Android Java Code for On-Demand Computation Offloading 8 Forwards the method invocations to the latter Keeps unchanged if the location of the proxied class N is changed from local to remote, or from one remote server to another -> program structure will not know if the server or connection is changed Determine the current location of N Cross network communication from X to N

9. Nguyen Thi Thanh Nha - HMCL Refactoring Android Java Code for On-Demand Computation Offloading 9 Two Types of classes Movable Anchored: use some special resources available only on the phone Structure is changed to process on remote server. Classes that frequently interacted should be offloaded as a whole. Avoid the time-consuming network communication Help accelerate runtime decision The Java byte code and resources are packaged and generated into two deployable files.

10. Nguyen Thi Thanh Nha - HMCL 10 Refactoring Android Java Code for On-Demand Computation Offloading

11. Nguyen Thi Thanh Nha - HMCL 11  Anchored class  Exist “native” keyword in class methods  The class extends/implements/uses the Android system classes  E.g. the “android.view.View” class is used as the parent class for drawing the GUI of an Android app  Movable class  The rest of classes  False negative: a class is classified as anchored but it can actually be offloaded.  False positive: a class is classified as movable but it cannot be offloaded. Provides a configuration file in which the naming patterns of anchored classes Provides a configuration file in which the naming patterns of anchored classes Refactoring Android Java Code for On-Demand Computation Offloading

12. Nguyen Thi Thanh Nha - HMCL 12  make a proxy act exactly like its proxied class  the proxy will have the same program structure as the proxied class  N extends NParent, NProxy should also extend NParent’s proxy Refactoring Android Java Code for On-Demand Computation Offloading

13. Nguyen Thi Thanh Nha - HMCL  Evaluated on 3 Android applications  Reduced execution time by 46%-97%  Reduced battery consumption 27%-83% Refactoring Android Java Code for On-Demand Computation Offloading 13

14. Nguyen Thi Thanh Nha - HMCL THANK YOU Refactoring Android Java Code for On-Demand Computation Offloading 14