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Android OS Development What Lies Beyond SDK !

Android OS Development What Lies Beyond SDK !. Bhanu Kaushik April 16 2013 PhD Student Department of Computer Science, University of Massachusetts, Lowell, MA. . Outline. Session II : Android SDK All You Need to Know Samples Summary Session II. Session I : Android OS

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Android OS Development What Lies Beyond SDK !

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  1. Android OS Development What Lies Beyond SDK ! Bhanu Kaushik April 16 2013 PhD Student Department of Computer Science, University of Massachusetts, Lowell, MA.

  2. Outline • Session II : Android SDK • All You Need to Know • Samples • Summary Session II • Session I : Android OS • Introduction • Android Architecture • Download and Build • Android Code Organization • Implementation - Demo • SmartParcel • Session I – Summary

  3. Introduction Well This is Not Necessary ! • Supports Millions of mobile devices in more than 190 countries. • It's the largest installed base of any mobile platform.

  4. Session I Android OS

  5. Session I What will we learn ! • How to get Android Source code ? • What Goes Where in Android? • How to Compile the code? • How can I create apps shipped with OS ? • How to modify OS to offer new Services? • How to use custom services in Apps ? • Using all above , How can I provide solutions to real life problems ?

  6. Android Architecture

  7. Android Architecture Enhancements over Linux 2.6 • Binder: OpenBinder-based driver to facilitate inter-process communication (IPC) • Android Power Management: a light weight power management driver optimized for embedded systems. • Low Memory Killer: To kill off processes to free up memory as necessary. • Logger: A light weight logging device used to capture system, radio, log data, etc. • USB Gadget: Uses the USB function framework. • Android/PMEM: Provide contiguous physical memory regions to userspace libraries that interact with the digital signal processor (DSP). • Android Alarm: A driver which provides timers that can wake the device up from sleep.

  8. Downloadand Build Environment Setup • Available at, http://source.android.com/source/initializing.html (Link) • Requirements • Linux or MacOS (Only Unix Based Systems) • Python 2.6 -- 2.7 (python.org.) • GNU Make 3.81 - 3.82 (gnu.org,) • JDK 6 if you wish to build Gingerbread or newer • JDK 5 for Froyo or older. You can download both from (java.sun.com.) • Git 1.7 or newer (git-scm.com.)

  9. Downloadand Build Download • Available at, http://source.android.com/source/downloading.html (Link) • Basic Steps • Initialize Repo • Choose Build Version (Link) • Sync Repo • Go Grab a coffee – This will take a while !

  10. Downloadand Build Build • Instructions available at (Link) • Basic Steps • Setup Environment paths • $ source build/envsetup.sh • Choose Build Target using lunch • $ lunch full-eng • $ make –jN (j4, j8…j32) • Chose N between 1 and 2 times the number of hardware threads on the computer being used for the build • Go Grab a Lunch and a Nap – This will take a Loooong time!

  11. Android Code Organization Lets Dive into the Code

  12. Android Code Organization What we have seen so far ! • /bionic.: where the bionic library is. • /build/: is the main make file system. • /dalvik/: where the Dalvik VM and dex compiler is. • /development/: integration to IDE like eclipse emacs etc. • /device/: device specific code lies here. • /external/:external libraries go here. Eg. Skia, jpeg, sqlite. • /frameworks/:all the android frameworks go here. • /hardware/: HAL, hardware abstract layer • /prebuilt/: all the prebuilt code. Linux Kernel goes here. • /packages/: all default apps shipped with system • /out/: final output directory.

  13. Implementation - Demo

  14. Implementation System APP - Steps involved • Create App using SDK (or otherwise) • Turn off the Build Automatically in Eclipse. • Copy the code to /packages/apps/YOUR_APP • Create make file • Template • LOCAL_PATH:= $(call my-dir) • include $(CLEAR_VARS) • LOCAL_SRC_FILES := $(call my-dir/src/) • LOCAL_PACKAGE_NAME := AppCall • include $(BUILD_PACKAGE) • Expose Application • In/build/target/product/core.mk • Add , YOUR_APP \ in product packages section

  15. Implementation Steps involved • Create service Aidl (Link) • Add AIDL to Build • Add Service Functionality • Expose service • Use the service

  16. Session I SmartParcel: A Collaborative Data Sharing Framework for Mobile Operating Systems Bhanu Kaushik∗ , HonggangZhang†, XinwenFu∗, BenyuanLiu∗ , JieWang∗ ∗Department of Computer Science, University of Massachusetts, Lowell, MA. †Department of Computer and Information Science, Fordham University, Bronx NY

  17. Introduction • Huge number of Mobile Devices such as Smartphones, Tablets, PDAs, portable media players etc. • “About 6.2 billion users around the globe” – Ericsson, 2012. • These devices support large number of Internet based applications. • These Applications work on simple one-to-one client-server data distribution model. • Results in: • Increasing concerns about volume of global online digital content generated by these devices. • Multi-fold increase in Network traffic originating from these devices • “100 PetaByte/Month in 2007 to 700 PetaByte/Month in 2012”-Ericsson, 2012. • Huge incumbent content availability and maintainability cost.

  18. Motivation and Related Work Motivation • Major challenges faced by mobile Internet users • Carrier enforced limited data plans, • Unavailability of hardware (3G or LTE), • Unavailability of access points, • Service outagesand • Network and server overloads. • Results in: • Unavailability of application data to the users • High service maintainability cost, to both the service providers and hosting servers.

  19. Motivation and Related Work Related Work : Data Offloading • Proposed Solutions for data offloading • Large Scale • Alvarion, “Mobile data offloading for 3G and LTE networks.” • Cisco, “Architecture for mobile data offload over Wi-Fi access networks.” • Small Scale • Han et. al. “Mobile data offloading through opportunistic communications and social participation” • Lee et. al., “Mobile data offloading: How much can wifi deliver?” • Unaddressed Issues: • Entail huge changes in both, state of the art software and hardware technologies • Do not take into account the heterogeneity of application data.

  20. Motivation and Related Work Related Work: Opportunistic Data delivery and Familiar Strangers • Delay-Tolerant Networks (DTN) • Target the interoperability between and among challenged networks • Familiar Strangers • Coined by Stanley Milgram in 1972, “Individuals that regularly observe and exhibit some common patterns in their daily activities”. • SmartParcel uses the idea of opportunistic connectivity and in-network storage and retransmission from DTN architecture to ensure data delivery among the nodes in a “Familiar Strangers” network set up.

  21. Problem Definition SmartParcel • Our Goal is to develop framework of a Mobile data offloading and Service Assurance scheme by encouraging collaborative data sharing among spatio-temporally co-existing mobile devices. Fig. 1 : Proposed SmartParcel Approach

  22. Architecture Components • Service Discovery Manager • Data Transfer Manager • Service Cache Manager • Dynamic Cache • Static Cache • Network Interface Manager • Service APIs • Central Control Manager Fig. 2 : SmartParcel Service Architecture.

  23. Architecture Component Details • Service Discovery Manager: • Identifies the available candidates for data transfer by broadcasting a “SYN” message periodically • “SYN” packet contains meta-data about applications registered to SmartParcel. • The meta-data is organized as a key value pair, i.e., (“ApplicationId, TimeStamp”). • At receiver, based on the meta-data information it sets up a one-to-one connection • Data Transfer Manager: • Manages the data transfer. • Can manage concurrent connections to multiple devices. • To reduce the network overhead, sends data for multiple applications as one chunk.

  24. Architecture Component Details • Service Cache Manager: • Service cache to store the application specific (heterogeneous ) data . • Dynamic Cache • In-memory cache for storing the applications meta-data information. • Implemented as Hash Map with (Application Id, Timestamp) as key-value pairs. • Static Cache • Static cache for storing the actual application specific data. • Maintained as SQLite database. • Schema “Ap- plication Id (as string), Data (as blob), Time Stamp” • Primary key : Application id and timestamp • Flexibility to developer to assign “Time to live” and “Reset-Time” for the application data, end of day by default.

  25. Architecture Component Details • Central Control Manager: • Manage the control from all components of the SmartParcel service. • All components work under same instance for synchronous operation. • Network Interface Manager: • Internal service, responsible for managing network connections. • Assists Service Discovery for identifying available devices on different network interfaces (3G, LTE, WiFi, BlueTooth etc.). • Service APIs: • Subscribe or unsubscribe to service • Update app data • Settings • Sharing statistics etc.

  26. Architecture Android and SmartParcel • Android SDK • New set of permissions. • SMP_ALL, SMP_BLUETOOTH, SMP_WIFI, SMP_NFC and SMP_BT_WIFI. Table 1 : Resources used in different permissions Fig. 3 : Integration of SmartParcel in Android framework • Android OS • Integrated in the “System Server” module. • System Server is launched by Zygote. • Zygote forks the SmartParcel service as a system service. • Ensures system level privileges and independence from the application “context”.

  27. Simulation Setup Data Set • MIT Reality Mining Data Set • 100 unique devices, 500,000 hours, 9 months • We use the Bluetooth encounters data. Table 2 : Data Set Description Fig 5 : Distribution of Device Encounters. Fig 4 : Distribution of Active Devices Per Day. Fig 6 : Hourly Variation of Device Encounters.

  28. Simulation Setup Setup Parameters • Data Refresh Rate (DRR) : The frequency with which the data is being refreshed. • Allowed Server Connections (ASC) : Number of devices allowed to get data from server on each day. • User Participation Probability (UPP) : The Probability of user acting selfish, i.e., limiting its participation by only receiving data and not sending data • We measure the Data Availability Ratio (DAR)

  29. Results Effect of user’s social activity level • User Participation Probability (UPP) = 100% • Data Refresh Rate (DRR) =1 Refresh interval Fig 6 : Effect of ASC on DAR over the Day, when ASC = 1 Fig 8 : Effect of ASC on DAR , when ASC =1 to 75 devices. Fig 7 : Effect of ASC on DAR over the Day, when ASC = 30

  30. Results Effect of Data Refresh Rate (DRR) • User Participation Probability (UPP) = 100% • Data Refresh Rate (DRR) = 2 Refresh intervals, • 12:00am -11:59am and 12:00am-07:59am Fig 9 : Variation of Data Availability Ratio (DAR) with Data Refresh Rate (DRR) when DRR = 2 and Refresh Interval 12:00 am - 11:59 am. Fig 10 : Variation of Data Availability Ratio (DAR) with Data Refresh Rate (DRR) when DRR = 2 and Refresh Interval 12:00pm - 11:59pm.

  31. Results Effect of Data Refresh Rate (DRR) • User Participation Probability (UPP) = 100% • Data Refresh Rate (DRR) = 3 Refresh intervals. Fig 12 : Refresh Interval 08:00am-03:59pm. Fig 11 : Refresh Interval 12:00am-07:59am. Fig 13 : Refresh Interval 04:00pm-11:59pm.

  32. Results Effect of Selfishness • User Participation Probability (UPP) = 10%, 20%, 50% and 90%. • Data Refresh Rate (DRR) = 1 Refresh interval • Allowed Server Connections(ASC) = 1 to 90 devices. Fig 14 : Variation of Data Availability Ratio with User Participation Probability(UPP) and Allowed Server Connections(ASC). (*Median of 1000 Simulation runs)

  33. Conclusions and Future Work • “SmartParcel” - A novel approach for Data sharing among co-existing and co-located devices is presented. • “One for all”, multiple incentive system for application developers, Internet service providers and application data providers (eg. cloud services) with collateral benefits for the consumer itself. • We discussed the Design and implementation “SmartParcel” in Android. • Implementation in android framework dictates the feasibility of the architecture. • Flexibility of design ensures integration in almost every existing mobile operating system. • In the future, we intend to investigate the scalability and performance issues encountered on real devices.

  34. Session I : Summary • Android Source code Download • Code Organization in Android- What Goes Where. • Compiling the code. • Creating Apps shipped with OS • Modifying OS to offer new Services • Using custom services in Apps • Demo of Sample project - SmartParcel

  35. Session II Android SDK

  36. Session II What will we learn ! • Getting the right tools ! • Basic Android app • Services in Apps • AsyncTask -Performance Enhancement • Sound Recoder demo

  37. Implementation - Demo

  38. Session II Summary ! • Basic Android app • Services in Apps • AsyncTask -Performance Enhancement • Sound Recorder demo

  39. Thank You ! Questions ?

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