Lecture 11. RFS A Network File System for Mobile Devices and the Cloud
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1 Lecture 11 RFS A Network File System for Mobile Devices and the Cloud Yuan Dong, Jinzhan Peng, Dawei Wang, Haiyang Zhu, Fang Wang, Sun C. Chan, Michael P. Mesnier Advanced Operating Systems January 4th, 2012 SOA/OS Lecture 11, RFS 1/44
2 Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 2/44
3 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 3/44
4 Context Mobile Devices increasing number of applications - lots of data - key issue: access to dependable storage cloud storage - attractive Cloud storage for mobile devices - new issues unpredictable wireless network connectivity data privacy over the network Solution: RaindropFS wireless friendly network file-system... for mobile devices and the cloud SOA/OS Lecture 11, RFS 4/44
5 RaindropFS Wireless friendly network connectivity average bandwidth around the world (2010 study): 105 Kbps MBps Network file system - issues to be resolved unpredictable connectivity of the wireless network data privacy introduced by the cloud SOA/OS Lecture 11, RFS 5/44
6 Issue #1: Unpredictable Wireless Connectivity local storage cache - the right approach the unpredictable connectivity problem server-centric management server controlled synchronization between server and client caches not well suited for unpredictable wireless connectivity constrains such as varying bandwidth cost, battery life etc. solution: management controlled by the client continuous file consistency not a goal SOA/OS Lecture 11, RFS 6/44
7 Issue #2: Data Privacy mobile devices - single user public clouds: no satisfactory solution to privacy solution: client-centric approach which depends on applications SOA/OS Lecture 11, RFS 7/44
8 Contributions - Raindrop FS device-aware cache management different networks different costs energy-awareness different levels of client-driven data security and privacy policies client-aware optimizations at the server previous usage recorded predict usage server prepush partial file caching for large files integrate with Amazon S3 cloud storage tested Android running on top of Raindrop FS (x86-based netbook) SOA/OS Lecture 11, RFS 8/44
9 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 9/44
10 Design Goals Cloud storage abstraction ability to connect using any interface to cloud storage synchronize data efficiently and transparently Connection optimization adapt connections based on the mobile device s connectivity Client data protection client-controlled user data security and privacy SOA/OS Lecture 11, RFS 10/44
11 Cloud storage abstraction Components RaindropFS server responsible for mapping files to the cloud RaindropFS client residing on the mobile devices HTTP for client-server communication Features Cloud cache (64 MB segment = unit of transmission between RFS server and cloud provider) Cloud adapter - support for multiple clouds SOA/OS Lecture 11, RFS 11/44
12 The Raindrop FS client-server model Figura: The Raindrop FS client-server model SOA/OS Lecture 11, RFS 12/44
13 Network communication in Raindrop FS Demand fetching update local storage from cloud Synchronization transfer data between client-cache and cloud Consistency maintenance consistency of files over multiple clients Figura: Packets transmitted over WiFi for sync/consistency maintenance SOA/OS Lecture 11, RFS 13/44
14 Connection optimization Network file-system design server-centric - server controls synchronization and consistency maintenance client-centric - clients decide when to synchronize Consistency models close-to-open - each close() requires interaction with the server RFS s client-controlled consistency - synchronization at client-specified sync points; server maintains version numbers for files and folders SOA/OS Lecture 11, RFS 14/44
15 Consistency models Figura: Consistency models SOA/OS Lecture 11, RFS 15/44
16 Device-aware synchronization scheduling Figura: Device states used in RFS multiple levels per state user configuration is required to define sync conditions - example: low-cost/free network, high battery capacity, low CPU and memory load SOA/OS Lecture 11, RFS 16/44
17 Reintegration logging all file operations: costly solution: status vector (files: 5 bits; folders: 4 bits - no modify bit) <deleted, created, renamed, attr-changed, modified> Figura: File status vector transition SOA/OS Lecture 11, RFS 17/44
18 Raindrop FS Architecture Figura: RFS Architecture SOA/OS Lecture 11, RFS 18/44
19 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 19/44
20 Overview Raindrop FS client Linux kernel module for performance critical components: local cache heaps, metadata manager user space: Sync daemon, encryption engine Raindrop FS server built on cloud storage directly RFS files: regular files, links to public Internet resources uses HTTP 1.1 and SOAP, allowing clients to bypass network firewalls, use gateways or proxies zlib compression algorithm for communication efficiency SOA/OS Lecture 11, RFS 20/44
21 Managing local cache heaps other network file systems: local file mapping, separate partition in RFS: partial file caching all cached blocks for a given RFS file stored in one file organized as a heap heaps are preallocated (blocks physically contiguous) recycle action (cache evictions) for freeing up space (heap can no longer accommodate new cached blocks) support for block-pinning SOA/OS Lecture 11, RFS 21/44
22 on mount: metadata loaded into memory Managing local cache heaps client maintains a dirty list of modified files and directories bitmap per file indicating dirty blocks that need sync if metadata updates from server: client invalidates cached blocks Figura: How RFS directories & files map to a local cache SOA/OS Lecture 11, RFS 22/44
23 Integrating the RFS server and the cloud metadata in MySQL (adapts to Amazon s RDS) file data on Amazon S3 (thin storage API with Get/Put/Delete) updates pushed to the server in 64 MB segments (communication efficiency) RFS RESTful web service API (without management options) (files, directories) create, delete, rename (files, directories) set/get entity attributes (files) read, write file blocks (directories) read - retrieve file list update - retrieve update information from the server within specified time interval SOA/OS Lecture 11, RFS 23/44
24 Data privacy client-side encryption user-policy based (not everything needs to be encrypted) AES used on the client for read/write operations metadata currently not encrypted reveals structure of the client file system to the server tradeoff that allows block-level optimizations such as updates of the system files SOA/OS Lecture 11, RFS 24/44
25 Server prepush used to speed up cold file fetching (unknown files) file s block access pattern collected across multiple users more blocks are pushed on a new request from a client based on the access pattern access patterns stored per file in groups of tuples <start-block, end-block> requests trigger lookups into the groups of tuples on match, server prepushes blocks on miss, server records a new access pattern groups can be merged if adjacent prepush hint added to client requests SOA/OS Lecture 11, RFS 25/44
26 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 26/44
27 Conditions Mobile device (Asus EeePC 1000H, 1.6 GHz Atom CPU, 1GB RAM) Ubuntu Mobile Compared to FScache (with NFS as server) and Coda Connections Wired (100 MBps Ethernet) WiFi (54 MBps over a D-Link wireless router) WCDMA (7.2 MBps 3G network) Benchmarks grep - search for a text over the mounted network FS copyin - copy from the local FS to the mounted network FS copyout - copy from mounted network FS to the local FS install - untar archive in the network FS Cold vs. Warm (data in local cache) tests SOA/OS Lecture 11, RFS 27/44
28 Benchmark Warm mode testing - RFS lazy sync design FScache only caches for reading - no changes for warm mode copyin & install tests Figura: Benchmark performance (seconds) SOA/OS Lecture 11, RFS 28/44
29 Benchmark Coda - small number of request for sync (network type has no impact) RFS - no requests sent Figura: Benchmark packets SOA/OS Lecture 11, RFS 29/44
30 Privacy overhead encryption in read/write synchronization operations no encryption in local operations lower overhead on low bandwidth connections Figura: Privacy overhead of the read operation SOA/OS Lecture 11, RFS 30/44
31 Case Study Description Android-x86 platform on EeePC 1000H ported RFS to the Android Linux kernel changed /root/init.rc to point to the Android system on the RFS server only Linux kernel & ramdisk on local FS boot Android over RFS Android system files are public files (not encrypted) SOA/OS Lecture 11, RFS 31/44
32 Android system: 1322 files, 463 MB total RFS on boot transfer: 167 files, 49.4 MB Booting Android over RFS Figura: Booting Android over RFS SOA/OS Lecture 11, RFS 32/44
33 Booting Android over RFS Figura: Top 12 files in Android booting SOA/OS Lecture 11, RFS 33/44
34 Android booting with server prepush mmap() to load executables each page fault triggers remote file block read with server prepush request count drops 24x transmission size drops by 10% Figura: Server prepush on Android booting SOA/OS Lecture 11, RFS 34/44
35 Android booting with server prepush (speedup) Figura: Booting Android with server prepush SOA/OS Lecture 11, RFS 35/44
36 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 36/44
37 Related work (1) Cache management previous work - mainly server-centric popular network file systems not designed for mobile RFS - clients control Disconnected opperation Local cache: Coda, Version Control systems (CVS, SVN), browsers (offline mode), HTML5 (Local Storage) RFS - client-controlled caching File Systems for weak connectivity - Moxie reduced data transfer, addresses weak connections protects data in transmission (data privacy) vs. RFS (information privacy) no prefetching SOA/OS Lecture 11, RFS 37/44
38 Related work (2) Prefetch vs. Prepush lots of literature on prefetching MFS uses prefetching for adapting data access patterns to network availability server prepush - block access patterns collected across multiple users Privacy for the cloud NFS, Coda rely on trusted administrators, taking into account only access controls Amazon/Rackspace provide cloud service hosting but with no data privacy Applications atop of cloud storage Dropbox Jungle Disk, S3 Backup - client side encryption usually targeted for personal backup systems SOA/OS Lecture 11, RFS 38/44
39 Comparison between RFS and other mobile file systems Figura: Comparison between RFS and other mobile file systems SOA/OS Lecture 11, RFS 39/44
40 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 40/44
41 Conclusion client-centric design addresses unpredictable wireless network connectivity data privacy over the network client-control synchronization and consistency new optimizations server prepush for speeding up cold file fetching reintegration of changes in the device s with the cloud future work user-specified management policies hashing file contents for detecting redundant blocks additional encryption algorithms (e.g. public-key) SOA/OS Lecture 11, RFS 41/44
42 Outline Introduction Design Implementation Evaluation & Case Study Related work Conclusion Keywords SOA/OS Lecture 11, RFS 42/44
43 Keywords mobile network file system cloud storage data privacy device-aware cache management network aware battery aware partial file caching data synchronization server prepush Android Amazon S3 SOA/OS Lecture 11, RFS 43/44
44 Resources Yuan Dong, Haiyang Zhu, Jinzhan Peng, Fang Wang, Michael P. Mesnier, Dawei Wang, and Sun C. Chan. RFS: a network file system for mobile devices and the cloud, SIGOPS Operating Systems Review, Volume 45, Issue 1 (February 2011), SOA/OS Lecture 11, RFS 44/44
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