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研究生:張乃元
研究生(外文):Nai-Yuan Jhang
論文名稱:內建服務品質考量之資料回復策略的節能糾刪碼框架研究設計
論文名稱(外文):A QoS-aware Data Reconstruction Strategy within an Energy-efficient Erasure Codes Framework
指導教授:石維寬石維寬引用關係
指導教授(外文):Wei-Kuan Shih
學位類別:碩士
校院名稱:國立清華大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:英文
論文頁數:30
中文關鍵詞:糾刪碼節能資料回復
相關次數:
  • 被引用被引用:0
  • 點閱點閱:120
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  • 下載下載:5
  • 收藏至我的研究室書目清單書目收藏:0
近年來,市面上有許多雲端儲存系統,像是:GOOGLE Drive、Dropbox、iCloud跟Sky Drive,在儲存用戶的私用資料跟系統資料的方面必須保證端儲存系統必須有可靠性跟安全性,因此雲端儲存系統為了提高資料的可靠性,市面的儲存系統大多數會使用糾錯碼機制來當作其系統的資料容錯機制,雖然這些容錯機制增加了資料的可靠性,但是也增加系統儲存成本跟耗電量,然而,目前節能資料儲存系統都是開發在RAID-base的架構,並沒有開發在使用糾錯碼的系統,根據上述,我們想要提供一個能節能並有著基於糾錯碼資料回復上面有著服務品質考量的叫做EECache-scheme儲存系統,這個方案可以減少在資料回覆時候的耗電量跟減少回應使用者需求時間。
Recently, many applications and users rely on cloud storage services, such as
Google drive, Dropbox, iCloud and Sky drive, to store private files and system data,
and cloud storage services must thus be reliable and secure. To increase reliability,
previous studies have proposed a variety of erasure coding algorithms for data fault
tolerance for use in storage systems. Although these data fault tolerance mechanisms
increase data reliability, implementation also increases storage system costs and energy
consumption due to data redundancy. However, to date energy-efficient schemes have
only been developed based on a RAID architecture, and none have been implemented
using an erasure coding algorithm. To address this issue, this study proposes an energyaware
I/O framework with a quality-of service (QoS) aware data reconstruction
scheduler for erasure coding algorithms, called the EECache-scheme. This approach
reduces storage system energy consumption and decreases response times for user
requests when the system restores failed disks. A series of experiments show that the
proposed scheme can significantly reduce power consumption in storage systems and
reduces response times by xx% over a solution without QoS control.
Contents
ABSTRACT 2
Chapter 1. INTRODUCTION 3
Chapter 2. BACKGROUND AND MOTIVATIONS 5
2.1 Data Fault-Tolerance Mechanism for Cloud Storage 5
2.2 Green Data Center 6
2.3 Local Reconstruction Codes 7
2.4 Motivation 9
Chapter 3. A GENERAL ENERGY-EFFICIENT FRAMEWORK 10
3.1 Overview 10
3.2 Temporal Cache - An Endurance-aware policy 13
3.3 Read Cache - A Performance-enhanced Design 15
3.4 A Modified Round-robin Scheduler 16
3.5 A QoS-aware Data Reconstruction Strategy 18
3.6 File Operations Management 20
Chapter 4. PERFORMANCE EVALUATION 23
4.1 Experimental Setup 23
4.2 Experiential Results 24
Chapter 5. CONCLUSION AND FUTURE WORK 27
REFERENCES 28

[1] D. Ford, F. Labelle, F. I. Popovici, M. Stokely, V.-A. Truong, L. Barroso, C. Grimes, and S. Quinlan, Availability in Globally Distributed Storage Systems, in the 9th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’10), 2010.
[2] B. Calder, J. Wang, A. Ogus, N. Nilakantan, A. Skjolsvold, S. McKelvie, Y. Xu, S. Srivastav, J. Wu, H. Simitci, J. Haridas, C. Uddaraju, H. Khatri, A. Edwards, V. Bedekar, S. Mainali, R. Abbasi, A. Agarwal, M. F. ul Haq, M. I. ul Haq, D. Bhardwaj, S. Dayanand, A. Adusumilli, M. McNett, S. Sankaran, K. Manivannan, and L. Rigas, Windows Azure Storage: a highly available cloud storage service with strong consistency, in Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (SOSP ’11), pp. 143-157, 2011.
[3] K. V. Rashmi, N. B. Shah, D. Gu, H. Kuang, D. Borthakur, and K. Ramchandran, A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster, in the 5th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage ’13), 2013.
[4] H.-Y. Lin and W.-G. Tzeng, A Secure Decentralized Erasure Code for Distributed Networked Storage, in IEEE Transactions on Parallel and Distributed Systems, vol. 21, no. 11, pp. 1586-1594, 2010.
[5] H.-Y. Lin and W.-G. Tzeng, A Secure Erasure Code-Based Cloud Storage System with Secure Data Forwarding, in IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 6, pp. 995-1003, 2012.
[6] X. Luo and J. Shu, Load-Balanced Recovery Schemes for Single-Disk Failure in Storage Systems with Any Erasure Code, in the 42nd International Conference on Parallel Processing (ICPP13), pp. 552-561, 2013.
[7] F. Andr, A.-M. Kermarrec, E. L. Merrer, N. L. Scouarnec, G. Straub, and A. v. Kempen, Archiving cold data in warehouses with clustered network coding, in the Proceedings of the Ninth European Conference on Computer Systems (EuroSys14), 2014.
[8] M. Silberstein, L. Ganesh, Y. Wang, L. Alvisi, and M. Dahlin, Lazy Means Smart: Reducing Repair Bandwidth Costs in Erasure-coded Distributed Storage, in Proceedings of International Conference on Systems and Storage (SYSTOR14), pp. 1-7, 2014.
[9] T. Xie, SEA: A Striping-Based Energy-Aware Strategy for Data Placement in RAID-Structured Storage Systems, in IEEE Transactions on Computers, vol. 57, no. 6, pp. 748-761, 2008.

[10] R. T. Kaushik and M. Bhandarkar, GreenHDFS: Towards an Energyconserving, Storageefcient, Hybrid Hadoop Compute Cluster, in Proceedings of the 2010 International Conference on Power Aware Computing and Systems (HotPower10). pp. 19, 2010.
[11] D. Patterson, G. Gibson, and R. Katz, A case for redundant arrays of inexpensive disks (RAID), in Proceedings of the 1988 ACM SIGMOD international conference on Management of data (SIGMOD88), pp. 109- 116, 1988.
[12] J. S. Plank, The RAID-6 Liberation codes, in 6th USENIX Conference on File and Storage Technologies (FAST08), pp. 97-110, 2008.
[13] K. Hwang, H. Jin, and R. Ho, RAID-x: a new distributed disk array for I/O-centric cluster computing, in the Ninth International Symposium on High-Performance Distributed Computing, (HPDC2000), pp. 279-286, 2000.
[14] G. Zhang, W. Zheng, and K. Li, Rethinking RAID-5 Data Layout for Better Scalability, in IEEE Transactions on Computers, vol. 63, no. 11, pp. 2816-2828, July 2013.
[15] J. L. Hafner, WEAVER Codes: Highly Fault Tolerant Erasure Codes for Storage Systems, in 3rd USENIX Conference on File and Storage Technologies (FAST05), pp. 211-224, 2005.
[16] G.-L. Feng, R. H. Deng, F. Bao, J.-C. Shen, New Efficient MDS Array Codes for RAID Part II: Rabin-Like Codes for Tolerating Multiple (greater than or equal to 4) Disk Failures, in IEEE Transactions on Computers, vol.54, no. 12, pp. 1473-1483, December 2005.
[17] C. Huang, H. Simitci, Y. Xu, A. Ogus, B. Calder, P. Gopalan, J. Li, and S. Yekhanin, Erasure Coding in Windows Azure Storage, in 2012 USENIX Annual Technical Conference (ATC12), pp. 15-26, 2012.
[18] C. Weddle, M. Oldham, J. Qian, and A. A. Wang, PARAID: The gearshifting power-aware RAID, in 2007 USENIX Conference on File and Storage Technologies (FAST07), pp. 245-260, 2007.
[19] J. Wang, H. Zhu, and Dong Li, eRAID: Conserving Energy in Conventional Disk-Based RAID System, in IEEE Transactions on Computers, vol.57, no. 3, pp. 359-374, March 2008.
[20] L. Xiao, Tan Yu-An, and Sun Zhizhuo, Semi-RAID: A reliable energyaware RAID data layout for sequential data access, in IEEE 27th Symposium on Mass Storage Systems and Technologies (MSST11), pp.1 11, 23-27 May 2011
[21] A. Verma, R. Koller, L. Useche, and R. Rangaswami, SRCMap: energy proportional storage using dynamic consolidation, in Proceedings of the 8th USENIX conference on File and storage technologies (FAST’10), pp.20 20, 2010.

[22] H. Huang, W. Hung, and K. G. Shin, FS2: dynamic data replication in free disk space for improving disk performance and energy consumption, in Proceedings of the twentieth ACM symposium on Operating systems principles (SOSP05), pp.263 276, 2005.
[23] T.-Y. Chen, T.-T. Yeh, H.-W. Wei, Y.-X. Fang, W.-K. Shih, and T.-s. Hsu, CacheRAID: An Efficient Adaptive Write Cache Policy to Conserve RAID Disk Array Energy, in Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing (UCC12), pp.117-124, 2012.
[24] K.M. Greenan, X. Li, and J.J. Wylie, Flat XOR-based erasure codes in storage systems: Constructions, efficient recovery, and tradeoffs, in IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST10), pp.1-14, 2010.
[25] C. Huang, M. Chen, and J. Li, Pyramid Codes: Flexible Schemes to Trade Space for Access Efficiency in Reliable Data Storage Systems, in ACM Transactions on Storage, vol.9, no. 1, pp. 3:1–3:28, 2013.

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