A Metadata Cooperative Caching Architecture Based on SSD and DRAM for File Systems

The metadata IO plays a critical role in achieving the high IO scalability and throughput to file systems. Due to the resource contention, the performance of the metadata IO is low. Adding the SSD into the storage system is a effective way to improve the performance of file systems, but the current methods mainly focus on the performance of the data server, rarely aim to the performance of the metadata IO. In this paper, we proposed a novel cooperative caching management algorithm based on DRAM and SSD named ACSH. By exploiting the temporal locality widely exhibited in most of the metadata workloads, ACSH can improve the performance of the metadata IO with reducing the write traffic to the SSD, and it includes a adaptive adjustment model, which can adjust the number of the cached metadata according to the locality strength of the metadata workload for improving the perforamcne and reducing the write traffic to the SSD cache layer further. ACSH has been evaluated based on the real-world workloads. Our experiments show that ACSH can reduce the latency by upi¾źto 1.5---3X in contrast with the original cache consisting of DRAM which has the same cost with ACSH. Compared with the recent study LARC, it can reduce the write traffic to the SSD by upi¾źto 23---30i¾ź%.

[1]  Shankar Pasupathy,et al.  Spyglass: Fast, Scalable Metadata Search for Large-Scale Storage Systems , 2009, FAST.

[2]  Robert B. Ross,et al.  On the role of burst buffers in leadership-class storage systems , 2012, 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST).

[3]  Carlos Maltzahn,et al.  Ceph: a scalable, high-performance distributed file system , 2006, OSDI '06.

[4]  Scott A. Brandt,et al.  Dynamic Metadata Management for Petabyte-Scale File Systems , 2004, Proceedings of the ACM/IEEE SC2004 Conference.

[5]  Sridhar Mahadevan,et al.  DROP: Facilitating distributed metadata management in EB-scale storage systems , 2013, 2013 IEEE 29th Symposium on Mass Storage Systems and Technologies (MSST).

[6]  Qi Zhang,et al.  Characterization of storage workload traces from production Windows Servers , 2008, 2008 IEEE International Symposium on Workload Characterization.

[7]  Ethan L. Miller,et al.  Usage behavior of a large-scale scientific archive , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.

[8]  Antony I. T. Rowstron,et al.  Migrating server storage to SSDs: analysis of tradeoffs , 2009, EuroSys '09.

[9]  Sorin Faibish,et al.  Jitter-free co-processing on a prototype exascale storage stack , 2012, 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST).

[10]  Armand M. Makowski,et al.  The output of a cache under the independent reference model: where did the locality of reference go? , 2004, SIGMETRICS '04/Performance '04.

[11]  Anand Sivasubramaniam,et al.  HybridStore: A Cost-Efficient, High-Performance Storage System Combining SSDs and HDDs , 2011, 2011 IEEE 19th Annual International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems.

[12]  Howard Gobioff,et al.  The Google file system , 2003, SOSP '03.

[13]  Cristina L. Abad,et al.  A storage-centric analysis of MapReduce workloads: File popularity, temporal locality and arrival patterns , 2012, 2012 IEEE International Symposium on Workload Characterization (IISWC).

[14]  Galen M. Shipman,et al.  Workload characterization of a leadership class storage cluster , 2010, 2010 5th Petascale Data Storage Workshop (PDSW '10).

[15]  Kaladhar Voruganti,et al.  SLO-aware hybrid store , 2012, 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST).

[16]  Fred Douglis,et al.  Characteristics of backup workloads in production systems , 2012, FAST.

[17]  Li Fan,et al.  Web caching and Zipf-like distributions: evidence and implications , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[18]  Pete Wyckoff,et al.  File Creation Strategies in a Distributed Metadata File System , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[19]  Jie Ma,et al.  Adaptive and scalable metadata management to support a trillion files , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[20]  Feng Wang,et al.  File System Workload Analysis For Large Scale Scientific Com puting Applications , 2004 .

[21]  Himabindu Pucha,et al.  Cost Effective Storage using Extent Based Dynamic Tiering , 2011, FAST.

[22]  Ming Zhao,et al.  Write policies for host-side flash caches , 2013, FAST.

[23]  A. L. Narasimha Reddy,et al.  Exploiting superpages in a nonvolatile memory file system , 2012, 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST).

[24]  Steve Byan,et al.  Mercury: Host-side flash caching for the data center , 2012, 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST).

[25]  Eunji Lee,et al.  Unioning of the buffer cache and journaling layers with non-volatile memory , 2013, FAST.

[26]  Andrew W. Leung,et al.  Organizing, indexing, and searching large-scale file systems , 2009 .

[27]  Hong Jiang,et al.  A Novel Weighted-Graph-Based Grouping Algorithm for Metadata Prefetching , 2010, IEEE Transactions on Computers.

[28]  John Bent,et al.  Storage challenges at Los Alamos National Lab , 2012, 012 IEEE 28th Symposium on Mass Storage Systems and Technologies (MSST).

[29]  Robert Latham,et al.  Understanding and improving computational science storage access through continuous characterization , 2011, MSST.

[30]  Shankar Pasupathy,et al.  Measurement and Analysis of Large-Scale Network File System Workloads , 2008, USENIX Annual Technical Conference.

[31]  Dan Feng,et al.  Improving flash-based disk cache with Lazy Adaptive Replacement , 2013, 2013 IEEE 29th Symposium on Mass Storage Systems and Technologies (MSST).

[32]  Jongmoo Choi,et al.  Caching less for better performance: balancing cache size and update cost of flash memory cache in hybrid storage systems , 2012, FAST.

[33]  Brent Welch,et al.  Optimizing a hybrid SSD/HDD HPC storage system based on file size distributions , 2013, 2013 IEEE 29th Symposium on Mass Storage Systems and Technologies (MSST).

[34]  Feng Chen,et al.  Hystor: making the best use of solid state drives in high performance storage systems , 2011, ICS '11.

[35]  Raju Rangaswami,et al.  I/O Deduplication: Utilizing content similarity to improve I/O performance , 2010, TOS.