A High-Performance Storage System Based with Dual RAID Engine

With the advent of the 5G, more and more applications use cloud storage to store data. Data becomes the cornerstone of the development of smart society. At the same time, these data have the characteristics of uneven generation rate, large write demand and low read requirement. The dynamic change of load during data storage has new requirements for storage architecture. This paper proposes a storage system that allocates strips in real time based on current load changes. Based on the traditional RAID layout, a dual-engine based high-performance storage system (DSH) is proposed. This system uses software and hardware co-processing architecture to implement strip allocation and address calculation. The strip allocation functions using software and the verification algorithm is implemented by hardware transfer to the FPGA through PCIE. Through experimental analysis shows that the DSH algorithm has a great advantage in saving CPU computing resources and saving disk energy consumption in the dynamic load storage environment.

[1]  Mahmut T. Kandemir,et al.  DRPM: dynamic speed control for power management in server class disks , 2003, 30th Annual International Symposium on Computer Architecture, 2003. Proceedings..

[2]  Yuanyuan Zhou,et al.  Hibernator: helping disk arrays sleep through the winter , 2005, SOSP '05.

[3]  Luiz André Barroso,et al.  The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines , 2009, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines.

[4]  Samee U. Khan,et al.  Boafft: Distributed Deduplication for Big Data Storage in the Cloud , 2020, IEEE Transactions on Cloud Computing.

[5]  Garth A. Gibson,et al.  RAID: high-performance, reliable secondary storage , 1994, CSUR.

[6]  Jie Wu,et al.  Improving Restore Performance in Deduplication Systems via a Cost-Efficient Rewriting Scheme , 2019, IEEE Transactions on Parallel and Distributed Systems.

[7]  Ricardo Bianchini,et al.  Conserving disk energy in network servers , 2003, ICS '03.

[8]  Qing Yang,et al.  A Case for Continuous Data Protection at Block Level in Disk Array Storages , 2009, IEEE Transactions on Parallel and Distributed Systems.

[9]  Meng Xiaofeng and Ci Xiang,et al.  Big Data Management: Concepts,Techniques and Challenges , 2013 .