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Prefetch-aware fingerprint cache management for data deduplication systems

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Frontiers of Computer Science 2019年第3期13卷 500-515页

作者： Mei LI Hongjun ZHANG Yanjun WU Chen ZHAO Institute of Software Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

Data deduplication has been widely utilized in large-scale storage systems, particularly backup systems. Data deduplication systems typically divide data streams into chunks and identify redundant chunks by comparing chunk fingerprints. Maintaining all fingerprints in memory is not cost-effective because fingerprint indexes are typically very large. Many data deduplication systems maintain a fingerprint cache in memory and exploit fingerprint prefetching to accelerate the deduplication process. Although fingerprint prefetching can improve the performance of data deduplication systems by leveraging the locality of workloads, inaccurately prefetched fingerprints may pollute the cache by evicting useful fingerprints. We observed that most of the prefetched fingerprints in a wide variety of applications are never used or used only once, which severely limits the performance of data deduplication systems. We introduce a prefetch-aware fingerprint cache management scheme for data deduplication systems (PreCache) to alleviate prefetch-related cache pollution. We propose three prefetch-aware fingerprint cache replacement policies (PreCache-UNU, PreCache-UOO, and PreCache-MIX) to handle different types of cache pollution. Additionally, we propose an adaptive policy selector to select suitable policies for prefetch requests. We implement PreCache on two representative data deduplication systems (Block Locality Caching and SiLo) and evaluate its performance utilizing three real-world workloads (Kernel, MacOS, and Homes). The experimental results reveal that PreCache improves deduplication throughput by up to 32.22% based on a reduction of on-disk fingerprint index lookups and improvement of the deduplication ratio by mitigating prefetch-related fingerprint cache pollution.

关键词： data deduplication fingerprint prefetch fingerprint cache

A Lookahead Read Cache： Improving Read Performance for deduplication Backup Storage

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Journal of Computer Science & Technology 2017年第1期32卷 26-40页

作者： Dongchul Park Ziqi Fan Young Jin Nam David H. C. Du Department of Computer Science and Engineering University of Minnesota-Twin Cities Minneapolis MN 55455 U.S.A.

Data deduplication （dedupe for short） is a special data compression technique. It has been widely adopted to save backup time as well as storage space, particularly in backup storage systems. Therefore, most dedupe research has primarily focused on improving dedupe write performance. However, backup storage dedupe read performance is also a crucial problem for storage recovery. This paper designs a new dedupe storage read cache for backup applications that improves read performance by exploiting a special characteristic： the read sequence is the same as the write sequence. Consequently, for better cache utilization, by looking ahead for future references within a moving window, it evicts victims from the cache having the smallest future access. Moreover~ to further improve read cache performance. it maintains a small log buffer to judiciously cache future access data chunks. Extensive experiments with real-world backup workloads demonstrate that the proposed read cache scheme improves read performance by up to 64.3%

关键词： deduplication dedupe read cache backup

Leach： an automatic learning cache for inline primary deduplication system

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Frontiers of Computer Science 2014年第2期8卷 175-183页

作者： Bin LIN Shanshan LI Xiangke LIAO Jing ZHANG Xiaodong LIU School of Computer National University of Defense Technology Changsha 410073 China

deduplication technology has been increasingly used to reduce storage costs. Though it has been successfully applied to backup and archival systems, existing techniques can hardly be deployed in primary storage systems due to the associated latency cost of detecting duplicated data, where every unit has to be checked against a substantially large fin- gerprint index before it is written. In this paper we introduce Leach, for inline primary storage, a self-learning in-memory fingerprints cache to reduce the writing cost in deduplica- tion system. Leach is motivated by the characteristics of real- world I/O workloads： highly data skew exist in the access patterns of duplicated data. Leach adopts a splay tree to or- ganize the on-disk fingerprint index, automatically learns the access patterns and maintains hot working sets in cache mem- ory, with a goal to service a majority of duplicated data de- tection. Leveraging the working set property, Leach provides optimization to reduce the cost of splay operations on the fin- gerprint index and cache updates. In comprehensive experi- ments on several real-world datasets, Leach outperforms con- ventional LRU （least recently used） cache policy by reducing the number of cache misses, and significantly improves write performance without great impact to cache hits.

关键词： deduplication duplicate detection splay tree,cache

Updatable block-level deduplication of encrypted data with efficient auditing in cloud storage

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The Journal of China Universities of Posts and Telecommunications 2019年第3期26卷 56-72页

作者： Dang Qianlong Xie Ying Li Donghao Hu Gongcheng School of Mathematics and Statistics Xidian University Xi'an 710071 China School of Natural and Applied Sciences Henan University of Technology Zhengzhou 450001 China

Updatable block-level message-locked encryption(MLE) can efficiently update encrypted data, and public auditing can verify the integrity of cloud storage data by utilizing a third party auditor(TPA). However, there are seldom schemes supporting both updatable block-level deduplication and public auditing. In this paper, an updatable block-level deduplication scheme with efficient auditing is proposed based on a tree-based authenticated structure. In the proposed scheme, the cloud server(CS) can perform block-level deduplication, and the TPA achieves integrity auditing tasks. When a data block is updated, the ciphertext and auditing tags could be updated efficiently. The security analysis demonstrates that the proposed scheme can achieve privacy under chosen distribution attacks in secure deduplication and resist uncheatable chosen distribution attacks(UNC-CDA) in proof of ownership(PoW). Furthermore, the integrity auditing process is proven secure under adaptive chosen-message attacks. Compared with previous relevant schemes, the proposed scheme achieves better functionality and higher efficiency.

关键词： data update operation block-level deduplication efficient auditing tree-based authenticated structure proof of ownership

Secured Data Storage Using deduplication in Cloud Computing Based on Elliptic Curve Cryptography

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Computer Systems Science & Engineering 2022年第4期41卷 83-94页

作者： N.Niyaz Ahamed N.Duraipandian Department of Computer Science and Engineering Velammal Engineering CollegeChennai600066India

The tremendous development of cloud computing with related technol-ogies is an unexpected ***,centralized cloud storage faces few chal-lenges such as latency,storage,and packet drop in the *** storage gets more attention due to its huge data storage and ensures the security of secret *** of the developments in cloud storage have been positive except better cost model and effectiveness,but still data leakage in security are billion-dollar questions to *** data security techniques are usually based on cryptographic methods,but these approaches may not be able to with-stand an attack from the cloud server's ***,we suggest a model called multi-layer storage(MLS)based on security using elliptical curve cryptography(ECC).The suggested model focuses on the signiﬁcance of cloud storage along with data protection and removing duplicates at the initial *** on divide and combine methodologies,the data are divided into three ***,theﬁrst two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding *** other part of the encrypted data is saved in the *** viability of our model has been tested by research in terms of safety measures and test evaluation,and it is truly a powerful comple-ment to existing methods in cloud storage.

关键词： Cloud storage deduplication fog computing and elliptic curve cryptography

Hash-Indexing Block-Based deduplication Algorithm for Reducing Storage in the Cloud

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Computer Systems Science & Engineering 2023年第7期46卷 27-42页

作者： D.Viji S.Revathy Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennaiIndia

Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage *** potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data *** creates a complex nature to increase the storage consumption under *** resolve this problem,this paper proposes an efficient storage reduction called Hash-Indexing Block-based deduplication(HIBD)based on Segmented Bind Linkage(SBL)Methods for reducing storage in a cloud ***,preprocessing is done using the sparse augmentation ***,the preprocessed files are segmented into blocks to make *** block of the contents is compared with other files through Semantic Content Source deduplication(SCSD),which identifies the similar content presence between the *** on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a ***,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match *** implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage.

关键词： Cloud computing deduplication hash indexing relational content analysis document clustering cloud storage record linkage

Health Data deduplication Using Window Chunking-Signature Encryption in Cloud

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Intelligent Automation & Soft Computing 2023年第4期36卷 1079-1093页

作者： G.Neelamegam P.Marikkannu Department of Computer Science and Engineering Anna University Regional Campus CoimbatoreCoimbatore641046India

Due to the development of technology in medicine,millions of health-related data such as scanning the images are *** is a great challenge to store the data and handle a massive volume of *** data is stored in the cloud-fog storage *** cloud-Fog based health model allows the users to get health-related data from different sources,and duplicated informa-tion is also available in the ***,it requires an additional sto-rage area,increase in data acquisition time,and insecure data replication in the *** paper is proposed to eliminate the de-duplication data using a window size chunking algorithm with a biased sampling-based bloomﬁlter and provide the health data security using the Advanced Signature-Based Encryp-tion(ASE)algorithm in the Fog-Cloud Environment(WCA-BF+ASE).This WCA-BF+ASE eliminates the duplicate copy of the data and minimizes its sto-rage space and maintenance *** data is also stored in an efﬁcient and in a highly secured *** security level in the cloud storage environment Win-dows Chunking Algorithm(WSCA)has got 86.5%,two thresholds two divisors(TTTD)80%,Ordinal in Python(ORD)84.4%,Boom Filter(BF)82%,and the proposed work has got better security storage of 97%.And also,after applying the de-duplication process,the proposed method WCA-BF+ASE has required only less storage space for variousﬁle sizes of 10 KB for 200,400 MB has taken only 22 KB,and 600 MB has required 35 KB,800 MB has consumed only 38 KB,1000 MB has taken 40 KB of storage spaces.

关键词： Health data encryption chunks cloud fog deduplication bloomﬁlter Algorithm 3:Generation of Key

dCACH: Content Aware Clustered and Hierarchical Distributed deduplication

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Journal of Software Engineering and Applications 2019年第11期12卷 460-490页

作者： Girum Dagnaw Ke Zhou Hua Wang Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Wuhan China

In deduplication, index-lookup disk bottleneck is a major obstacle which limits the throughput of backup processes. One way to minimize the effect of this issue and boost speed is to use very high course-grained chunks for deduplication at a cost of low storage saving and limited scalability. Another way is to distribute the deduplication process among multiple nodes but this approach introduces storage node island effect and also incurs high communication cost. In this paper, we explore dCACH, a content-aware clustered and hierarchical deduplication system, which implements a hybrid of inline course grained and offline fine-grained distributed deduplication where routing decisions are made for a set of files instead of single files. It utilizes bloom filters for detecting similarity between a data stream and previous data streams and performs stateful routing which solves the storage node island problem. Moreover, it exploits the negligibly small amount of content shared among chunks from different file types to create groups of files and deduplicate each group in their own fingerprint index space. It implements hierarchical deduplication to reduce the size of fingerprint indexes at the global level, where only files and big sized segments are deduplicated. Locality is created and exploited first using the big sized segments deduplicated at the global level and second by routing a set of consecutive files together to one storage node. Furthermore, the use of bloom filter for similarity detection between streams has low communication and computation cost while it enables to achieve duplicate elimination performance comparable to single node deduplication. dCACH is evaluated using a prototype deployed on a server environment distributed over four separate machines. It is shown to have 10× the speed of Extreme_Binn with a minimal communication overhead, while its duplicate elimination effectiveness is on a par with a single node deduplication system.

关键词： Clustered deduplication Content Aware Grouping Hierarchical deduplication Stateful Routing Similarity Bloom Filters

Differentially Authorized deduplication System Based on Blockchain

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ZTE Communications 2021年第2期19卷 67-76页

作者： ZHAO Tian LI Hui YANG Xin WANG Han ZENG Ming GUO Haisheng WANG Dezheng Shenzhen Graduate School Peking UniversityShenzhen 518055China ZTE Corporation Shenzhen 518057China

In architecture of cloud storage, the deduplication technology encrypted with theconvergent key is one of the important data compression technologies, which effectively improvesthe utilization of space and bandwidth. To further refine the usage scenarios for varioususer permissions and enhance user’s data security, we propose a blockchain-based differentialauthorized deduplication system. The proposed system optimizes the traditionalProof of Vote (PoV) consensus algorithm and simplifies the existing differential authorizationprocess to realize credible management and dynamic update of authority. Based on thedecentralized property of blockchain, we overcome the centralized single point fault problemof traditional differentially authorized deduplication system. Besides, the operations oflegitimate users are recorded in blocks to ensure the traceability of behaviors.

关键词： convergent key deduplication blockchain differential authorization