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2nd International Conference on Computer Science and Applications (CSA)

作者： Huo, Lin Yi, Ran Guangxi Univ Coll Comp & Elect Informat Nanning 530000 Peoples R China

ISBN: (纸本)9781479999613

Traditional distributed file system in availability, scalability, and data access performance has been difficult to meet the growing demand for data storage. This paper proposes a Metadata Server (MDS) Cluster scheme based on two-server high availability. On this basis, use a combination of a directory subtree partitioning and improved consistency hash algorithm divides the metadata, ensure the cluster load balancing and adapted to the change of the size of the cluster. For the load imbalance caused by the difference of data access during operation, propose a dynamic load balancing algorithm to adjust the load balance of cluster. Finally, the experimental results show that the scheme has good effect on the availability, access performance, load balance.

关键词： distributed file system metadata Consistent hash load balancing

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Personalized User Profiles-based Insider Threat Detection for distributed file system 21

Personalized User Profiles-based Insider Threat Detection fo...

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21st IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom)

作者： Xin, Wu Shen, Qingni Feng, Ke Xia, Yutang Wu, Zhonghai Lin, Zhenghao Peking Univ Acad Adv Interdisciplinary Studies Ctr Data Sci Beijing Peoples R China Peking Univ Sch Software & Microelect Beijing Peoples R China Peking Univ Sch Econ Beijing Peoples R China Boston Univ Questrom Sch Business Coll Arts & Sci Boston MA 02215 USA

ISBN: (纸本)9781665494250

In recent years, data security incidents caused by insider threats in distributed file systems have attracted the attention of academia and industry. The most common way to detect insider threats is based on user profiles. Through analysis, we realize that based on existing user profiles are not efficient enough, and there are many false positives when a stable user profile has not yet been formed. In this work, we propose personalized user profiles and design an insider threat detection framework, which can intelligently detect insider threats for securing distributed file systems in real-time. To generate personalized user profiles, we come up with a time window-based clustering algorithm and a weighted kernel density estimation algorithm. Compared with non-personalized user profiles, both the Recall and Precision of insider threat detection based on personalized user profiles have been improved, resulting in their harmonic mean F1 increased to 96.52%. Meanwhile, to reduce the false positives of insider threat detection, we put forward operation recommendations based on user similarity to predict new operations that users will produce in the future, which can reduce the false positive rate (FPR). The FPR is reduced to 1.54% and the false positive identification rate (FPIR) is as high as 92.62%. Furthermore, to mitigate the risks caused by inaccurate authorization for users, we present user tags based on operation content and permission. The experimental results show that our proposed framework can detect insider threats more effectively and precisely, with lower FPR and high FPIR.

关键词： Data Security Insider Threat Detection User Profile Machine Learning distributed file system HDFS

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Towards Building a distributed file system for Remote Sensing Image Process

Towards Building a Distributed File System for Remote Sensin...

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IEEE International Conference on Big Data Analysis (ICBDA)

作者： Li, Zhenju Li, Xuejun Liu, Tao Xie, Jianwei PLA Equipment Acad Beijing Peoples R China

ISBN: (纸本)9781467395915

Remote sensing image processing is a part of the digital photogrammetric system, and data management is very important in this system. The aim of this paper was to build a distributed file system for massive remote sensing image management in the processing. The proposed distributed file system, RSI-DFS, has a flexible namespace mechanism, takes normal file as data model, takes TCP as data transfer model. Experiments indicates that the proposed distributed file system has a stable read and write performance compared with the existing systems.

关键词： data management remote sensing image distributed file system digital photogrammetric system

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Wharf: Sharing Docker Images in a distributed file system

Wharf: Sharing Docker Images in a Distributed File System

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ACM Symposium on Cloud Computing (SoCC)

作者： Zheng, Chao Rupprecht, Lukas Tarasov, Vasily Thain, Douglas Mohamed, Mohamed Skourtis, Dimitrios Warke, Amit S. Hildebrand, Dean Univ Notre Dame Notre Dame IN 46556 USA IBM Res Almaden San Jose CA USA Google Mountain View CA USA

ISBN: (纸本)9781450360111

Container management frameworks, such as Docker, package diverse applications and their complex dependencies in self-contained images, which facilitates application deployment, distribution, and sharing. Currently, Docker employs a shared-nothing storage architecture, i.e. every Docker-enabled host requires its own copy of an image on local storage to create and run containers. This greatly inflates storage utilization, network load, and job completion times in the cluster. In this paper, we investigate the option of storing container images in and serving them from a distributed file system. By sharing images in a distributed storage layer, storage utilization can be reduced and redundant image retrievals from a Docker registry become unnecessary. We introduce Wharf, a middleware to transparently add distributed storage support to Docker. Wharf partitions Docker's runtime state into local and global parts and efficiently synchronizes accesses to the global state. By exploiting the layered structure of Docker images, Wharf minimizes the synchronization overhead. Our experiments show that compared to Docker on local storage, Wharf can speed up image retrievals by up to 12x, has more stable performance, and introduces only a minor overhead when accessing data on distributed storage.

关键词： Container Docker distributed file system

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MDFS: A Mimic Defense Theory based Architecture for distributed file system 5

MDFS: A Mimic Defense Theory based Architecture for Distribu...

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IEEE International Conference on Big Data (IEEE Big Data)

作者： Lin, Zhili Li, Kedan Hou, Hanxu Yang, Xin Li, Hui Peking Univ Shenzhen Key Lab Informat Theory & Future Interne Shenzhen Grad SchPKU Inst Big Data TechnolFutur Shenzhen Engn Lab Converged Networking TechnolHu Shenzhen Peoples R China UIUC Dept Comp Sci Champaign IL USA Dongguan Univ Technol Sch Elect Engn & Intelligentizat Dongguan Peoples R China

ISBN: (纸本)9781538627150

As the Internet and the big data system evolve rapidly, the deployment of distributed applications becomes widespread, promoting the development of distributed file system (DFS). The existing defense technologies for DFS, such as detection or patching, mainly aim to protect the system from known attacks and vulnerabilities. However, it is difficult for those systems to solve the growing security issues from the unknown threats due to their passiveness and hysteresis. In this paper, we propose MDFS, a mimic defense theory based architecture for DFS with the capability to improve the data security. Mimic Defense (MD), a proactive defense embedded in MDFS, emphasizes dynamism, heterogeneity and redundancy. The key benefits of MD are transferring the attack surface as well as increasing the cost of modification.

关键词： distributed file system data security mimic defense dynamic heterogeneity redundancy

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CFS: Scaling Metadata Service for distributed file system via Pruned Scope of Critical Sections 23

CFS: Scaling Metadata Service for Distributed File System vi...

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18th European Conference on Computer systems (EuroSys)

作者： Wang, Yiduo Wu, Yufei Li, Cheng Zheng, Pengfei Cao, Biao Sun, Yan Zhou, Fei Xu, Yinlong Wang, Yao Xie, Guangjun Univ Sci & Technol China Hefei Peoples R China Baidu China Co Ltd Beijing Peoples R China Anhui Prov Key Lab High Performance Comp Hefei Peoples R China

ISBN: (纸本)9781450394871

There is a fundamental tension between metadata scalability and POSIX semantics within distributed file systems. The bottleneck lies in the coordination, mainly locking, used for ensuring strong metadata consistency, namely, atomicity and isolation. CFS is a scalable, fully POSIX-compliant distributed file system that eliminates the metadata management bottleneck via pruning the scope of critical sections for reduced locking overhead. First, CFS adopts a tiered metadata organization to scale file attributes and the remaining namespace hierarchies independently with appropriate partitioning and indexing methods, eliminating cross-shard distributed coordination. Second, it further scales up the single metadata shard performance by single-shard atomic primitives, shortening the metadata requests' lifespan and removing spurious conflicts. Third, CFS drops the metadata proxy layer but employs the light-weight, scalable client-side metadata resolving. CFS has been running in the production environment of Baidu AI Cloud for three years. Our evaluation with a 50-node cluster and microbenchmarks shows that CFS simultaneously improves the throughput of baselines like HopsFS and InfiniFS by 1.76-75.82x and 1.22-4.10x, and reduces their average latency by up to 91.71% and 54.54%, respectively. Under cases with higher contention and larger directories, CFS' throughput benefits expand by one order of magnitude. For three real-world workloads with data accesses, CFS introduces 1.62-2.55x end-to-end throughput speedups and 35.06-62.47% tail latency reductions over InfiniFS.

关键词： distributed file system Metadata management

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Challenges and Solutions for distributed file system 2

Challenges and Solutions for Distributed File System

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Gupta, Richa Gupta, Amit Bhatla, Shruti Tripathi, Vikas Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350371055

A distributed file system (DFS) is a file system that allows multiple users to access and share files and data across a network. In a DFS, files are stored on multiple servers, and users can access them from any location on the network as if they were stored on their local computer. DFS provides a way to organize and manage files and folders across multiple servers in a unified way, making it easier for users to access and share data without worrying about the physical location of the files. This can help to improve data availability, reliability, and scalability in a networked environment. DFS also provides a way to replicate data across multiple servers for redundancy and fault tolerance, so that if one server fails, the data can still be accessed from other servers. Some examples of popular distributed file systems include Hadoop distributed file system (HDFS), Google file system (GFS), and Windows distributed file system (DFS). LCCFS (light weight cloud computing file system) which help to reduce the overhead and increase the performance of the distributed system RADOS (Reliable autonomic distributed object storage) which utilized for implementing distributed file system for cloud computing Pangea is a new system which allow different units to combine into a single unit and PLSF (Virtual Parallel log structured file system) which pick up the performance by improving the bandwidth are some new terminologies introduced by some previous research are discussed in this research. © 2024 IEEE.

关键词： Ceph Cloud file system distributed file system Gluster HDFS

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Self Stabilizing distributed file system

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2000年

Description: Shlomi Dolev and Ronen I. Kat Department of Computer Science, Ben-Gurion University of the Negev fdolev,katg@*** Abstract A self-stabilizing distributed file system is presented. The system constructs and maintains a spanning tree for each file volume. The spanning tree consists of the servers that have volume replicas and caches for the specific file volume. The spanning trees are constructed and maintained by selfstabilizing distributed algorithms. file system updates use

关键词： distributed file system programming storage

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GMount: An Ad Hoc and Locality-Aware distributed file system by using SSH and FUSE 09

GMount: An Ad Hoc and Locality-Aware Distributed File System...

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9th IEEE/ACM International Symposium on Cluster Computing and the Grid

作者： Dun, Nan Taura, Kenjiro Yonezawa, Akinori Univ Tokyo Grad Sch Informat Sci & Technol Bunkyo Ku Tokyo Japan

ISBN: (纸本)9781424439355

Developing and deploying distributed file system has been important for the Grid computing. By GMount, non-privileged users can instantaneously and effortlessly build a distributed file system on arbitrary machines that are reachable via SSH. It is scalable to hundreds of nodes in the wide-area Grid environments and adapts to NAT/Firewall. Unlike conventional distributed file systems, GMount can directly harness local file systems of each node without importing/exporting application data and utilize the network topology to make the metadata operations locality-aware. In this paper we present the design and implementation of GMount by using two popular modules: SSH and FUSE. We demonstrate its viability, and locality-aware metadata operation performance in a large scale Grid with over 32 nodes spreading across 12 clusters that are connected by heterogeneous wide-area links.

关键词： distributed file system

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An adaptive dynamic feedback load balancing algorithm based on QoS in distributed file system

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Journal of Communications and Information Networks 2017年第3期2卷 30-40页

作者： Ming Wang Jianfeng Guan Beijing University of Posts and Telecommunications Beijing 100876China

An adaptive dynamic load balancing algorithm based on QoS is proposed to improve the performance of load balancing in distributed file system,combining the advantages of a variety of load balancing *** new algorithm uses a tuple containing the number of files and the total file size as the QoS measure for the requested *** master node sets a threshold for the requested task based on the QoS to filter storage nodes that meet the requirements of the *** order to guarantee the reliability of the new algorithm,we consider the impact of CPU utilization,memory usage,disk IO occupancy rate,network bandwidth usage and hard disk usage on load balancing performance when calculating the real-time load balancing of storage *** heterogeneity of the network is considered when the master node schedule task assignments to ensure the fairness of the *** comprehensive evaluation value is determined based the performance load ratio,which is calculated from the real-time load value of the storage node and a performance value after *** master node assigns tasks to the storage node with the highest comprehensive evaluation *** storage nodes provide adaptive feedback based on changes in the degree of connectivity,rather than periodic update of the load *** actual distributed file system environment is set up on the server cluster,the performance of the new algorithm is tested through a contrast *** experimental results show that the new algorithm can effectively reduce the average response time of the system,improve throughput,and enable the system load to reach a good balance.

关键词： distributed file system load balancing QoS performance load ratio adaptive dynamic feedback

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