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DAReSch: deadline-aware request scheduling for cloud storage services

ANNALS OF TELECOMMUNICATIONS 2019年第9-10期74卷 545-557页

作者： Tlili, Ghada Yahyaoui, Haythem Zhani, Mohamed Faten Elbiaze, Halima Ecole Technol Super ETS Montreal Montreal PQ Canada Univ Quebec Montreal Montreal PQ Canada

With the emergence of cloud computing and big data, many companies are increasingly relying on the cloud to store and retrieve tremendous amounts of data to leverage the scalability and performance offered by cloud storage services. As a result, data retrieval time has become of a paramount importance for cloud users especially. However, current data management systems are still not optimized to reduce such time. In this paper, we present a deadline-aware data request scheduling scheme, called DAReSch, that aims at scheduling data requests in order to minimize data transfer times and to meet the deadlines specified by the users. We show through real experiments using openstack storage system (i.e., swift) that, compared with the traditional swift Client system, DAReSch significantly increases the percentage of requests meeting their deadlines, reduces data transfer time, and maximizes bandwidth usage. Furthermore, we also study the impact of the request deadlines on the studied performance metrics. Our extensive experiments show that, when deadlines are stringent, DAReSh allows 60% of the requests to meet their deadline requirements compared with only 10% for the existing solution. When the deadline is less stringent, 90% of the requests can meet their deadline requirements with DAReSh compared with 40% for the existing solution.

关键词： Cloud storage systems openstack swift Request scheduling Deadline-aware data retrieval

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Secure Processing-aware Media Storage and Archival (SPMSA)

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2024年 159卷 290-306页

作者： Noor, Jannatun Ratul, Rizwanul Hoque Basher, Md. Samiul Soumik, Jarif Ahmed Sadman, Sakib Rozario, Niloy Julious Reaz, Rezwana Chellappan, Sriram Islam, A. B. M. Alim Al Bangladesh Univ Engn & Technol Dept CSE Next Generat Comp NeC Res Grp Dhaka Bangladesh BRAC Univ Sch Data & Sci Dept Comp Sci & Engn Comp Sustainabil & Social Good C2SG Res Grp Dhaka Bangladesh BRAC Univ Dept Comp Sci & Engn Dhaka Bangladesh Bangladesh Univ Engn & Technol Dept Comp Sci & Engn Dhaka Bangladesh Univ S Florida Dept Comp Sci & Engn Tampa FL USA

The demand for a robust as well as a highly -available surveillance system with efficient media sharing capability has considerably risen in recent times. In this regard, CCTV offers a well -accepted pervasive solution all over the globe. Here, individuals and industries generally face challenges in storing CCTV video footage in their local machines. Besides, an alternative solution of long-time archiving of large -size video footage in the cloud is also challenging due to the associated steep rise in requirements of bandwidth, computing, and storage requirements. To face these challenges, in this paper, we propose a new methodology to utilize openstack swift's object storage to efficiently store and archive media data. Our method leverages expanding the cloud file -sharing capabilities from storing media files to processing and archiving them along with performing encryption. Our proposed approach first segments encodes, and transcodes the videos according to several resolutions for covering diversified remote devices. Then, we store the processed video footage in the storage server of openstack swift. Afterward, we perform necessary media encryption-decryption, compress the files containing the video data, and archive them using an archive server. We perform all these tasks in our proposed architectural model by developing several new middleware services in openstack swift. As a whole, we build a new storage system architecture where we can efficiently as well as securely store and share large video surveillance data, and later we can find and retrieve that data even after a few years. We carry out rigorous experiments over a real setup comprising machines deployed in two different countries (Canada and Bangladesh), located over two different continents, to validate the efficacy and efficiency of our proposed architecture and methodology. Experimental results demonstrate substantial performance improvement using our approach over conventional alternative solutions

关键词： Media cloud openstack swift PJPEG Middleware Image resizing Encryption Video surveillance system Fault tolerance

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Is cloud storage ready? Performance comparison of representative IP-based storage systems

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JOURNAL OF SYSTEMS AND SOFTWARE 2018年 138卷 206-221页

作者： Ou, Zhonghong Song, Meina Hwang, Zhen-Huan Yla-Jaaski, Antti Wang, Ren Cui, Yong Hui, Pan Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China Amadeus SAS Valbonne France Aalto Univ Dept Comp Sci Espoo Finland Intel Labs Pittsburgh PA USA Tsinghua Univ Beijing Peoples R China Hong Kong Univ Sci & Technol Hong Kong Hong Kong Peoples R China

Network based storage systems have traditionally been dominated by Network Attached Storage (NAS) and Storage Area Network (SAN). Cloud based storage systems, including object storage, have gained growing popularity among both private and enterprise users in recent years. Certain enterprises have even considered replacing traditional storage systems with cloud-based systems. Nevertheless, there still lacks a systematic comparative study on the performance of the aforementioned systems to assist such a transition. To fill in this gap, in this paper, we conduct a comprehensive study on the three major network storage systems with realistic network conditions and application behaviours. Specifically, we select one representative from each category for comparison, i.e., Network File System (NFS) from NAS, Internet Small Computer System Interface (iSCSI) from SAN, and openstack swift from cloud storage. As the first study of its kind, we mainly focus on the client-side and take performance as the perspective for comparison. We build a testbed and a suite of micro-benchmarks to study the impact of network complexities and access behaviours on performance. In addition, we employ two widely used macro benchmarks - PostMark and FileBench - to test the three systems under realistic workloads. Through a set of comprehensive experiments and thorough analysis, we make several key observations. (1) iSCSI excels under good network conditions, e.g., in local area networks (LANs);when network complexities like network delay and packet loss exist, its performance degrades significantly, especially for data-intensive operations. (2) For Internet-like environments, NFS performs poorly, while swift demonstrates much resilience. (3) Overall, swift is a viable replacement for NFS in all network scenarios, while it is not ready yet to replace iSCSI for performance-critical environments. (4) System configuration on the client side impacts storage performance significantly and deserves adequ

关键词： Cloud storage NAS SAN iSCSI NFS openstack swift

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Performance Analysis and Framework Optimization of Open Source Cloud Storage System

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China Communications 2016年第6期13卷 110-122页

作者： Lei Li Dagang Li Zhiliang Su Lianwen Jin Ganbo Huang School of Electronic and Information Engineering South China University of Technology University at Buffalo State University of New York 21CN Co. Ltd.

More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is very important for Internet development. This paper presents the performance evaluation of the open source distributed storage system, a highly available, distributed, eventually consistent object/blob store from Open Stack cloud computing components. This paper mainly focuses on the mechanism of cloud storage as well as the optimization methods to process different sized files. This work provides two major contributions through comprehensive performance evaluations. First, it provides different configurations for Open Stack swift system and an analysis of how every component affects the performance. Second, it presents the detailed optimization methods to improve the performance in processing different sized files. The experimental results show that our method improves the performance and the structure. We give the methods to optimize the object-based cloud storage system to deploy the readily available storage system.

关键词： Cloud Computing openstack swift Object Storage Distribute System Storage Service Optimization

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Revised cloud storage structure for light-weight data archiving in LHD

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FUSION ENGINEERING AND DESIGN 2014年第5期89卷 707-711页

作者： Hideya, Nakanishi Masaki, Ohsuna Mamoru, Kojima Setsuo, Imazu Miki, Nonomura Masahiko, Emoto Takashi, Yamamoto Yoshio, Nagayama Takahisa, Ozeki Noriyoshi, Nakajima Katsumi, Ida Osamu, Kaneko Natl Inst Nat Sci Natl Inst Fus Sci Toki Gifu 5095292 Japan Japan Atom Energy Agcy Naka Ibaraki 3110193 Japan

The LHD data archiving system has newly selected GlusterFS distributed filesystem for the replacement of the present cloud storage software named "IznaStor/dSS". Even though the prior software provided many favorable functionalities of hot plug and play node insertion, internal auto-replication of data files, and symmetric load balancing between all member nodes, it revealed a poor feature in recovering from an accidental malfunction of a storage node. Once a failure happened, the recovering process usually took at least several days or sometimes more than a week with a heavy cpu load. In some cases they fell into the so-called "split-brain" or "amnesia" condition, not to get recovered from it. Since the recovery time tightly depends on the capacity size of the fault node, individual HDD management is more desirable than large volumes of HDD arrays. In addition, the dynamic mutual awareness of data location information may be removed if some other static data distribution method can be applied. In this study, the candidate middleware of "openstack/swift" and "GlusterFS" has been tested by using the real mass of LHD data for more than half a year, and finally GlusterFS has been selected to replace the present IznaStor. It has implemented very limited functionalities of cloud storage but a simplified RAID10-like structure, which may consequently provide lighter-weight read/write ability. Since the LABCOM data system is implemented to be independent of the storage structure, it is easy to plug off the IznaStor and on the new GlusterFS. The effective I/O speed is also confirmed to be on the same level as the estimated one from raw performance of disk hardware. This achievement maybe informative to implement the ITER CODAC and the remote archiving system. (C) 2014 Elsevier B.V. All rights reserved.

关键词： LHD Data archiving GlusterFS openstack swift IznaStor LABCOM system

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Data-Driven Serverless Functions for Object Storage 17

Data-Driven Serverless Functions for Object Storage

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18th ACM/IFIP/USENIX International Middleware Conference (Middleware)

作者： Sampe, Josep Sanchez-Artigas, Marc Garcia-Lopez, Pedro Paris, Gerard Univ Rovira & Virgili Tarragona Spain

ISBN: (纸本)9781450347204

Traditionally, active storage techniques have been proposed to move computation tasks to storage nodes in order to exploit data locality. However, we argue in this paper that active storage is ill-suited for cloud storage for two reasons: 1. Lack of elasticity: Computing can only scale out with the number of storage nodes;and 2. Resource Contention: Sharing compute resources can produce interferences in the storage system. Serverless computing is now emerging as a promising alternative for ensuring painless scalability, and also, for simplifying the development of disaggregated computing tasks. Here we present an innovative data-driven serverless computing middleware for object storage. It is a lightweight compute solution that allows users to create small, stateless functions that intercept and operate on data flows in a scalable manner without the need to manage a server or a runtime environment. We demonstrate through different use cases how our solution scales with minimal overhead, while getting rid of the resource contention problems incurred by active storage tasks.

关键词： serverless functions object storage programmability data flow interception openstack swift cloud computing data management

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Vertigo: Programmable Micro-controllers for Software-Defined Object Storage 9

Vertigo: Programmable Micro-controllers for Software-Defined...

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9th IEEE International Conference on Cloud Computing (CLOUD)

作者： Sampe, Josep Garcia-Lopez, Pedro Sanchez-Artigas, Marc Univ Rovira & Virgili Dept Comp Engn & Math Tarragona Spain

ISBN: (纸本)9781509026197

Software-defined storage (SDS) aims to minimize the complexity of data management in the Cloud. SDS decouples the control plane from the data plane and simplifies the management of the storage system via automated storage policy enforcement. In this paper, we propose a novel SDS framework for Object Storage that allows to decentralize policy enforcement through the deployment of per-object management policies in the storage nodes. As in active storage systems, we leverage the underutilized CPU time in the storage nodes. But our framework goes one step further. It provides a new management abstraction called microcontrollers which operate on objects depending on their state and content, thereby permitting the implementation of sophisticated management policies, such as the automated deletion of an object based on its access history, and even allowing the orchestration of active storage tasks. Our SDS system avoids the massive interception of data flows by moving that logic to the appropriate objects. Furthermore, our extensible model simplifies the customization of Object Storage services. We present in the validation several interesting use cases such as automated deletion, content level access control, and Web prefetching.

关键词： Object Storage Software-defined Storage openstack swift Active Storage

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Performance Analyzing System Based on Visualization of Packet Transfers and Method Calls on Object Storage System 15

Performance Analyzing System Based on Visualization of Packe...

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15th International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Nakagami, Makoto Hayakawa, Shunpei Yamaguchi, Saneyasu Kogakuin Univ Elect Engn & Elect Grad Sch Tokyo Japan Kogakuin Univ Dept Informat & Commun Engn Tokyo Japan

ISBN: (纸本)9781665423182

Object storage systems are widely used for unstructured data such as video data and music data. As these data are increasing its amount, the performance improvement of these object storage systems is increasing their importance. However, understanding their behaviors and finding the bottleneck process in them are difficult because these are distributed systems composed of multiple server computers. In this paper, we evaluate the file uploading performance of the swift, which is a popular object storage implementation, and show that each uploading takes a long time in some cases. We then propose an analyzing system that visualizes packet transmissions and method calls. The analyzing system identifies the reasons why uploading takes a long time. For evaluating the proposed system, we apply this analyzing method to the swift and reveal that a process in the Identity Server takes a long time and a hashing function $bcrypt$ is the bottleneck process. Finally, we present a discussion on performance importance based on this analyzing result.

关键词： Object Storage openstack swift Cloud Computing

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A Construction Method and Data Migration Strategy for Hybrid Cloud Storage 18

A Construction Method and Data Migration Strategy for Hybrid...

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18th International Conference on Computer and Information Technology (ICCIT)

作者： Duan, Zhiying Cao, Yizhen Song, Mingli Commun Univ China Sch Comp Beijing Peoples R China

ISBN: (纸本)9781467399302

With more and more enterprises constructed their own private cloud storage platforms, certain limitations and challenges come for small and medium enterprises. So hybrid cloud storage is imperative with public cloud as a complement. In this paper, we propose a fast and efficient method to build a hybrid cloud storage framework: base on open source software openstack swift to build the private cloud storage, use Baidu Object Storage as the public cloud provider, and do a second development of Cyberduck as the cloud storage client. This framework can realize the seamless integration of private and public cloud. To tackle the data migration problem in hybrid cloud storage, we present a part-migration-part-retention self-adaptive periodic migration strategy, and the specific implementation of migration process is given. The strategy not only improve the utilization rate of local cloud storage, but also make reasonable use of public cloud storage.

关键词： hybrid cloud cloud storage openstack swift BOS Cyberduck Self-Adaptive Data Migration

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Revised cloud storage structure for light-weight data archiving in LHD

Revised cloud storage structure for light-weight data archiv...

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9th IAEA Technical Meeting on Control, Data Acquisition and Remote Participation for Fusion Research

关键词： LHD Data archiving GlusterFS openstack swift IznaStor LABCOM system

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