Relevant bibliographies by topics / Distributed Storage Server (DSS)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Distributed Storage Server (DSS)'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Distributed Storage Server (DSS)"

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Shubham, Pote1 Vipul Jain2 Rutuja Shinde3 Prasanna Paigude4 Prof.Deepali Ahir 5. "OPOR: PROOF OF RETRIEVABILITY IN CLOUD COMPUTING WITH RECOVERY AND REMOTE INTEGRITY CHECK." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 6 (2017): 58–65. https://doi.org/10.5281/zenodo.802818.

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Cloud computing is popular ,and adopted because there is many security and privacy. A issue found in cloud storage is, when client out-source data to the cloud storage, the clients don’t know that their data is damaged or not. Also the computational burden is too high. To tackle the issue, OPoR, another distributed storage method including a distributed storage server (DSS) and a TPA is proposed here. TPA is thought to be semi-legitimate. Specifically, we consider the assignment of permitting the TPA for the cloud clients, to pre-process the information before transferring to the DSS and later
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Wunarso, Novita Belinda, Andrias Rusli, Michelle Angelica, and Arabella Margaret Salim. "Implementasi Distributed File Server pada Apache Web Server." Jurnal ULTIMA InfoSys 4, no. 2 (2013): 84–88. http://dx.doi.org/10.31937/si.v4i2.245.

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In this research, a Distributed File Server (DFS) is developed to manage the need of a large storage space in the server, especially when the multimedia files are saved permanently in the web server. In the development, Apache Web Server is used with 1 computer as the main server, 2 computers as file servers, and 1 computer as the client who sends request. The result from the implementation of the DFS is the usage of main server’s storage space can be reduced by 99,77% from the full usage condition, causing an optimization in the web server. Another parameter is also being tested by the implem
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Al-Janabi, Sufyan T., Ali J. Dawood, and Abeer Dawood Salman. "Enhancing the Security and Privacy of WBAN-Based Distributed Storage Systems." Journal of University of Human Development 1, no. 2 (2015): 288. http://dx.doi.org/10.21928/juhd.v1n2y2015.pp288-294.

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The sensors of a Wireless Body Area Network (WBAN) that are spread inside and outside of a human body collect medical information and transfer it into the back-end server that is managed by the hospital or medical center; where the professionals analyze this data. This server is considered a very critical device because it has sensitive information. Therefore, the security and privacy of that server must be defended. Networked storage systems have become an efficient way to use in WBAN. It can be divided into two types: Centralized storage systems and Distributed Storage Systems (DSSs). Storin
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Akbar, Hawwin Purnama, Achmad Basuki, and Eko Setiawan. "Peningkatan Utilisasi Jaringan Distributed Storage System Menggunakan Kombinasi Server dan Link Load Balancing." Jurnal Teknologi Informasi dan Ilmu Komputer 8, no. 3 (2021): 525. http://dx.doi.org/10.25126/jtiik.2021834294.

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<p><em>Distributed Storage System </em>(DSS) memiliki sejumlah perangkat server penyimpanan yang terhubung dengan banyak perangkat <em>switch</em> untuk meningkatkan utilisasi jaringan. DSS harus memperhatikan keseimbangan beban pada sisi server penyimpanan dan trafik data pada semua jalur yang terhubung. Jika beban pada sisi server penyimpanan dan trafik data tidak seimbang, maka dapat menyebabkan <em>bottleneck network</em> yang menurunkan utilisasi jaringan. Kombinasi <em>server</em> dan <em>link</em> <em>load balancing
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Thilaganga, V., and S. Selvam. "A Prefetching Technique using Apriori and Logistic Methods for the DFS in Cloud." Asian Journal of Engineering and Applied Technology 6, no. 1 (2017): 10–13. http://dx.doi.org/10.51983/ajeat-2017.6.1.817.

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This paper presents an creativity data prefetching scheme on the loading servers in distributed file systems for cloud computing. The server will get and piggybacked the frequent data from the client system, after analyzing the fetched data is forward to the client machine from the server. To place this technique to work, the data about client nodes is piggybacked onto the real client I/O requests, and then forwarded to the relevant storage server. Next, dual prediction algorithms have been proposed to calculation future block access operations for directing what data should be fetched on stor
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R. Vigneshwaran, N. Mageshwaran, J. Akash, S. Kumaravel, and R. Mohana Santhiya. "ENABLING DATA STORAGE SECURITYWITH BLOCKCHAIN TECHNOLOGY." international journal of engineering technology and management sciences 9, no. 2 (2025): 26–35. https://doi.org/10.46647/jetms.2025.v09i02.006.

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There are multiple ways of keeping data by using a single or Distributed Database on thecloud, yet a single database client can keep data only on a single server, and if multiple clients try toaccess those at the same time with data consistency, the data may be altered at the time ofconcurrent data access. Handling data on a single database could be easy, but problems associatedwith data consistency, confidentiality, availability, and bottleneck/single point of failure are alwaysthere. To eliminate these problems, today the author uses the Distributed Database approach, inwhich data is stored
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Sumirat, Ucu, Antonius Setiawan, Sinka Wilyanti, and Rosyid Al-Hakim. "Analysis of Distributed File System Replication Using the NDLC Method with Hyper-V Virtual Simulation Machine." SaNa: Journal of Blockchain, NFTs and Metaverse Technology 1, no. 1 (2023): 10–22. http://dx.doi.org/10.58905/sana.v1i1.59.

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The need to access file sharing easily on an organization's computer network was increased. Users didn't have to worry about the number of file server addresses that can be accessed and are made with only one access address to use file sharing. The availability of data on the network to file storage availability in an organization was also essential. Data would be permanently lost, following a reason including hardware failure, or even accidentally deleted. It was important to ensure that there was a copy of the data. Achieving good data availability requires a system strategy built in the org
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Pawar, Ankush Balaram, Shashikant U. Ghumbre, and Rashmi M. Jogdand. "Advanced Cryptographic Standards-Based Secure Data Protocol for Distributed Data Storage and Communication in the Cloud." International Journal of Cloud Applications and Computing 12, no. 1 (2022): 1–16. http://dx.doi.org/10.4018/ijcac.297097.

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In this research, an ACS-based secure data protocol (ACS-based secure data protocol) is introduced for distributed data storage and communication in cloud. The component is constructed using the Owner’s Machine (OM), Data Processing Section (DPS), Cloud Monitoring Server (CMS), Metadata table, Key Management Server (KMS) and Receiver’s Machine (RM). The session key is generated by exchanging the data between the client and server using the mathematical operations, such as interpolation, hashing, Walsh transform and Elliptic curve cryptography. The Triple Data Encryption Algorithm (3DES) is use
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Athira, A. R., and P. Sasikala. "An Efficient Secure Data Deduplication and Portability In Distributed Cloud Server Using Whirlpool-Hct And Lf-Wdo." Electrical and Automation Engineering 1, no. 1 (2022): 28–32. http://dx.doi.org/10.46632/eae/1/1/5.

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Distributed Cloud Computing Storage has come up as a service that can expedite data owners (DO) to store their data remotely according to their application or data or file environment. However, insecure data storage, high uploading bandwidth, integration issues of DCS has breached the trustworthiness of the user to store data. In order to conquer the challenge, the work has developed a data Deduplication and portability-based secure data storage in DCS. The work aids to remove unwanted data and selects the most relevant features to avoid data loss by using GK-QDA Feature Reduction Method and H
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Shenbaga Bharatha Priya, A., J. Ganesh, and Mareeswari M. Devi. "Dynamic Load Rebalancing Algorithm for Private Cloud." Applied Mechanics and Materials 573 (June 2014): 556–59. http://dx.doi.org/10.4028/www.scientific.net/amm.573.556.

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Infrastructure-As-A-Service (IAAS) provides an environmental setup under any type of cloud. In Distributed file system (DFS), nodes are simultaneously serve computing and storage functions; that is parallel Data Processing and storage in cloud. Here, file is considered as a data or load. That file is partitioned into a number of File chunks (FC) allocated in distinct nodes so that Map Reduce tasks can be performed in parallel over the nodes. Files and Nodes can be dynamically created, deleted, and added. This results in load imbalance in a distributed file system; that is, the file chunks are
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Dissertations / Theses on the topic "Distributed Storage Server (DSS)"

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Gkikas, Nikolaos. "Data Transfer and Management through the IKAROS framework : Adopting an asynchronous non-blocking event driven approach to implement the Elastic-Transfer's IMAP client-server connection." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166740.

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Given the current state of input/output (I/O) and storage devices in petascale systems, incremental solutions would be ineffective when implemented in exascale environments. According to the "The International Exascale Software Roadmap", by Dongarra, et al. existing I/O architectures are not sufficiently scalable, especially because current shared file systems have limitations when used in large-scale environments. These limitations are: Bandwidth does not scale economically to large-scale systems, I/O traffic on the high speed network can impact on and be influenced by other unrelated jobs, a
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Chiou, Ying-Chuang, and 邱盈創. "A Load Distributed Server based on RTSP and The MPEG-2 TS Support in DSS." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/99066365090277149605.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>95<br>Because the limitations of hardware, a streaming server has the limitation of its service. In order to provide the scalability, the system provider must build a group of large servers to serve the customers. This thesis provides the implementation of a load distributed server based on RTSP. In this system, the master server uses the “303 See Other” response in RTSP to redirect the clients. Using the mechanism, we provide a loose architecture for scalable. We also add a monitoring mechanism to make the system reliable. If this system collaborates with smart cli
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Books on the topic "Distributed Storage Server (DSS)"

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Ecklund, Denise J. Robustness in a distributed storage server for engineering design data with versions. 1986.

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Book chapters on the topic "Distributed Storage Server (DSS)"

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Bonhomme, Alice, and Loïc Prylli. "A Distributed Storage System for a Video-on-Demand Server." In Euro-Par 2000 Parallel Processing. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44520-x_157.

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Ding, Jen-Wen, Yueh-Min Huang, Sheng-Yuan Zeng, and Chang-Chung Chu. "Video Database Techniques and Video-on-Demand." In Distributed Multimedia Databases. IGI Global, 2002. http://dx.doi.org/10.4018/978-1-930708-29-7.ch009.

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Generally, a large-scale video server is composed of numerous disk striping groups. The striping policies employed by each disk striping group largely determine the performance of a video server. For storage and transmission efficiency, video data are usually compressed using variable-bit-rate (VBR) encoding algorithms, such as JPEG and MPEG. The amount of data consumed by a VBR video stream varies with time. This property, when coupled with striping, unfortunately, results in load imbalance across disks, degrading the overall server performance significantly. This chapter focuses on VBR video
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Vinitha, K., P. Thirumoorthy, and S. Hemalatha. "Data Storage, Data Forwarding, Data Retrieval With Big Data Deepfakes in Secure Cloud Storage." In Advances in Multimedia and Interactive Technologies. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6060-3.ch009.

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Deduplication technologies are extensively used in distributed storage management to lower the space and transfer rate needs of services by eliminating redundant information and storing only its single replica. Many clients redistributing comparable data to a shared repository is ideal for deduplication; however, this practise raises concerns about data ownership and confidentiality. Each data owner can confidently show a distributed storage server that they are the rightful owner of a piece of data via confirmation of holding plans. In contrast to state, many clients would encrypt data before
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Sansiya, Rohit, Pushpendra Kumar, Ramjeevan Singh Thakur, and Abdulhai Mohammadi. "Integrate Hybrid Cloud Computing Server With Automated Remote Monitoring for Blockchain as a Service." In Blockchain Applications in IoT Security. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2414-5.ch012.

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Blockchain is also used for bitcoin transactions as a technology for accumulating data files in the cloud for key distribution and file manipulation in distributed fashion. It is a service of cloud that manages elasticity of compute cloud, storage, and technology of network security (i.e., secure solution to store and share information by offering a distributed ledger service). In distributed systems, abandoned events are much more frequent than centralized system. This concept causes a number of issues including data reliability, high economical cost, and information system security. In this
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Hung, Chim, and Deng Xiaotie. "A Semantics-Based Information Distribution Framework for Large Web- Based Course Forum System." In Advances in Distance Education Technologies. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-934-2.ch001.

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We propose a novel data distribution framework for developing a large Web-based course forum system. In the distributed architectural design, each forum server is fully equipped with the ability to support some course forums independently. The forum servers collaborating with each other constitute the whole forum system. Therefore, the workload of the course forums can be shared by a group of the servers. With the secure group communication protocol and fault tolerance design, the new distribution framework provides a robust and scalable distributed architecture for the large course forum syst
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Vanamoorthy, Muthumanikandan. "Secure Data Sharing Using Revocable-Storage Identity-Based Encryption." In Advances in Information Security, Privacy, and Ethics. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6646-9.ch005.

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Distributed computing provides flexible and informative information exchange and brings many benefits to both the general public and individuals. However, because the information often contains the most important data, there is a common lock that allows users to easily reuse cloud host information. Therefore, it is important for users to provide cryptographically enhanced access control to shared resources. Personality-based encryption is, for example, a promising encryption approach for building smart data sharing systems. Anyway, access to management is not a versatile solution. In such case
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Mejías, B., and P. Van Roy. "Beernet." In Technological Innovations in Adaptive and Dependable Systems. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0255-7.ch017.

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Distributed systems with a centralized architecture present the well known problems of single point of failure and single point of congestion; therefore, they do not scale. Decentralized systems, especially as peer-to-peer networks, are gaining popularity because they scale well, and do not need a server to work. However, their complexity is higher due to the lack of a single point of control and synchronization, and because consistent decentralized storage is difficult to maintain when data constantly evolves. Self-management is a way of handling this higher complexity. In this paper, the aut
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Ma, Minhua, and Andreas Oikonomou. "Network Architectures and Data Management for Massively Multiplayer Online Games." In Evolving Developments in Grid and Cloud Computing. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0056-0.ch010.

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Current-generation Massively Multiplayer Online Games (MMOG), such as World of Warcraft, Eve Online, and Second Life are mainly built on distributed client-server architectures with server allocation based on sharding, static geographical partitioning, dynamic micro-cell scheme, or optimal server for placing a virtual region according to the geographical dispersion of players. This paper reviews various approaches on data replication and region partitioning. Management of areas of interest (field of vision) is discussed, which reduces processing load dramatically by updating players only with
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Verma, Chitresh, and Rajiv Pandey. "Mobile Cloud Computing Integrating Cloud, Mobile Computing, and Networking Services Through Virtualization." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5339-8.ch010.

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Mobile computing is a critical technology area which is actively integrated with field of cloud computing. It is broadly an application of virtualization technology at both ends of client server architecture. The mobile and cloud computing is a natural combination as mobile devices have limited computing and storage capacity, thus to reap the benefits of high end computing, cloud is the answer. Thus, amalgamation of mobile platform with cloud platform is inevitable. This chapter shall deliberate on the various aspects of mobile computing, mobile cloud computing and its relationship with virtua
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Alfiansyah, Agung, Helena Widiarti, Vincentius Reynaldo, Wilsen Widjaja, and Laurent Bobelin. "A Framework for Multi Institutional Collaboration for Pneumonia Screening by Means of Federated Learning." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia231185.

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This project addresses in reducing pneumonia-related mortality by involving a development of an automatic screening system that analyzes X-ray images and distributed image data storage. This objective is achieved through a collaborative approach, employing Federated Learning to establish a platform that fosters cooperation of the hospitals. Each of them contributes to the advancement of diagnostics by constructing local models from their respective data. These local models are then transmitted to a central server that aggregate models to create a comprehensive global model. This process ensure
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Conference papers on the topic "Distributed Storage Server (DSS)"

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Fukatani, Takayuki, Hieu Hanh Le, and Haruo Yokota. "Lightweight Dynamic Redundancy Control for Server-Based Storage." In 2019 38th Symposium on Reliable Distributed Systems (SRDS). IEEE, 2019. http://dx.doi.org/10.1109/srds47363.2019.00042.

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Yu, Huihuang, Zongwei Zhu, XiangLan Chen, Yuming Cheng, Yahui Hu, and Xi Li. "Accelerating Distributed Training in Heterogeneous Clusters via a Straggler-Aware Parameter Server." In 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2019. http://dx.doi.org/10.1109/hpcc/smartcity/dss.2019.00042.

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Bonomi, Silvia, Shlomi Dolev, Maria Potop-Butucaru, and Michel Raynal. "Stabilizing Server-Based Storage in Byzantine Asynchronous Message-Passing Systems." In PODC '15: ACM Symposium on Principles of Distributed Computing. ACM, 2015. http://dx.doi.org/10.1145/2767386.2767441.

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Chen, Bo, Anil Kumar Ammula, and Reza Curtmola. "Towards Server-side Repair for Erasure Coding-based Distributed Storage Systems." In CODASPY'15: Fifth ACM Conference on Data and Application Security and Privacy. ACM, 2015. http://dx.doi.org/10.1145/2699026.2699122.

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Zhang, Hao, and GAI Rong-Li. "Distributed HBase Cluster Storage Engine and Database Performance Optimization." In 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys). IEEE, 2021. http://dx.doi.org/10.1109/hpcc-dss-smartcity-dependsys53884.2021.00341.

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Feihn, Heinz Ulrich Boehmer, Mark A. Hinkle, Richard Wallace Kenyon, and Alan Mickelson. "Management of Distributed Electrical Storage in Wide Area Communication Systems." In 2017 IEEE 19th International Conference on High Performance Computing and Communications, IEEE 15th International Conference on Smart City and IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2017. http://dx.doi.org/10.1109/hpcc-smartcity-dss.2017.15.

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Choe, Yung Ryn, and Vijay S. Pai. "Achieving Reliable Parallel Performance in a VoD Storage Server Using Randomization and Replication." In 2007 IEEE International Parallel and Distributed Processing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/ipdps.2007.370220.

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Rashid, Md Tahmid, Daniel Zhang, and Dong Wang. "EdgeStore: Towards an Edge-Based Distributed Storage System for Emergency Response." In 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2019. http://dx.doi.org/10.1109/hpcc/smartcity/dss.2019.00356.

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Ming, Liang, Dan Feng, Fang Wang, Haifeng Sun, and Sen Wu. "A High Performance and High Reliability Storage Server for Parallel File System." In 2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2012. http://dx.doi.org/10.1109/cyberc.2012.20.

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Guillen, Luis, Satoru Izumi, Toru Abe, Takuo Suganuma, and Hiroaki Muraoka. "SDN-based hybrid server and link load balancing in multipath distributed storage systems." In NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2018. http://dx.doi.org/10.1109/noms.2018.8406286.

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