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4th International Conference on Frontiers of Manufacturing and Design Science (ICFMD 2013)

作者： Mao, Hongxia Sichuan TOP IT Vocat Inst Coll Comp Chengdu 611743 Sichuan Peoples R China

ISBN: (纸本)9783037859926

In this paper, an extensible system prototype of cloud storage is designed. Considering the load balance of cloud storage system, an improved data storage strategy based on consistent hashing algorithm is proposed in this paper. The strategy adopts virtual nodes to storage data and real-time monitoring of load rate of each storage node to adjust load balancing of the whole storage system. In the improved strategy, the priority is introduced into the storage system to rapidly raise the utilization rate of the new storage nodes. The strategy can effectively optimize the performance of the whole storage system, and improve the overall effect of the load balancing.

关键词： cloud storage consistent hashing distributed data storage priority load balancing

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Blockchain-based solutions for mobile crowdsensing: A comprehensive survey

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COMPUTER SCIENCE REVIEW 2023年 50卷

作者： Yu, Ruiyun Oguti, Ann Move Obaidat, Mohammad S. Li, Shuchen Wang, Pengfei Hsiao, Kuei-Fang Northeastern Univ Software Coll Shenyang 110819 Peoples R China Univ Jordan King Abdullah Sch Informat Technol 2 Amman 11942 Jordan Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China SRM Univ Sch Comp Dept Computat Intelligence SRM Nagar Kattankulathur 603203 Tamil Nadu India Amity Univ Sch Engn Noida 201301 Uttar Pradesh India Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China Univ Texas Permian Basin Comp Sci Dept 4901 E Univ Blvd ST 2118 Odessa TX 79762 USA Univ Texas Permian Basin Cybersecur Ctr 4901 E Univ Blvd ST 2118 Odessa TX 79762 USA

Mobile crowdsensing (MCS) is an emerging data-driven paradigm that leverages the collective intel-ligence of the crowd, their mobility, and the crowd-companioned smart mobile devices embedded with powerful sensors to acquire information from the physical environment for crowd intelligence extraction and human-centric service delivery. However, existing MCS systems operate in a centralized manner, giving rise to several challenges, including privacy, security, incentives, and dependence on a central service provider. Blockchain is a novel application paradigm that incorporates point-to-point transmission, consensus mechanisms, cryptography, intelligent contracts, distributed data storage, and other computing technologies, creating a shift from the current centralized paradigm to a decentralized paradigm. Nonetheless, the convergence of MCS and blockchains necessitates addressing numerous fundamental challenges arising from their merger. This paper examines the major issues facing MCS systems and blockchain's potential role in addressing them. We present the MCS-blockchain integrated deployment strategies, architectural designs, and core blockchain technology principles that contribute significantly to the performance of blockchain-based MCS applications. Additionally, the advancement of blockchain technology and its impact on MCS system security and performance requirements are investigated. Finally, we highlight current research gaps and future research opportunities that may inspire the deployment of novel blockchain-based MCS systems.(c) 2023 Elsevier Inc. All rights reserved.

关键词： Mobile crowdsensing Blockchain Privacy Incentive mechanisms distributed data storage

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The central role of data repositories and data models in data Science and Advanced Analytics

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2022年 129卷 13-17页

作者： Bellatreche, Ladjel Ordonez, Carlos Mery, Dominique Golfarelli, Matteo Abdelwahed, El Hassan LIAS ISAE ENSMA Poitiers Univ Poitiers France Univ Houston Data Sci Syst Lab Houston TX 77004 USA LORIA Nancy France Univ Bologna Comp Engn Bologna Italy Univ Cadi Ayyad Comp Sci Marrakech Morocco

In the age of ''data Science and Advanced Analytics'', we are witnessing a race for developing data-driven smart systems in various domains such as business, finance, healthcare, environment, cybersecurity, etc. due the explosion of the data issued by various providers. This development contributes in getting added value for companies and citizens. Two complementary ingredients are required for ensuring valuable systems: data and models. The data dimension is mainly related to data Science that unifies machine learning, statistics, data mining, databases, and distributed systems. The achievement of this value may pass through the augmentation of input data by resources such as Knowledge Graphs. The success of the above techniques strongly depends on the quality of the input data and the consideration of other non-functional properties related to legal, ethical, and economical aspects. On the other hand, modeling plays a crucial role in data Science since it covers all steps of data Science workflow. Regarding data provenance and its quality, models contribute to providing vendor-independent solutions. At the algorithmic level, models help in explaining the inner working of the used methods/algorithms to system designers, users, regulators, and citizens to achieve trust and accountability. Therefore, the success of data Science depends on our skill to use it a smart way and simultaneously exploiting data and modeling capabilities. (C) 2021 Published by Elsevier B.V.

关键词： data Science data science workflow Advanced Analytics Value Knowledge Graphs distributed data storage Model engineering Formal methods Model driven engineering distributed algorithms

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Optimal Codes for distributed storage

Optimal Codes for Distributed Storage

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International Conference on Computing, Networking and Communications (ICNC)

作者： Ren, Jian Li, Jian Li, Tongtong Michigan State Univ Dept ECE E Lansing MI 48824 USA Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China

ISBN: (纸本)9781665457194

Regenerating codes are a class of distributed storage codes that allow for efficient repair of failed nodes, as compared to traditional erasure codes, which enables it to achieve high data reliability, security, and cost-efficiency and a critical infrastructure of the computing system. Existing data storage largely depends on a centralized cloud, which is not only costly but also vulnerable to single points of failure and other types of security attacks. To provide data security, data encryption has to be used, which requires extensive computing power and cumbersome key management. distributed storage system (DSS) is being widely viewed as a natural solution to future online data storage due to improved access time and lower storage cost. However, the existing DSS also has the limitations of low storage efficiency and lack of data security. In this paper, we investigate multi-layer code-based distributed data storage systems that can achieve inherit content confidentiality and optimal storage efficiency. Our comprehensive shows that the optimal code can improve the reliable data storage by nearly 50% comparing to the existing state-of-art research.

关键词： distributed data storage regeneration code optimal storage adversarial networks

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DITIS: A distributed Tiered storage Simulator

INFOCOMMUNICATIONS JOURNAL

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INFOCOMMUNICATIONS JOURNAL 2022年第4期14卷 18-25页

作者： Filho, Edson Ramiro Lucas Odysseos, Lambros Lun, Yang Kebo, Fu Herodotou, Herodotos Cyprus Univ Technol Data Intens Comp Res Lab Limassol Cyprus Cyprus Univ Technol Limassol Cyprus Huawei Technol Co Ltd Shenzhen Peoples R China

This paper presents DITIS, a simulator for dis-tributed and tiered file-based storage systems. In particular, DITIS can model a distributed storage system with up to three levels of storage tiers and up to three additional levels of caches. Each tier and cache can be configured with different number and type of storage media devices (e.g., HDD, SSD, NVRAM, DRAM), each with their own performance characteristics. The simulator utilizes the provided characteristics in fine-grained performance cost models (which are distinct for each device type) in order to compute the duration time of each I/O request processed on each tier. At the same time, DITIS simulates the overall flow of requests through the different layers and storage nodes of the system using numerous pluggable policies that control every aspect of execution, ranging from request routing and data redundancy to cache and tiering strategies. For performing the simulation, DITIS adapts an extended version of the Actor Model, during which key components of the system exchange asynchronous messages with each other, much like a real distributed multi-threaded system. The ability to simulate the execution of a workload in such an accurate and realistic way brings multiple benefits for its users, since DITIS can be used to better understand the behavior of the underlying file system as well as evaluate different storage setups and policies.

关键词： storage Simulator distributed data storage Tiered storage Performance Cost Models

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SmartKV: A cost-effective and low-latency geo-distributed key-value store for the computing continuum

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2025年 171卷

作者： Poveda, Juan Aznar Ebner, Maximilian Franz Fahringer, Thomas Samani, Zahra Najafabadi Etheredge, Marlon Pedratscher, Stefan Saurabh, Nishant Univ Innsbruck Distributed & Parallel Syst Grp Tech Str 21A A-6020 Innsbruck Austria Univ Utrecht Dept Informat & Comp Sci Princetonpl 5 NL-3584 Utrecht Netherlands

Many data-intensive and distributed applications rely on low-latency and scalable key-value storage systems across the Computing Continuum. Key-value storage systems typically use consistent hashing or hash slotsharding mechanisms to distribute data across storage nodes, which ensures load balancing but often leads to sub-optimal response times and monetary costs, particularly in geo-distributed systems where nodes might have different unit prices and be widely dispersed. In this paper, we propose SmartKV, a cost-efficient geodistributed key-value store that optimizes data placement dynamically, abstracting the intricacies of data organization, transfer, access, and processing. SmartKV integrates a decentralized data placement algorithm that optimizes the replication factor and selects suitable locations for key-value pairs and replicas, balancing cost and access latency while keeping optimization overhead low. We employ a realistic cost model based on public and private Cloud and Edge providers that consider data transfer, request, and storage costs. In addition to conventional key-value pairs, SmartKV supports active key-value pairs, which enable the definition of custom data types and the execution of user-defined functions directly on the storage side. This contributes to reducing data transfer costs and round-trip times. We thoroughly evaluate SmartKV across different regions of the Chameleon testbed using several realistic workloads. Results show that the utilized decentralized data placement strategy allows SmartKV to reduce round trip times between 9 and 84% while reducing costs up to 4.84x under different client workloads and consistency models compared to state-of-the-art data placement strategies.

关键词： distributed data distributed key-value storage distributed data storage Decentralized data placement data migration Replica management Computing continuum

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Implementation of a Network-Centric Production storage System in distributed High-Performance Computing Systems 11th

Implementation of a Network-Centric Production Storage Syste...

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11th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production (HPCST)

作者： Bashlykova, Anna MIREA Russian Technol Univ Vernadsky Ave 78 Moscow 119454 Russia Russian Acad Sci VA Kotelnikov Inst Radio Engn & Elect Mokhovaya St 11-7 Moscow 125009 Russia

ISBN: (纸本)9783030941413;9783030941406

The main components of a network production data storage system in distributed high-performance computing systems are defined. A hybrid method of organizing a data storage network is considered. A feature of distributed data storage is the semantic distribution of data blocks. The interoperability of local data storage (LDS) and data export utilities is to transform the low-level organization of LDS data. When organizing a resource center, LDS plays the role of a DBMS, and the data export utility serves to organize data in a form suitable for processing by the main storage module. Thus, the interoperability of local data stores and data export utilities implies the formalization of DBMS (LDS) data for their subsequent processing. The data of interaction of the storage system when accessing computing clusters is reduced to the form of a JSON file, divided into "entities", "actions" and "links".

关键词： High-performance environment distributed computing environment Information management systems (IMS) distributed data storage Network-centric production system

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A blockchain-assisted framework for secure and reliable data sharing in distributed systems

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2021年第1期2021卷 1-19页

作者： Guo, Yu Wang, Shenling Huang, Jianhui Beijing Normal Univ Sch Artificial Intelligence Beijing Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China

The explosive growth of big data is pushing forward the paradigm of cloud-based data store today. Among other, distributed storage systems are widely adopted due to their superior performance and continuous availability. However, due to the potentially wide attacking surfaces of the public cloud, outsourcing data store inevitably raises new concerns on user privacy exposure and unauthorized data access. Besides, directly introducing a centralized third-party authority for query authorization management does not work because it still can be compromised. In this paper, we propose a blockchain-assisted framework that can support trustworthy data sharing services. In particular, data owners allow to outsource their sensitive data to distributed systems in encrypted form. By leveraging smart contracts of blockchain, a data owner can distribute secret keys for authorized users without extra round interaction to generate the permitted search tokens. Meanwhile, such blockchain-assisted framework naturally solves the trust issues of query authorization. Besides, we devise a secure local index framework to support encrypted keyword search with forward privacy and mitigate blockchain overhead. To validate our design, we implement the prototype and deploy it at Amazon Cloud. Extensive experiments demonstrate the security, efficiency, and effectiveness of the blockchain-assisted design.

关键词： Dynamic searchable encryption distributed data storage Forward security Smart contract Blockchain

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CoopStor: a cooperative reliable and efficient data collection protocol in fault and delay tolerant wireless networks

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WIRELESS NETWORKS 2021年第1期27卷 367-381页

作者： Papadopoulos, Georgios Z. Mavromatis, Alex Gallais, Antoine Theoleyre, Fabrice IRISA IMT Atlantique Rennes France Univ Bristol Fac Engn Bristol Avon England Polytech Univ Hauts de France CNRS LAMIH Lab Valenciennes France Univ Strasbourg CNRS Pole API ICube Lab Blvd Sebastien Brant F-67412 Illkirch Graffenstaden France

Internet of things consist in the deployment of constrained and battery-powered devices with a radio interface. Most industrial applications require to respect strict reliability and delay constraints. Lossy links imply mechanisms to retransmit the packets to improve the reliability. However, transient faults (e.g. obstacles, interference) may also impact the reliability, and require to change the routes. In this article, we present cooperative storing mode (CoopStor), that detects the faults and triggers action before a packet is dropped. In particular, the packets are cooperatively stored in the network, until the routing protocol re-converges. The congested zone gradually increases to serve as a local storage facility. CoopStor relies on a selection of relay and leaf nodes to reduce the energy consumption while providing a low end-to-end delay in steady state. Our performance evaluation campaign highlights a reduction of packet drops and an improved energy-efficient data collection procedure.

关键词： Fault-tolerance Congestion distributed data storage Reliability Queue management storage nodes Synchronized MAC

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Partial MDS Codes With Regeneration

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IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第10期67卷 6425-6441页

作者： Holzbaur, Lukas Puchinger, Sven Yaakobi, Eitan Wachter-Zeh, Antonia Tech Univ Munich Inst Commun Engn D-80333 Munich Germany Tech Univ Denmark DTU Dept Appl Math & Comp Sci DK-2800 Lyngby Denmark Technion Israel Inst Technol Comp Sci Dept IL-3200003 Haifa Israel

Partial MDS (PMDS) and sector-disk (SD) codes are classes of erasure correcting codes that combine locality with strong erasure correction capabilities. We construct PMDS and SD codes with local regeneration where each local code is a bandwidth-optimal regenerating MDS code. In the event of a node failure, these codes reduce both, the number of servers that have to be contacted as well as the amount of network traffic required for the repair process. The constructions require significantly smaller field size than the only other construction known in literature. Further, we present a construction of PMDS codes with global regeneration which allow to efficiently repair patterns of node failures that exceed the local erasure correction capability of the code and thereby invoke repair across different local groups.

关键词： Maintenance engineering Bandwidth Redundancy Loss measurement Encoding Servers Resilience Partial MDS codes maximally recoverable codes regenerating codes erasure correction distributed data storage

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