AR-RRNS: Configurable reliable distributed data storage systems for Internet of Things to ensure security

2019 ◽  
Vol 92 ◽  
pp. 1080-1092 ◽  
Author(s):  
Nikolay Chervyakov ◽  
Mikhail Babenko ◽  
Andrei Tchernykh ◽  
Nikolay Kucherov ◽  
Vanessa Miranda-López ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Data Storage ◽  
Storage Systems ◽  
Distributed Data ◽  
Distributed Data Storage

Activity of public control entities and development of distributed computing and distributed data storage systems

2018 ◽  
pp. 14-22
Author(s):  
D. V. Gribanov
Keyword(s):  
Distributed Computing ◽  
Data Storage ◽  
Storage Systems ◽  
Legal Regulation ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Public Control ◽  
Blockchain Technology ◽  
Legal Method ◽  
Digital Assets

Introduction. This article is devoted to legal regulation of digital assets turnover, utilization possibilities of distributed computing and distributed data storage systems in activities of public authorities and entities of public control. The author notes that some national and foreign scientists who study a “blockchain” technology (distributed computing and distributed data storage systems) emphasize its usefulness in different activities. Data validation procedure of digital transactions, legal regulation of creation, issuance and turnover of digital assets need further attention.Materials and methods. The research is based on common scientific (analysis, analogy, comparing) and particular methods of cognition of legal phenomena and processes (a method of interpretation of legal rules, a technical legal method, a formal legal method and a formal logical one).Results of the study. The author conducted an analysis which resulted in finding some advantages of the use of the “blockchain” technology in the sphere of public control which are as follows: a particular validation system; data that once were entered in the system of distributed data storage cannot be erased or forged; absolute transparency of succession of actions while exercising governing powers; automatic repeat of recurring actions. The need of fivefold validation of exercising governing powers is substantiated. The author stresses that the fivefold validation shall ensure complex control over exercising of powers by the civil society, the entities of public control and the Russian Federation as a federal state holding sovereignty over its territory. The author has also conducted a brief analysis of judicial decisions concerning digital transactions.Discussion and conclusion. The use of the distributed data storage system makes it easier to exercise control due to the decrease of risks of forge, replacement or termination of data. The author suggests defining digital transaction not only as some actions with digital assets, but also as actions toward modification and addition of information about legal facts with a purpose of its establishment in the systems of distributed data storage. The author suggests using the systems of distributed data storage for independent validation of information about activities of the bodies of state authority. In the author’s opinion, application of the “blockchain” technology may result not only in the increase of efficiency of public control, but also in the creation of a new form of public control – automatic control. It is concluded there is no legislation basis for regulation of legal relations concerning distributed data storage today.

scholarly journals REQUEST BALANCING METHOD FOR INCREASING THEIR PROCESSING EFFICIENCY WITH INFORMATION REPLICATION IN A DISTRIBUTED DATA STORAGE SYSTEM

2021 ◽  
pp. 75-82
Author(s):  
Igor Boyarshin ◽  
Anna Doroshenko ◽  
Pavlo Rehida
Keyword(s):  
Data Storage ◽  
Storage Systems ◽  
Storage System ◽  
New Method ◽  
Distributed Data ◽  
Processing Efficiency ◽  
Distributed Data Storage ◽  
Shared Data ◽  
Multiple Data ◽  
Data Storage System

The article describes a new method of improving efficiency of the systems that deal with storage and providing access of shared data of many users by utilizing replication. Existing methods of load balancing in data storage systems are described, namely RR and WRR. A new method of request balancing among multiple data storage nodes is proposed, that is able to adjust to input request stream intensity in real time and utilize disk space efficiently while doing so.

scholarly journals A novel approach for energy- and memory-efficient data loss prevention to support Internet of Things networks

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092982
Author(s):  
Pooya Hejazi ◽  
Gianluigi Ferrari
Keyword(s):  
Internet Of Things ◽  
Load Balancing ◽  
Data Storage ◽  
Optimization Problem ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Distributed Data ◽  
Data Loss ◽  
Distributed Data Storage ◽  
Wide Range

Internet of Things integrates various technologies, including wireless sensor networks, edge computing, and cloud computing, to support a wide range of applications such as environmental monitoring and disaster surveillance. In these types of applications, IoT devices operate using limited resources in terms of battery, communication bandwidth, processing, and memory capacities. In this context, load balancing, fault tolerance, and energy and memory efficiency are among the most important issues related to data dissemination in IoT networks. In order to successfully cope with the abovementioned issues, two main approaches—data-centric storage and distributed data storage—have been proposed in the literature. Both approaches suffer from data loss due to memory and/or energy depletion in the storage nodes. Even though several techniques have been proposed so far to overcome the abovementioned problems, the proposed solutions typically focus on one issue at a time. In this article, we propose a cross-layer optimization approach to increase memory and energy efficiency as well as support load balancing. The optimization problem is a mixed-integer nonlinear programming problem, and we solve it using a genetic algorithm. Moreover, we integrate the data-centric storage features into distributed data storage mechanisms and present a novel heuristic approach, denoted as Collaborative Memory and Energy Management, to solve the underlying optimization problem. We also propose analytical and simulation frameworks for performance evaluation. Our results show that the proposed method outperforms the existing approaches in various IoT scenarios.

scholarly journals Data Security Storage Method for Power Distribution Internet of Things in Cyber-Physical Energy Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiayong Zhong ◽  
Xiaofu Xiong
Keyword(s):  
Internet Of Things ◽  
Data Storage ◽  
Data Security ◽  
Power Distribution ◽  
Homomorphic Encryption ◽  
Control Mode ◽  
Joint Control ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Storage Method

The existing cloud storage methods cannot meet the delay requirements of intelligent devices in the power distribution Internet of Things (IoT), and it is difficult to ensure the data security in the complex network environment. Therefore, a data Security Storage method for the power distribution IoT is proposed. Firstly, based on the “cloud tube edge end” power distribution IoT structure, a cloud edge collaborative centralized distributed joint control mode is proposed, which makes full use of the collaborative advantages of cloud computing and edge computing to meet the real-time requirements. Then, a distributed data storage method based on the Kademlia algorithm is proposed, and the homomorphic encryption and secret sharing algorithm are used to store the data in the cloud as ciphertext and perform data query directly on the ciphertext. Finally, considering the heterogeneity of edge nodes, the security protection model of edge nodes based on noncooperative differential game is established, and the algorithm of optimal defense strategy of edge nodes is designed to ensure the security of edge nodes. The experimental results show that the proposed method obtained excellent query performance, and the ability to resist network attacks is better than other comparison methods. It can reduce the data storage and query delay and ensure the data security of the system.

Technologies of distributed data storage systems for numerical simulation of materials

2016 ◽  
Vol 43 (12) ◽  
pp. 375-377
Author(s):  
A. M. Zakharov ◽  
M. A. Kazaryan ◽  
A. V. Obkhodskii ◽  
A. S. Popov
Keyword(s):  
Numerical Simulation ◽  
Data Storage ◽  
Storage Systems ◽  
Distributed Data ◽  
Distributed Data Storage
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