IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges

Cai, Hongming; Xu, Bin; Jiang, Lihong; Vasilakos, Athanasios V.

doi:10.1109/jiot.2016.2619369

Cited by 461 publications

(172 citation statements)

References 73 publications

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“…Such logs include certain timestamped information that may be exposed publicly (i.e., it can be scrutinized by all the entities that interact with the blockchain). Some Industry 4.0 applications follow this approach in a strict way and store every performed transaction to be able to carry out audits, to keep accurate traceability records or to make use of Big Data techniques or predictive analytics [27], [28]. It is worth mentioning that such features have been traditionally provided by databases, whose security is essential, especially when they are accessed through the Internet and thus exposed publicly to attacks on their availability or on the data privacy.…”

Section: Introductionmentioning

confidence: 99%

A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories

2019

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Industry 4.0 is a concept devised for improving the way modern factories operate through the use of some of the latest technologies, like the ones used for creating Industrial Internet of Things (IIoT), robotics or Big Data applications. One of such technologies is blockchain, which is able to add trust, security and decentralization to different industrial fields. This article focuses on analyzing the benefits and challenges that arise when using blockchain and smart contracts to develop Industry 4.0 applications. In addition, this paper presents a thorough review on the most relevant blockchain-based applications for Industry 4.0 technologies. Thus, its aim is to provide a detailed guide for future Industry 4.0 developers that allows for determining how blockchain can enhance the next generation of cybersecure industrial applications.

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Section: Introductionmentioning

confidence: 99%

A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories

2019

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“…Many modern technological systems are data‐intensive systems. For example, in emerging Internet‐of‐Things (IoT) systems, smart sensors are being designed into increasingly more devices that interact with daily life of human beings . These applications are making significant contributions to data growth .…”

Section: Introductionmentioning

confidence: 99%

“…For example, in emerging Internet‐of‐Things (IoT) systems, smart sensors are being designed into increasingly more devices that interact with daily life of human beings . These applications are making significant contributions to data growth . As a result, the growing data sources require highly reliable data storage solutions .…”

Section: Introductionmentioning

confidence: 99%

Fault‐level coverage analysis of multistate cloud‐RAID storage systems

Mandava

Xing

Wang

2019

Engineering Reports

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In this paper, a multistate cloud‐RAID (redundant array of independent disks) storage system subject to fault‐level coverage (FLC) is modeled and analyzed. Most of the existing works on reliability analysis of cloud‐RAID systems have either assumed binary‐state for storage disks or failed to consider imperfect fault coverage, an inherent behavior of fault‐tolerant systems. This work advances the state of the art by proposing a combinatorial method based on multivalued decision diagrams for analyzing reliability of a multistate cloud‐RAID system with FLC. The FLC is one common type of imperfect fault coverage behaviors, where the system fault recovery capability is dependent on the number of disk faults happening within a certain recovery window. Effects of the functional dependence behavior between the RAID controller and disks are addressed. The method is illustrated through a detailed analysis of an example cloud‐RAID 5 storage system. Numerical results are provided to show the impact of different design parameters on system performance. These results also demonstrate that failure to consider FLC leads to inaccurate system state probabilities, further misleading system design activities based on these probabilities such as maintenance and optimization.

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“…Due to the fact that traditional cloud computing poses many challenges, mobile edge computing (MEC) is proposed, which consists of relatively weak edge devices [8][9][10]. MEC is a novel paradigm that extends cloud computing capabilities and services to the edge of the network.…”

Section: Introductionmentioning

confidence: 99%

Data Processing Delay Optimization in Mobile Edge Computing

Wang

et al. 2018

Wireless Communications and Mobile Computing

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With the development of Internet of Things (IoT), the number of mobile terminal devices is increasing rapidly. Because of high transmission delay and limited bandwidth, in this paper, we propose a novel three-layer network architecture model which combines cloud computing and edge computing (abbreviated as CENAM). In edge computing layer, we propose a computational scheme of mutual cooperation between the edge devices and use the Kruskal algorithm to compute the minimum spanning tree of weighted undirected graph consisting of edge nodes, so as to reduce the communication delay between them. Then we divide and assign the tasks based on the constrained optimization problem and solve the computation delay of edge nodes by using the Lagrange multiplier method. In cloud computing layer, we focus on the balanced transmission method to solve the data transmission delay from edge devices to cloud servers and obtain an optimal allocation matrix, which reduces the data communication delay. Finally, according to the characteristics of cloud servers, we solve the computation delay of cloud computing layer. Simulation shows that the CENAM has better performance in data processing delay than traditional cloud computing.

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IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges

Cited by 461 publications

References 73 publications

A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories

A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories

Fault‐level coverage analysis of multistate cloud‐RAID storage systems

Data Processing Delay Optimization in Mobile Edge Computing

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