Blockchain as a Platform for Fog Computing

Podsevalov, Ivan; Iakushkin, Oleg; Kurbangaliev, Ruslan; Korkhov, Vladimir

doi:10.1007/978-3-030-24296-1_48

Cited by 10 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Modern advancements such as big data analytics, machine learning, and deep learning are combined with fog for generating data analytics on the fly with adaptive learning [ 31 , 32 , 33 , 34 ]. Leveraging the technology of blockchain to accommodate privacy and security features in the fog layer is proposed in [ 35 , 36 , 37 ]. Software-defined networks (SDNs) with customized routing protocols are used to increase the energy efficiency and performance between fog nodes [ 38 ].…”

Section: Current State-of-the-artmentioning

confidence: 99%

An Overview of Fog Data Analytics for IoT Applications

Bhatia

Italiya²,

Jadeja

et al. 2022

Sensors

View full text Add to dashboard Cite

With the rapid growth in the data and processing over the cloud, it has become easier to access those data. On the other hand, it poses many technical and security challenges to the users of those provisions. Fog computing makes these technical issues manageable to some extent. Fog computing is one of the promising solutions for handling the big data produced by the IoT, which are often security-critical and time-sensitive. Massive IoT data analytics by a fog computing structure is emerging and requires extensive research for more proficient knowledge and smart decisions. Though an advancement in big data analytics is taking place, it does not consider fog data analytics. However, there are many challenges, including heterogeneity, security, accessibility, resource sharing, network communication overhead, the real-time data processing of complex data, etc. This paper explores various research challenges and their solution using the next-generation fog data analytics and IoT networks. We also performed an experimental analysis based on fog computing and cloud architecture. The result shows that fog computing outperforms the cloud in terms of network utilization and latency. Finally, the paper is concluded with future trends.

show abstract

Section: Current State-of-the-artmentioning

confidence: 99%

An Overview of Fog Data Analytics for IoT Applications

Bhatia

Italiya²,

Jadeja

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Recently few papers [27][28][29][30][31][32][33][34][35][36][37] were published using Blockchain and IPFS concepts for different real time applications, but these papers have not provided detailed information about how to store data into the Blockchain, how to connect Blockchain with IPFS and how transaction size affects to performance. Existing papers concentrated mostly on algorithms and Blockchain concepts.…”

Section: Literature Workmentioning

confidence: 99%

Adaptation of Blockchain using Ethereum and IPFS for Fog based E-Healthcare Activity Recognition System

Kodavali

Kuppuswamy

2022

Trends Sci

View full text Add to dashboard Cite

The cloud storage is far away from us and it is not capable of handling huge bandwidth data due to network latency. The goal of the Fog computing is to decrease the data that needs to be transferred to the cloud for data processing and to increase the efficiency. Fog computing improves the QoS and also reduces network bandwidth. All machine learning algorithm performances are dependent on the quality of the training data. If the training data is inadequate or it is modified by attackers, then the machine learning algorithm will miss predict and may give invalid results. In order to avoid modification of training data, it is preferable to store it in Blockchain. Blockchain is a decentralized model and its data structure is practically difficult to forge, hence it has attracted both industry and research now-a-days. Proposed system uses Ethereum platform to implement Blockchain. Ethereum allows users to create and run decentralized applications (DApps) to make agreements and to conduct transactions directly with each other without any third party by making use of smart contracts. Blockchain is convenient to store only a small amount of data, hence alternative solution to store large amount of data, for example in healthcare, in Blockchain is possible with the help of IPFS (Interplanetary File System). In e-healthcare applications, Activity Recognition System (ARS) is the most significant undertaking in remote checking of patients experiencing physical medical issues for taking quick action. Hence this paper, especially concentrate on the overall framework of the e-healthcare ARS and implementation of Blockchain to store e-healthcare training data to avoid forging, ultimately which improves ARS results. Our implementation results also show that constant and less transaction fee required to store into Blockchain irrespective of size of training data with help of IPFS and also proved transaction throughput increases and network delay decreases with help of IPFS. HIGHLIGHTS All machine learning algorithm performances are dependent on the quality of the training data. If the training data is inadequate or it is modified by attackers, then the machine learning algorithm will miss predict and may give invalid results To avoid modification of training data, it is preferable to store it in Blockchain. Blockchain is a decentralized model, and its data structure is practically difficult to forge Proposed system uses Ethereum platform and IPFS to implement Blockchain using smart contracts for health care applications Our implementation results also show that constant and less transaction fee required to store into Blockchain irrespective of size of training data with help of IPFS, and proved transaction throughput increases and network delay decreases with help of IPFS GRAPHICAL ABSTRACT

show abstract

“…This allocation of computing resources to miners was shown to be computationally efficient. Authors of [42] proposed Blockchain-as-a-Platform for FC applications using the Corda distributed ledger platform 5 . Groups of vacuum cleaners, representing Things, were connected to Raspberry Pi nodes, representing fog nodes, to which the maps of the cleaned areas were transmitted.…”

Section: B Smart Mobile Devices Applications (Smds)mentioning

confidence: 99%

A Survey on Blockchain-Fog Integration Approaches

Baniata

Kertész

2020

IEEE Access

View full text Add to dashboard Cite

Fog computing (FC) is the extension of Cloud Computing (CC), from the core of the internet architecture to the edge of the network, with the aim to perform processes closer to end-users. This extension is proven to enhance security, and to reduce latency and energy consumption. Blockchain (BC), on the other hand, is the base technology behind crypto-currencies, yet is implemented in wide range of different applications. The security and reliability, along with the distributed trust management criteria proposed in BC, excited the research community to integrate it with FC, in a step towards reaching a distributed and trusted, Data, Payment, Reputation, and Identity management systems. In this survey we present the upto-date state-of-the-art of FC-BC integration with a detailed literature review and classification. We discuss and categorize the related papers according to the year of publication, domain, used algorithms, BC roles, and the placement of the BC in the FC architecture. Our research presents detailed observations, analysis, and open challenges for the BC-FC integration. We believe such conclusions may clarify the vision of the BC-FC integration, and calibrate the compass towards open issues and future research directions.

show abstract

Blockchain as a Platform for Fog Computing

Cited by 10 publications

References 5 publications

An Overview of Fog Data Analytics for IoT Applications

An Overview of Fog Data Analytics for IoT Applications

Adaptation of Blockchain using Ethereum and IPFS for Fog based E-Healthcare Activity Recognition System

A Survey on Blockchain-Fog Integration Approaches

Contact Info

Product

Resources

About