ANN Based Estimation of Reputation of Newcomer Web Services in Fog Computing

Hallappanavar, Vijay L.; Bulla, Chetan; Birje, Mahantesh N.

doi:10.1109/iccci50826.2021.9402656

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…In contrast to some approaches (e.g. [9,15]), we propose to include a model that estimates the reputation of newcomer services based on the correlation between the QoS of a service and its reputation using a regression based technique. 4.…”

Section: Context and Motivationmentioning

confidence: 99%

A reputation assessment model for trustful service recommendation

Tibermacine

Cherif

2023

Computer Standards & Interfaces

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Section: Context and Motivationmentioning

confidence: 99%

A reputation assessment model for trustful service recommendation

Tibermacine

Cherif

2023

Computer Standards & Interfaces

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Blockchain‐Enabled Task Offloading and Resource Allocation in Fog Computing Networks

Huang

Deng

Liang

et al. 2021

Wireless Communications and Mobile Computing

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To address the data security and user privacy issues in the task offloading process and resource allocation of the fog computing network, a blockchain-enabled fog computing network task offloading model is proposed in this paper. Furthermore, to reduce the network utility which is defined as the total energy consumption of the fog computing network and the total delay of the blockchain network, a blockchain-enabled fog computing network task offloading and resource allocation algorithm (TR-BFCN) is proposed to jointly optimize the task offloading decision and resource allocation. Finally, the original nonconvex optimization problem is converted into two suboptimization problems, namely, task offloading decisions and computational resource allocations. Moreover, a two-stage Stackelberg game model is designed to obtain the optimal amount of purchased resource and the optimal resource pricing. Simulation results show that the proposed TR-BFCN algorithm can effectively reduce the network utility compared with other algorithms.

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A comprehensive review on trust management approaches in fog computing

Karthikeyan,

Brindha

2023

IFS

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Decentralised fog computing can provide real-time interaction, minimize latency, heterogeneity, and provide networking services between edge devices and cloud data centers. One of the biggest challenges in the fog layer network is finding a trustworthy fog node. Trust management encompasses the process of being trustworthy and the act of assessing the reliability of other nodes. It is essential to carry out a comprehensive review using a systematic approach in this field to advance our understanding, address emerging challenges, and foster secure and efficient trust management practices. This research paper considers a comprehensive analysis of high-quality fog computing trust management literature from 2018 to 2022. A variety of distinct approaches have been chosen by fog computing-based trust management and these techniques are classified into three categories: algorithms, challenges, and limitations. Further, it reviews the various trust attacks in fog environments, details the solutions proposed in the current literature, and concludes with a discussion of the open challenges and potential future research directions in fog computing.

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ANN Based Estimation of Reputation of Newcomer Web Services in Fog Computing

Cited by 3 publications

References 24 publications

A reputation assessment model for trustful service recommendation

A reputation assessment model for trustful service recommendation

Blockchain‐Enabled Task Offloading and Resource Allocation in Fog Computing Networks

A comprehensive review on trust management approaches in fog computing

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