Bai, Fenhua, Shen, Tao, Yu, Zhuo, Song, Jian, Gong, Bei, Waqas, Muhammad ORCID: https://orcid.org/0000-0003-0814-7544 and Alasmary, Hisham (2024) Blockchain-enhanced time-variant mean field-optimized dynamic computation sharing in mobile network. IEEE Transactions on Wireless Communications, 23 (9). pp. 12140-12156. ISSN 1536-1276 (Print), 1558-2248 (Online) (doi:10.1109/TWC.2024.3388411)

Preview

PDF (Author's Accepted Manuscript) 48663 WAQAS_Blockchain-Enhanced_Time-Variant_Mean_Field-Optimized_Dynamic_Computation_(AAM)_2021.pdf - Accepted Version Download (2MB) | Preview

Abstract

Although 5G and beyond communication technology empower a large number of edge heterogeneous devices and applications, the stringent security remains a major concern when dealing with the millions of edge computing tasks in the highly dynamic heterogeneous networks (HDHNs). Blockchains contribute significantly to addressing security challenges by guaranteeing the reliability of data and information. Since the node’s mobility, there are risks of exiting the network and leaving the remaining tasks noncomputed. Therefore, we model the cost function of offloaded computing tasks as a dynamic stochastic game. To reduce the computational complexity, the Time-Variant Mean-Field term (TVMF) is adopted to solve the cost-optimized problem. What’s more, we design an Adaptivity-Aware Practical byzantine fault tolerance consensus Protocol (AAPP) to dynamically formulate domains, execute leader node selection with regard to task completion and quickly verify computational results. In addition, a Dynamic Multi-domain Fractional Repetition uncoded repair storage (DMFR) scheme with variant redundancy is proposed to reduce the storage pressure and repair overhead. The simulation is implemented to demonstrate our scheme outperforms the benchmarks in terms of cost and time overhead.

Item Type:	Article
Uncontrolled Keywords:	dynamic networks, tasks offload, blockchains, mean-field game, fractional repetition code
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	13 Dec 2024 12:30
URI:	http://gala.gre.ac.uk/id/eprint/48663

Actions (login required)

View Item

Downloads