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With the rapid advancement of the Internet of Things (IoT), the typical application of wireless body area networks (WBANs) based smart healthcare has drawn wide attention from all sectors of society. To alleviate the pressing challenges, such as resource limitations, low-latency service provision, mass data processing, rigid security demands, and the lack of a central entity, the advanced solutions of fog computing, software-defined networking (SDN) and blockchain are leveraged in this work. On the basis of these solutions, a task offloading strategy with a centralized low-latency, secure and reliable decision-making algorithm having powerful emergency handling capacity (LSRDM-EH) is designed to facilitate the resource-constrained edge devices for task offloading. Additionally, to well ensure the security of the entire network, a comprehensive blockchain-based two-layer and multidimensional security strategy is proposed. Furthermore, to tackle the inherent time-inefficiency problem of blockchain, we propose a blockchain sharding scheme to reduce system time latency. Extensive simulation has been conducted to validate the performance of the proposed measures, and numerical results verify the superiority of our methods with lower time-latency, higher reliability and security.


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Task Offloading Strategy with Emergency Handling and Blockchain Security in SDN-Empowered and Fog-Assisted Healthcare IoT

Show Author's information Junyu RenJinze LiHuaxing LiuTuanfa Qin( )
School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, China
Guangxi Key Laboratory of Multimedia Communications and Network Technology, School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China
Faculty of Earth Sciences & Geography, Trinity College, University of Cambridge, Cambridge, CB21TN, UK
Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China
Guangxi University, Xingjian College of Science and Liberal Arts Nanning 530004, China

Abstract

With the rapid advancement of the Internet of Things (IoT), the typical application of wireless body area networks (WBANs) based smart healthcare has drawn wide attention from all sectors of society. To alleviate the pressing challenges, such as resource limitations, low-latency service provision, mass data processing, rigid security demands, and the lack of a central entity, the advanced solutions of fog computing, software-defined networking (SDN) and blockchain are leveraged in this work. On the basis of these solutions, a task offloading strategy with a centralized low-latency, secure and reliable decision-making algorithm having powerful emergency handling capacity (LSRDM-EH) is designed to facilitate the resource-constrained edge devices for task offloading. Additionally, to well ensure the security of the entire network, a comprehensive blockchain-based two-layer and multidimensional security strategy is proposed. Furthermore, to tackle the inherent time-inefficiency problem of blockchain, we propose a blockchain sharding scheme to reduce system time latency. Extensive simulation has been conducted to validate the performance of the proposed measures, and numerical results verify the superiority of our methods with lower time-latency, higher reliability and security.

Keywords: fog computing, software-defined networking (SDN), blockchain, wireless body area networks (WBANs), healthcare IoT, task offloading, blockchain sharding

References(36)

[1]
J. J. Hu, M. Reed, N. Thomos, M. F. Ai-Naday, and K. Yang, Securing SDN controlled IoT networks through edge-block chain, IEEE Internet of Things Journal, vol. 8, no. 4, pp. 2102-2115, 2021.
[2]
S. Garg, K. Kaur, G. Kaddoum, S. H. Ahmed, and D. N. K. Jayakody, SDN-based secure and privacy-preserving scheme for vehicular networks: A 5G perspective, IEEE Transactions on Vehicular Technology, vol. 68, no. 9, pp. 8421-8434, 2019.
[3]
K. Kaur, S. Garg, G. Kaddoum, S. H. Ahmed, and M. Atiquzzaman, KEIDS: Kubernetes-based energy and interference driven scheduler for industrial IoT in edge-cloud ecosystem, IEEE Internet of Things Journal, vol. 7, no. 5, pp. 4228-4237, 2020.
[4]
A. Dorri, S. S. Kanhere, R. Jurdak, and P. Gauravaram, Blockchain for IoT security and privacy: The case study of a smart home, in 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, HI, USA, 2017, pp. 618-623.
DOI
[5]
S. Sarkar, S. Chatterjee, and S. Misra, Assessment of the suitability of fog computing in the context of Internet of Things, IEEE Transactions on Cloud Computing, vol. 1, no. 1, pp. 46-59, 2018.
[6]
M. Mukherjee, S. Kumar, M. Shojafar, Q. Zhang, and C. X. Mavromoustakis, Joint task offloading and resource allocation for delay-sensitive fog networks, in 53rd IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 618-623.
DOI
[7]
W. S. Shi, J. Cao, Q. Zhang, Y. H. Z. Li, and L. Y. Xu, Edge computing: Vision and challenges, IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637-646, 2016.
[8]
G. S. Aujla, R. Chaudhary, N. Kumar, R. Kumar, and J. J. P. C. Rodrigues, An ensembled scheme for QoS-aware traffic flow management in software defined networks, presented at 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 2018, pp. 1-7.
DOI
[9]
M. Ojo, D. Adami, and S. Giordano, A SDN-IoT architecture with NFV implementation, presented at 2016 IEEE Globecom Workshops (GC Wkshps), Washington, DC, USA, 2016, pp. 1-6.
DOI
[10]
J. C. Wang, K. N. Han, A. Alexandridis, Z. Y. Chen, Z. Zilic, Y. Pang, G. Jeon, and F. Piccialli, A blockchain-based eHealthcare system interoperating with WBANs, Future Generation Computer Systems, vol. 110, pp. 675-685, 2020.
[11]
D. Kim, J. Son, D. Seo, Y. Kim, H. Kim, and J. T. Seo, A novel transparent and auditable fog-assisted cloud storage with compensation mechanism, Tsinghua Science and Technology, vol. 25, no. 1, pp. 28-43, 2020.
[12]
Y. Z. Wu, Y. Lyu, and Y. C. Shi, Cloud storage security assessment through equilibrium analysis, Tsinghua Science and Technology, vol. 24, no. 6, pp. 738-749, 2019.
[13]
A. Botta, W. D. Donato, V. Persico, and A. Pescapé, Integration of cloud computing and internet of things: A survey, Future Generation Computer Systems, vol. 56, pp. 684-700. 2016.
[14]
S. Ahmed, M. Saqib, M. Adil, T. Ali, and A. Ishtiaq, Integration of cloud computing with internet of things and wireless body area network for effective healthcare, preesented at 2017 International Symposium on Wireless Systems and Networks (ISWSN), Lahore, Pakistan, 2017, pp. 1-6.
DOI
[15]
S. Moulik, S. Misra, and A. Gaurav, Cost-effective mapping between wireless body area networks and cloud service providers based on multi-stage bargaining, IEEE Transactions on Mobile Computing, vol. 16, no. 6, pp. 1573-1586, 2017.
[16]
G. Almashaqbeh, T. Hayajneh, and A. V. Vasilakos, Qosaware health monitoring system using cloud-based WBANs, Journal of Medical Systems, vol. 38, no. 10, pp. 1-21, 2014.
[17]
Y. Z. Zhou, D. Zhang, and N. X. Xiong, and B. J. Mohd, Post-cloud computing paradigms: A survey and comparison, Tsinghua Science and Technology, vol. 22, no. 6, pp. 714-732, 2017.
[18]
A. Roy, C. Roy, S. Misra, Y. Rahulamathavan, and M. Rajarajan, CARE: Criticality-aware data transmission in CPS-based healthcare systems, pretended 2018 IEEE International Conference on Communications Workshops (ICC Workshops), Kansas City, MO, USA, 2018, pp. 1-6.
DOI
[19]
T. N. Gia, M. Z. Jiang, A. M. Rahmani, T. Westerlund, P. Liljeberg, and H. Tenhunen, Fog computing in healthcare internet of things: A case study on ECG feature extraction, presented at 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, Liverpool, UK, 2015, pp. 356-363.
DOI
[20]
A. Q. Zhang and X. D. Lin, Towards secure and privacypreserving data sharing in e-health systems via consortium blockchain, Journal of Medical Systems, vol. 42, no. 8, p. 140, 2018.
[21]
L. J. Xiao, D. Z. Han, X. W. Meng, W. Liang, and K. C. Li, A secure framework for data sharing in private blockchain-based WBANs, IEEE Access, vol. 8, pp. 153956-153968, 2020.
[22]
M. Cicioǧlu and A. Clhan, SDN-enabled wireless body area networks, presented at 2018 6th International Conference on Control Engineering and Information Technology, Stanbul, Turkey, 2018, pp. 1-5.
DOI
[23]
K. Hasan, K. Ahmed, K. Biswas, M. S. Islam, and O. A. Sianaki, Software defined application-specific traffic management for wireless body area networks, Future Generation Computer Systems, vol. 107, pp. 274-285, 2020.
[24]
M. Cicioǧlu and A. Clhan, SDN-based wireless body area network routing algorithm for healthcare architecture, ETRI Journal, vol. 41, no. 4, pp. 452-464, 2019.
[25]
M. Cicioǧlu and A. Clhan, Energy-efficient and SDN enabled routing algorithm for wireless body area network, Computer Communications, vol. 160, pp. 228-239, 2020.
[26]
V. Varadharajan, U. Tupakula, and K. Karmakar, Secure monitoring of patients with wandering behavior in hospital environments, IEEE Access, vol. 6, pp. 11523-11533, 2018.
[27]
W. Meng, K.-K. R. Choo, S. Furnell, A. V. Vasilakos, and C. W. Probst, Towards bayesian-based trust management for insider attacks in healthcare software-defined networks, IEEE Transactions on Network & Service Management, vol. 15, no. 2, pp. 761-773, 2018.
[28]
A. Yazdinejad, R. M. Parizi, A. Dehghantanha, Q. Zhang, and K. K. R. Choo, An energy-efficient SDN controller architecture for IoT networks with blockchain-based security, IEEE Transactions on Services Computing, vol. 13, no. 4, pp. 625-638, 2020.
[29]
L. Wang, G. Z. Yang, J. Huang, J. Y. Zhang, L. Yu, Z. D. Nie, and D. R. S. Cumming, A wireless biomedical signal interface system-on-chip for body sensor networks, IEEE Transactions on Biomedical Circuits & Systems, vol. 4, no. 2, pp. 112-117, 2010.
[30]
T. Hayajneh, K. Griggs, M. Imran, and B. J. Mohd, Secure and efficient data delivery for fog-assisted wireless body area networks, Peer-to-Peer Networking and Applications, vol. 12, no. 5, pp. 1289-1307, 2019.
[31]
R. Hasan, S. Zawoad, S. Noor, M. M. Haque, and D. Burke, How secure is the healthcare network from insider attacks? An audit guideline for vulnerability analysis, presented at 2016 IEEE 40th Computer Software & Applications Conference, Atlanta, GA, USA, 2016, pp. 417-422.
DOI
[32]
M. Zamani, M. Movahedi, and M. Raykova, Rapidchain: Scaling blockchain via full sharding, presented at 2018 ACM SIGSAC Conference, Toronto, Canada, 2018, pp. 931-948.
DOI
[33]
E. Kokoris-Kogias, P. Jovanovic, L. Gasser, N. Gailly, E. Syta, and B. Ford, OmniLedger: A secure, scale-out, decentralized ledger via sharding, presented at 2018 IEEE Symposium on Security and Privacy, San Francisco, CA, USA, 2018, pp. 583-598.
DOI
[34]
L. Liu, W. Feng, C. Chen, Y. R. Zhang, D. P. Lan, X. M. Yuan, and S. Vashisht, BSIoT: Blockchain based software defined network framework for internet of things, presented at IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Toronto, Canada, 2020, pp. 496-501.
DOI
[35]
M. Azrour, J. Mabrouki, A. Guezzaz, and Y. Farhaoui, New enhanced authentication protocol for internet of things, Big Data Mining and Analytics, vol. 4, no. 1, pp. 1-9, 2021.
[36]
J. Z. Li, Z. H. Wang, M. H. Li, and T. F. Qin, spectrum sharing management method for the small-area blockchain based on district partition (in Chinese), Journal of Xidian University (Nat. Sci.), vol. 47, no. 6, pp. 122-130, 2020.
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Publication history

Received: 25 May 2021
Accepted: 08 July 2021
Published: 09 December 2021
Issue date: August 2022

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© The author(s) 2022

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 61761007) and the Scientific Research Project of Guangxi University Xingjian College of Science and Liberal Arts (No. Y2021ZK03).

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The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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