Abstract
As a new generation of computing paradigm for Internet of things (IoT), edge computing has been proved to be promising in solving the problems of insufficient centralized computing power, bandwidth congestion and transmission delay by distributing traditional cloud resources down to edges. While so, massive of computing resources have not been utilized due to the physical heterogeneity and allocation issues. Addressing on the two major challenges, in this paper, we propose a blockchain-based edge computing solution (MECaaS), which integrates smart contract, component interface, distributed allocation algorithm and other elements as a service. Comparing with the existing blockchain-edge computing solutions, we focus more on technical implementation than just the theoretical framework, by distributing this service to inspire devices’ self-potential in interaction, perception and decision, in further forms a distributed intelligent system. The service is deployed in a heterogeneous IoT scenario, and proved to be efficient for edge computing. Also, experimental results show that distributed resource allocation strategies perform better than centralized ways to some extent.
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References
State of the IoT 2020: 12 billion IoT connections, surpassing non-IoT for the first time, IoT Analytics, Knud Lasse Lueth, 19 November 2020
Shi, W., Cao, J., Zhang, Q., Li, Y., Xu, L.: Edge computing: vision and challenges. IEEE Internet Things J. 3(5), 637–646 (2016). https://doi.org/10.1109/JIOT.2016.2579198
Cisco: Cisco Global Cloud Index: Forecast and Methodology, 2016–2021 (2018)
Yi, S., Hao, Z., Qin, Z., Li, Q.: Fog computing: platform and applications. In: Proceedings of 3rd IEEE Workshop Hot Topics Web Syst. Technol. (HotWeb), Washington, DC, USA, 2015, pp. 73–78 (2015)
Hwang, J., Nkenyereye, L., Sung, N., Kim, J., Song, J.: IoT Service Slicing and Task Offloading for Edge Computing. IEEE Internet Things J. 8(14), 11526–11547 (2021). https://doi.org/10.1109/JIOT.2021.3052498
Novo, O.: Blockchain meets IoT: an architecture for scalable access management in IoT. IEEE Internet Things J. 5(2), 1184–1195 (2018). https://doi.org/10.1109/JIOT.2018.2812239
Zhaofeng, M., Lingyun, W., Xiaochang, W., Zhen, W., Weizhe, Z.: Blockchain-enabled decentralized trust management and secure usage control of IoT big data. IEEE Internet Things J. 7(5), 4000–4015 (2020). https://doi.org/10.1109/JIOT.2019.2960526
Özyilmaz, K.R., Doğan, M., Yurdakul, A.: IDMoB: IoT data marketplace on blockchain. In: 2018 Crypto Valley Conference on Blockchain Technology (CVCBT), Zug, pp. 11–19 (2018). https://doi.org/10.1109/CVCBT.2018.00007
Chen, R., Li, Y., Yu, Y., Li, H., Chen, X., Susilo, W.: Blockchain-based dynamic provable data possession for smart cities. IEEE Internet Things J. 7(5), 4143–4154 (2020). https://doi.org/10.1109/JIOT.2019.2963789
The Hyperledger Project. Accessed 1 July 2019. http://www.Hyperledger.org
Yu, W., et al.: A survey on the edge computing for the internet of things. IEEE Access 6, 6900–6919 (2018). https://doi.org/10.1109/ACCESS.2017.2778504
Chatzopoulos, D., Ahmadi, M., Kosta, S., Hui, P.: FlopCoin: a cryptocurrency for computation offloading. IEEE Trans. Mob. Comput. 17(5), 1062–1075 (2018). https://doi.org/10.1109/TMC.2017.2748133
Pan, J., Wang, J., Hester, A., Alqerm, I., Liu, Y., Zhao, Y.: EdgeChain: an edge-IoT framework and prototype based on blockchain and smart contracts. IEEE Internet Things J. 6(3), 4719–4732 (2019). https://doi.org/10.1109/JIOT.2018.2878154
Cui, L., Yang, S., Chen, Z., Pan, Y., Ming, Z., Xu, M.: A decentralized and trusted edge computing platform for internet of things. IEEE Internet Things J. 7(5), 3910–3922 (2020). https://doi.org/10.1109/JIOT.2019.2951619
He, Y., Wang, Y., Qiu, C., Lin, Q., Li, J., Ming, Z.: Blockchain-based edge computing resource allocation in IoT: a deep reinforcement learning approach. IEEE Internet Things J. 8(4), 2226–2237 (2021). https://doi.org/10.1109/JIOT.2020.3035437
Martinez, I., Hafid, A.S., Jarray, A.: Design, resource management, and evaluation of fog computing systems: a survey. IEEE Internet Things J. 8(4), 2494–2516 (2021). https://doi.org/10.1109/JIOT.2020.3022699
Wang, P., Yao, C., Zheng, Z., Sun, G., Song, L.: Joint task assignment, transmission, and computing resource allocation in multilayer mobile edge computing systems. IEEE Internet Things J. 6(2), 2872–2884 (2019). https://doi.org/10.1109/JIOT.2018.2876198
Tan, H., Han, Z., Li, X.-Y., Lau, F.C.M.: Online job dispatching and scheduling in edge-clouds. In: Proceedings of IEEE INFOCOM, Atlanta, GA, USA, pp. 1–9, May 2017
Shah-Mansouri, H., Wong, V.W.S.: Hierarchical fog-cloud computing for IoT systems: a computation offloading game. IEEE Internet Things J. 5(4), 3246–3257 (2018). https://doi.org/10.1109/JIOT.2018.2838022
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This work is supported by The Key Science and Technology Project of China Southern Power Grid Co., Ltd.【036000KK52210047】
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Li, B. et al. (2023). MECaaS: Mobile Edge Computing as a Services Based on Blockchain. In: Li, J., Xie, K., Hu, J., Yang, Q. (eds) The Proceedings of the 17th Annual Conference of China Electrotechnical Society. ACCES 2022. Lecture Notes in Electrical Engineering, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-99-0451-8_106
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DOI: https://doi.org/10.1007/978-981-99-0451-8_106
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