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Building a blockchain-based decentralized ecosystem for cloud and edge computing: an ALLSTAR approach and empirical study

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Abstract

Cloud computing has been one of the disruptive technologies to change the traditional application operation for the last decades. The success of Cloud boosts ever more newly-built data centers. Although these data centers are distributed all around the world, the computing resources are managed in a relatively centralized manner within one big data center. For a specific small area, the centralized Cloud lacks the dispersion to satisfy the requirements of collaborative applications, e.g., the nearest data center might still be too far to satisfy the network latency. Through spreading the computing resources at the edge of the network, the emerging Edge computing can complete the data processing before uploading to Cloud. However, Edge computing still stays at the conceptual and experimental stage. Trust and incentive model are missing to motivate the Edge node and micro Cloud owners to share the computing infrastructure resources for building a more generalized and decentralized ecosystem. Traditional method of building trust through authority is not applicable in current edge environment, which is more like peer-to-peer relationship between the customer and provider. To tackle this issue, ALLSTAR is proposed, which is a blockchain-based approach to enhance the trust for equally combining all the Cloud and Edge resources to be seamlessly leveraged by the application. The ALLSTAR approach is a systematic solution to realize decentralized resource management, including Cloud and Edge resource sharing and trading, and target at building the trustworthy ALLSTAR ecosystem. In this paper, we first analyze the challenges of utilizing distributed Cloud and Edge resources, and describe the overall architecture of ALLSTAR, including the related key techniques, detailed application development and operations processes as well as the new business model. Moreover, an empirical study on the permissioned blockchain evaluation is conducted. The study not only demonstrates the ALLSTAR approach is feasible but also provides insights of which blockchain to choose when constructing such an ecosystem.

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Notes

  1. https://www.ngi.eu/about/

  2. https://opennebula.org/

  3. https://www.openstack.org/

  4. https://bitcoin.org/en/

  5. https://www.ethereum.org/

  6. https://etherscan.io/

  7. For simplicity, Sawtooth, Iroha, Fabric, Besu, and Ethereum are used in the following text.

  8. https://github.com/ZeshunShi/ALLSTAR

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Acknowledgements

This research is partially funded by the EU Horizon 2020 research and innovation program under grant agreements No. 825134 (ARTICONF), No. 824068 (ENVRI-FAIR), and No. 862409 (BLUECLOUD). This work is also supported by the National Key Research and Development Program of China under grant 2018YFB0204301 and the Natural Science Foundation of Hunan Province under grant No. 2020JJ3042. We thank MOG Technologies for providing the crowd journalism usecase. The author, Zeshun Shi, is also sponsored by China Scholarship Council.

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    Authors and Affiliations

    1. School of Computer Science, National University of Defense Technology, Deya Road 109, Kaifu District, Changsha, China

      Huan Zhou

    2. Multiscale Networked System Group, University of Amsterdam, Science Park 904, Amsterdam, The Netherlands

      Zeshun Shi & Zhiming Zhao

    3. School of Electronic Science, National University of Defense Technology, Deya Road 109, Kaifu District, Changsha, China

      Xue Ouyang

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    1. Huan Zhou
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    Correspondence to Xue Ouyang or Zhiming Zhao.

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    This article article is part of the Topical Collection: Special Issue on Blockchain for Peer-to-Peer Computing

    Guest Editors: Keping Yu, Chunming Rong, Yang Cao, and Wenjuan Li

    Huan Zhou and Zeshun Shi contributes equally to this paper.

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    Zhou, H., Shi, Z., Ouyang, X. et al. Building a blockchain-based decentralized ecosystem for cloud and edge computing: an ALLSTAR approach and empirical study. Peer-to-Peer Netw. Appl. 14, 3578–3594 (2021). https://doi.org/10.1007/s12083-021-01198-z

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