基于联盟链的运营商最佳缓存策略

姜静; 王凯; 许曰强; 杜剑波; 仇超; 巩译

doi:10.11999/JEIT220374

基于联盟链的运营商最佳缓存策略

doi: 10.11999/JEIT220374

姜静¹,
王凯^1, ,,
许曰强²,
杜剑波¹,
仇超³,
巩译⁴

1.
西安邮电大学陕西信息通信网络与安全重点实验室西安 710121
2.
北京邮电大学信息与通信工程学院北京 100876
3.
天津大学智能与计算学部天津 300350
4.
北京信息科技大学信息与通信工程学院北京 100192

基金项目: 国家自然科学基金(61871321, 61901367, 62101442)，国家科技重大专项(2016ZX03001016-004), 陕西自然科学基金(2020JQ-84)，陕西省教育厅专项科研计划(20JK0918)，陕西省教育厅服务地方专项(21JC032)

详细信息

作者简介:
姜静：女，教授，研究方向为边缘计算、人工智能及通感算一体化设计

王凯：男，硕士生，研究方向为边缘计算、区块链技术

许曰强：男，博士生，研究方向为边缘计算、区块链技术、人工智能

杜剑波：女，副教授，研究方向为边缘计算、资源分配、区块链技术、人工智能

仇超：女，讲师，研究方向为算力网络、区块链、边缘智能

巩译：女，副教授，研究方向为无线通信、区块链技术

通讯作者:
王凯　wk@stu.xupt.edu.cn

中图分类号: TN92
计量
- 文章访问数: 512
- HTML全文浏览量: 220
- PDF下载量: 83
- 被引次数: 0
出版历程
- 收稿日期: 2022-03-31
- 修回日期: 2022-07-31
- 录用日期: 2022-08-01
- 网络出版日期: 2022-08-03
- 刊出日期: 2022-09-19

Optimal Caching Strategy of Operators Based on Consortium Blockchain

1.
Shaanxi Key Laboratory of Information Communication Network and Security, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
2.
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
3.
College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
4.
School of Information & Communication Engineering, Beijing Information Science & Technology University, Beijing 100192, China

Funds: The National Natural Science Foundation of China (61871321, 61901367, 62101442), The National Science and Technology Major Project of China (2016ZX03001016-004), The Natural Science Foundation of Shaanxi Province (2020JQ-84), The Special Scientific Research Projects of Department of Education of Shaanxi Provincial (20JK0918), The Serving Local Special Scientific Research Project of Education Department of Shaanxi Province (21JC032)

摘要

摘要: 基于区块链的边缘缓存技术可以实现更大范围的内容共享并提高缓存内容的使用效率。针对不同运营商各自建设边缘设备，缓存内容相互隔离，难以共享信息的问题，该文提出一种基于联盟链的边缘缓存系统框架并设计了内容共享和交易流程，实现了不同运营商之间的内容共享。此外，为了降低高维缓存节点的共识开销，设计了基于内容缓存的部分实用拜占庭容错(pPBFT)共识机制，仅选取缓存相关内容的联盟链节点作为验证智能合约的执行节点。最后，将运营商内容共享所带来的收益进行量化并构建为最大化收益的优化问题。通过所提出的内容缓存算法，得到了最优缓存决策的闭式表达式和与内容流行度相关的最优缓存策略。仿真结果表明，在该框架中所提出的共识机制和缓存策略能够有效增加运营商的缓存收益。
- 边缘缓存 /
- 区块链 /
- 共识机制 /
- 内容共享
Abstract: The edge caching based on blockchain will achieve a wider range of content sharing, and enhance the efficiency of caching contents. However, different operators build their own edge devices and the cached contents are isolated and have difficulty in sharing information. In this paper, a blockchain-based edge caching system framework and a content sharing and transaction process is proposed, which can realize content sharing between different operators. In addition, a partial Practical Byzantine Fault Tolerant (pPBFT) consensus mechanism based on content caching is designed to reduce the consensus cost of high-dimensional caching nodes, in which only the consortium nodes that cache the relevant content can be selected as execution nodes for validating smart contracts. Finally, through quantifying the benefit obtained by operators' content sharing, the closed-form optimal solution is derived with the aim to maximize the profit by adopting the proposed content caching strategy, and the optimal caching strategy related to the popularity of the content is further developed. Simulation results show that the proposed consensus mechanism and caching strategy based on this framework can effectively increase the operator's caching revenue.
- Edge caching /
- Blockchain /
- Consensus mechanism /
- Content sharing

HTML全文

图 1 基于联盟链的运营商边缘缓存系统框架

下载: 全尺寸图片幻灯片

图 2 基于联盟链的运营商边缘缓存系统内容共享及交易过程

下载: 全尺寸图片幻灯片

图 3 时隙t的pPBFT共识机制

下载: 全尺寸图片幻灯片

图 4 不同共识方案下节点数量与开销关系

下载: 全尺寸图片幻灯片

图 5 缓存空间与缓存平均收益关系

下载: 全尺寸图片幻灯片

图 6 不同内容缓存数据量比较

下载: 全尺寸图片幻灯片

图 7 偏斜参数与缓存平均收益关系

下载: 全尺寸图片幻灯片

参考文献(18)

[1]	CISCO. Cisco visual networking index: Global mobile data traffic forecast update, 2017–2022[EB/OL]. https://branden.biz/wp-content/uploads/2019/05/white-paper-c11-738429.pdf, 2019.
[2]	SHERAZ M, AHMED M, HOU Xueshi, et al. Artificial intelligence for wireless caching: Schemes, performance, and challenges[J]. IEEE Communications Surveys & Tutorials, 2021, 23(1): 631–661. doi: 10.1109/COMST.2020.3008362
[3]	GUO Shaoyong, HU Xing, GUO Song, et al. Blockchain meets edge computing: A distributed and trusted authentication system[J]. IEEE Transactions on Industrial Informatics, 2020, 16(3): 1972–1983. doi: 10.1109/TII.2019.2938001
[4]	YOU Xiaohu, WANG Chengxiang, HUANG Jie, et al. Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts[J]. Science China Information Sciences, 2021, 64(1): 110301. doi: 10.1007/s11432-020-2955-6
[5]	SUN Wen, LI Sheng, and ZHANG Yan. Edge caching in blockchain empowered 6G[J]. China Communications, 2021, 18(1): 1–17. doi: 10.23919/JCC.2021.01.001
[6]	WANG Hongman, LI Yingxue, ZHAO Xiaoqi, et al. An algorithm based on Markov chain to improve edge cache hit ratio for blockchain-enabled IoT[J]. China Communications, 2020, 17(9): 66–76. doi: 10.23919/JCC.2020.09.006
[7]	LIU Jiadi, GUO Songtao, SHI Yawei, et al. Decentralized caching framework toward edge network based on blockchain[J]. IEEE Internet of Things Journal, 2020, 7(9): 9158–9174. doi: 10.1109/JIOT.2020.3003700
[8]	LIN Yuanzhuo, TIAN Hui, REN Jiazhi, et al. Caching and pricing based on blockchain in a cache-delivery market[C]. 2020 IEEE Wireless Communications and Networking Conference, Seoul, Korea (South), 2020: 1–7.
[9]	CHEN Mengqi, WU Guangming, ZHANG Yuhuang, et al. Distributed deep reinforcement learning-based content caching in edge computing-enabled blockchain networks[C]. 2021 13th International Conference on Wireless Communications and Signal Processing, Changsha, China, 2021: 1–5.
[10]	牛淑芬, 杨平平, 谢亚亚, 等. 区块链上基于云辅助的密文策略属性基数据共享加密方案[J]. 电子与信息学报, 2021, 43(7): 1864–1871. doi: 10.11999/JEIT200124 NIU Shufen, YANG Pingping, XIE Yaya, et al. Cloud-assisted Ciphertext policy attribute based Eencryption data sharing encryption scheme based on BlockChain[J]. Journal of Electronics &Information Technology, 2021, 43(7): 1864–1871. doi: 10.11999/JEIT200124
[11]	DAVENPORT A and SHETTY S. Air gapped wallet schemes and private key leakage in permissioned blockchain platforms[C]. 2019 IEEE International Conference on Blockchain, Atlanta, USA, 2019: 541–545.
[12]	ZHENG Peilin, XU Quangqing, ZHENG Zibin, et al. Meepo: Sharded consortium blockchain[C]. 2021 IEEE 37th International Conference on Data Engineering, Chania, Greece, 2021: 1847–1852.
[13]	ZHANG Ran, YU F R, LIU Jiang, et al. Deep Reinforcement Learning (DRL)-based Device-to-Device (D2D) caching with blockchain and mobile edge computing[J]. IEEE Transactions on Wireless Communications, 2020, 19(10): 6469–6485. doi: 10.1109/TWC.2020.3003454
[14]	LAO L, DAI Xiaohai, XIAO Bin, et al. G-PBFT: A location-based and scalable consensus protocol for IoT-Blockchain applications[C]. 2020 IEEE International Parallel and Distributed Processing Symposium, New Orleans, USA, 2020: 664–673.
[15]	PRENEEL B. Cryptographic hash functions[J]. European Transactions on Telecommunications, 1994, 5(4): 431–448. doi: 10.1002/ett.4460050406
[16]	刘浩洋, 王钢, 杨文超, 等. 基于随机几何理论的流行度匹配边缘缓存策略[J]. 电子与信息学报, 2021, 43(12): 3427–3433. doi: 10.11999/JEIT210493 LIU Haoyang, WANG Gang, YANG Wenchao, et al. Popularity matching edge caching policy based on stochastic geometry theory[J]. Journal of Electronics &Information Technology, 2021, 43(12): 3427–3433. doi: 10.11999/JEIT210493
[17]	ZHAN Yufeng, LIU C H, ZHAO Yinuo, et al. Free market of multi-leader multi-follower mobile crowdsensing: An incentive mechanism design by deep reinforcement learning[J]. IEEE Transactions on Mobile Computing, 2020, 19(10): 2316–2329. doi: 10.1109/TMC.2019.2927314
[18]	LIN Peng, SONG Qingyang, YU F R, et al. Task offloading for wireless VR-enabled medical treatment with blockchain security using collective reinforcement learning[J]. IEEE Internet of Things Journal, 2021, 8(21): 15749–15761. doi: 10.1109/JIOT.2021.3051419