雾网络中在线缓存方案设计

doi:10.19665/j.issn1001-2400.2022.02.005

西安电子科技大学学报 ›› 2022, Vol. 49 ›› Issue (2): 36-41.doi: 10.19665/j.issn1001-2400.2022.02.005

雾网络中在线缓存方案设计

孙蓉^1,²(),郑慧慧³(),刘景伟⁴()

1.西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西西安 710071
2.华侨大学厦门市移动多媒体通信重点实验室,福建厦门 361021
3.中原银行股份有限公司,河南郑州 450000
4.西安电子科技大学陕西省区块链与安全计算重点实验室,陕西西安 710071

收稿日期:2020-09-14 出版日期:2022-04-20 发布日期:2022-05-31
作者简介:孙蓉(1976—),女,副教授,博士,E-mail: rsun@mail.xidian.edu.cn;|郑慧慧(1992—),女,工程师,硕士,E-mail: zhenghuihui@zybank.com.cn;|刘景伟(1978—),男,副教授,博士,E-mail: jwliu@mail.xidian.edu.cn
基金资助:
装备预先研究(30604020102);陕西省重点研发计划重点产业创新链(2020ZDLGY05-04);陕西省重点研发计划重点产业创新链(2019ZDLGY13-05);陕西省重点研发计划重点产业创新链(2019ZDLGY12-01)

Design of an online caching scheme in fog networks

SUN Rong^1,²(),ZHENG Huihui³(),LIU Jingwei⁴()

1. State Key Laboratory of Integrated Services Networks,Xidian University,Xi’an 710071,China
2. Xiamen Key Laboratory of Mobile Multimedia Communications,Huaqiao University,Xiamen 361021,China
3. Zhong Yuan Bank Co.,Ltd,Zhengzhou 450000,China
4. Shaanxi Key Laboratory of Blockchain and Secure Computing,Xidian University,Xi’an 710071,China

Received:2020-09-14 Online:2022-04-20 Published:2022-05-31

摘要/Abstract

摘要：

5G网络中将会部署大量的超密集边缘设备,在边缘设备附近放置和处理数据,可以避免不必要的网络数据传输,减少网络传输时延。雾计算网络将云服务的能力扩展到网络边缘,通过近距离地为终端提供计算、存储和通信等服务,能够有效地降低系统数据传输时延。在5G愿景的驱动下,针对雾计算网络的数据存储,提出了一种利用编码缓存技术在雾计算网络中快速获取数据的有效方案——雾网络缓存架构,解决了缓存资源分配和数据传输问题。首先将基于雾网络的缓存架构建模为两跳网络,并为两跳网络提出一种基于文件分割和极大最小距离可分码的去中心化在线编码缓存方案。该方案通过合理设计服务器文件更新方法以及中继和用户的缓存更新策略,保证了服务器文件与中继和用户的缓存文件的一致性,使得中继和用户的缓存内容保持有效性。然后通过仿真分析了两跳网络的缓存内存和传输负载之间的关系。仿真结果证明了所提出的方案具有较低的传输负载,能够有效地缓解网络拥塞。

关键词: 雾计算, 在线缓存, 去中心化, 传输负载

Abstract:

Driven by the vision of 5G communications,an efficient solution which applies the coded caching technology to obtain data quickly in fog networks is proposed.First,this paper models the cache architecture based on the fog computing networks as the two-hop network,and proposes a decentralized online coded caching scheme based on file splitting and MDS encoding for the two-hop network.This scheme ensures that the cache content of relays and users is consistent with the files in the server by updating the server files and updating the cache content of relays and users,so as to maintain the validity of the cache content.We then analyze the tradeoff between the cache memory and the traffic load for two-hop networks where each relay and user has limited cache memories.Simulation results show that the proposed schemes have a low transmission load and can relieve network congestion effectively.

Key words: fog computing, online caching, decentralization, traffic load

中图分类号:

TN919.2

孙蓉,郑慧慧,刘景伟. 雾网络中在线缓存方案设计[J]. 西安电子科技大学学报, 2022, 49(2): 36-41.

SUN Rong,ZHENG Huihui,LIU Jingwei. Design of an online caching scheme in fog networks[J]. Journal of Xidian University, 2022, 49(2): 36-41.

图/表 3

参考文献 15

[1]	MAO Y, YOU C, ZHANG J, et al. A Survey on Mobile Edge Computing:The Communication Perspective[J], IEEE Communications Surveys & Tutorials, 2017, 19(4):2322-2358.
[2]	王忍, 王翊, 胡艳军, 等. 超密集异构网络中过载MEC服务器的协作卸载[J]. 西安电子科技大学学报, 2020, 47(2):126-134.
	WANG Ren, WANG Yi, HU Yanjun, et al, Collaborative Offloading of Overloaded Mec Servers In Ultra-Dense Heterogeneous Networks[J]. Journal of Xidian University, 2020, 47(2):126-134.
[3]	HU P, DHELIM S, NING H, et al. Survey on Fog Computing:Architecture,Key Technologies,Applications and Open Issues[J]. Journal of Network and Computer Applications, 2017, 98(15):27-42. doi: 10.1016/j.jnca.2017.09.002
[4]	BONOMI F, MILITO R, ZHU J, et al. Fog Computing and Its Role in the Internet of Things[C]// Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing.Helsinki:ACM, 2012:13-16.
[5]	胡骞, 武穆清, 郭嵩, 等. 一种用于内容中心网络的缓存随机放置策略[J]. 西安电子科技大学学报, 2014, 41(6):131-136.
	HU Qian, WU Muqing, GUO Song, et al. Random Cache Placement Strategy For Content-Centric Networking[J]. Journal of Xidian University, 2014, 41(6):131-136.
[6]	MADDAH-ALI M A, NIESEN U. Fundamental Limits of Caching[J]. IEEE Transactions on Information Theory, 2014, 60(5):2856-2867. doi: 10.1109/TIT.2014.2306938
[7]	MADDAH-ALI M A, NIESEN U. Decentralized Coded Caching Attains Order-Optimal MemoryRate Tradeoff[J]. IEEE/ACM Transactions on Networking, 2015, 23(4):1029-1040. doi: 10.1109/TNET.2014.2317316
[8]	YU Q, MADDAH-ALI M A, AVESTIMEHR A S. The Exact Rate-Memory Tradeoff for Caching with Uncoded Prefetching[J]. IEEE Transactions on Information Theory, 2018, 64(2):1281-1296. doi: 10.1109/TIT.2017.2785237
[9]	GHASEMI H, RAMAMOORTHY A. Improved Lower Bounds for Coded Caching[J]. IEEE Transactions on Information Theory, 2017, 63(7):4388-4413. doi: 10.1109/TIT.2017.2705166
[10]	NIESEN U, MADDAH-ALI M A. Coded Caching with Nonuniform Demands[J]. IEEE Transactions on Information Theory, 2017, 63(2):1146-1158. doi: 10.1109/TIT.2016.2639522
[11]	JI M, TULINO A M, LLORCA J, et al. On The Average Performance Of Caching And Coded Multicasting With Random Demands[C]// Proceedings of 2014 11th International Symposium on Wireless Communications Systems.Piscataway:IEEE, 2014:922-926.
[12]	SHARIATPANAHI S P, MOTAHARI S A, KHALAJ B H. Multi-Server Coded Caching[J]. IEEE Transactions on Information Theory, 2016, 62(12):7253-7271. doi: 10.1109/TIT.2016.2614722
[13]	MITAL N, GüNDüZ D, LING C. Coded Caching In A Multi-Server System With Random Topology[C]// Proceedings of 2018 IEEE Wireless Communications and Networking Conference.Piscataway:IEEE, 2018:1-6.
[14]	PEDARSANI R, MADDAH-ALI M A, NIESEN U. Online Coded Caching[J]. IEEE/ACM Transactions on Networking, 2016, 24(2):836-845. doi: 10.1109/TNET.2015.2394482
[15]	YAN Q, PARAMPALLI U, TANG X, et al. Online Coded Caching With Random Access[J]. IEEE Communications Letters, 2016, 21(3):552-555. doi: 10.1109/LCOMM.2016.2631552

雾网络中在线缓存方案设计

Design of an online caching scheme in fog networks

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 3

参考文献 15

相关文章 2

Metrics

本文评价

推荐阅读 10

[1]	刘锦辉,易必杰,张昊. 面向雾计算的嵌入式异构计算服务放置策略[J]. 西安电子科技大学学报, 2021, 48(6): 40-47.
[2]	王慧,王励成,柏雪,刘清华,沈晓鹰. 区块链隐私保护和扩容关键技术研究[J]. 西安电子科技大学学报, 2020, 47(5): 28-39.