UAV deployment and caching scheme based on user preference prediction

Jiazhi REN; Hui TIAN; Shaoshuai FAN; Yuanzhuo LIN; Gaofeng NIE; Jilong LI

doi:10.11959/j.issn.1000-436x.2020104

您当前的位置：

首页 >

文章列表页 >

UAV deployment and caching scheme based on user preference prediction

Papers | 更新时间：2024-06-05

- UAV deployment and caching scheme based on user preference prediction
- Journal on Communications Vol. 41, Issue 6, Pages: 1-13(2020)
- 作者机构：
  
  1. 北京邮电大学网络与交换技术国家重点实验室，北京 100876
  2. 国家广播电视总局广播电视科学研究院，北京 100866
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61801044)
- DOI：10.11959/j.issn.1000-436x.2020104
  CLC： TN929.53
- Online First：2020-06，
  
  Published：25 June 2020
- 稿件说明：
移动端阅览
Jiazhi REN, Hui TIAN, Shaoshuai FAN, et al. UAV deployment and caching scheme based on user preference prediction[J]. Journal on Communications, 2020, 41(6): 1-13.
DOI：

Jiazhi REN, Hui TIAN, Shaoshuai FAN, et al. UAV deployment and caching scheme based on user preference prediction[J]. Journal on Communications, 2020, 41(6): 1-13. DOI： 10.11959/j.issn.1000-436x.2020104.

摘要

针对蜂窝网络中的缓存问题，考虑用户内容请求的空间异构性及时间波动性，提出了一种基于单个用户内容偏好预测的蜂窝网中无人机位置部署及缓存内容部署方案。首先基于用户的历史上下文信息，利用文件相似性及用户相似性来预测每个用户的内容偏好特性，并使用一种基于线性回归的方法来预测用户未来发起内容请求时的位置和时间；然后根据预测的地理位置、请求时间和内容偏好，分别利用基于自组织映射神经网络（SOM）的聚类算法和基于凝聚嵌套（AGNES）的分簇算法设计无人机的部署位置，并根据相应的无人机位置设计内容部署方案。仿真结果表明，所提算法在缓存命中率和时延性能上均优于对比算法。对真实数据集的分析结果表明，不同的用户特征对内容偏好影响权重不等，因此需要对不同的用户特征赋予合理的权值。

Abstract

In order to design an efficient edge caching policy considering spatial heterogeneity and temporal fluctuations of users’ content requests

a proactive caching scheme was proposed with UAV’s deployment location design based on user preference prediction.Firstly

each user’s preference characteristics were predicted based on file similarity and user similarity

and the request time and user location were also predicted when a content request occurs.Thereafter

on the basis of the predicted geographical location

request time and user preference

each UAV’s deployment location and the corresponding content placement were determined by virtue of clustering method based on SOM and AGNES.Simulation results show that the proposed scheme outperforms other three comparison schemes in terms of hit ratio and transmission delay.Furthermore

the results also reveal that content preference is correlated with different user features by different weights.Accordingly

different impact weights should be matched with different user features.

关键词

Keywords

references

WANG X F , CHEN M , TALEB T , et al . Cache in the air:exploiting content caching and delivery techniques for 5G systems [J ] . IEEE Communications Magazine , 2014 , 52 ( 2 ): 131 - 139 .

张平 , 陶运铮 , 张治 . 5G 若干关键技术评述 [J ] . 通信学报 , 2016 , 37 ( 7 ): 15 - 29 .

ZHANG P , TAO Y Z , ZHANG Z . Survey of several key technologies for 5G [J ] . Journal on Communications , 2016 , 37 ( 7 ): 15 - 29 .

张平 , 牛凯 , 田辉 , 等 . 6G 移动通信技术展望 [J ] . 通信学报 , 2019 , 40 ( 1 ): 141 - 148 .

ZHANG P , NIU K , TIAN H , et al . Technology prospect of 6G mobile communications [J ] . Journal on Communications , 2019 , 40 ( 1 ): 141 - 148 .

MOHAMMAD M A , DENIZ G . Fundamental limits of coded caching:improved delivery rate-cache capacity tradeoff [J ] . IEEE Transactions on Communications , 2017 , 65 ( 2 ): 806 - 815 .

LI B , FEI Z S , ZHANG Y . UAV communications for 5G and beyond:recent advances and future trends [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 2 ): 2241 - 2263 .

ARMIR B , PALAZZI C E , RONZANI D . A comparison of stateless position-based packet routing algorithms for FANETs [J ] . IEEE Transactions on Mobile Computing , 2018 , 17 ( 11 ): 2468 - 2482 .

ZHANG S W , ZENG Y , ZHANG R . Cellular-enabled UAV communication:a connectivity-constrained trajectory optimization perspective [J ] . IEEE Transactions on Communications , 2019 , 67 ( 3 ): 2580 - 2604 .

CHENG N , XU W C , SHI W S , et al . Air-ground integrated mobile edge networks:architecture,challenges,and opportunities [J ] . IEEE Communications Magazine , 2018 , 56 ( 8 ): 26 - 32 .

3GPP.New SID on enhanced support for aerial vehicles:RP-170779 [R ] .(2017-03-06)[2019-10-17 ] .

3GPP.Study on enhanced LTE support for aerial vehicles:TR36.777-f00 [R ] .(2017-12)[2019-10-17 ] .

3GPP.New WID on enhanced LTE support for aerial vehicles:RP-172826 [R ] .(2017-12-18)[2019-10-17 ] .

3GPP.New WID on UE conformance test aspects – enhanced LTE support for aerial vehicles:RP-182324 [R ] .(2018-12-10)[2019-10-17 ] .

3GPP.Draft New WID on NR enhancements for UAV:RP-192451 [R ] .(2019-12-09)[2020-04-14 ] .

3GPP.email discussion summary on Rel-17 NR UAV:RP-192452 [R ] .(2019-12-09)[2020-04-14 ] .

3GPP.discussion on NR-UAV for Rel-17:RP-192578 [R ] .(2019-12-09)[2020-04-14 ] .

ZHANG H , SONG L , HAN Z , et al . Cooperation techniques for a cellular internet of unmanned aerial vehicles [J ] . IEEE Wireless Communications , 2019 , 26 ( 5 ): 1 - 7 .

FOTOUHI A , QIANG H , DING M , et al . Survey on UAV cellular communications:practical aspects,standardization advancements,regulation,and security challenges [J ] . IEEE Communications Surveys＆ Tutorials , 2019 , 21 ( 4 ): 3417 - 3442 .

MOZAFFARI M , SAAD W , BENNIS M , et al . A tutorial on UAVs for wireless networks:applications,challenges,and open problems [J ] . IEEE Communications Surveys ＆ Tutorials , 2019 , 21 ( 3 ): 2334 - 2360 .

BOR-YALINIZ I , SALEM M , SENERATH G , et al . Is 5G ready for drones:a look into contemporary and prospective wireless networks from a standardization perspective [J ] . IEEE Wireless Communications , 2019 , 26 ( 1 ): 18 - 27 .

CHEN M , MOZAFFARI M , SAAD W , et al . Caching in the sky:proactive deployment of cache-enabled unmanned aerial vehicles for optimized quality-of-experience [J ] . IEEE Journal on Selected Areas in Communications , 2017 , 35 ( 5 ): 1046 - 1061 .

XU X , ZENG Y , GUAN Y L , et al . Overcoming endurance issue:UAV-enabled communications with proactive caching [J ] . IEEE Journal on Selected Areas in Communications , 2018 , 36 ( 7 ): 1231 - 1244 .

ZHAO N , CHENG F , YU F R , et al . Caching UAV assisted secure transmission in hyper-dense networks based on interference alignment [J ] . IEEE Transactions on Communications , 2018 , 66 ( 5 ): 2281 - 2294 .

FANG T , TIAN H , ZHANG X , et al . Context-aware caching distribution and UAV deployment:a game-theoretic approach [J ] . Applied Sciences , 2018 , 8 ( 10 ): 1 - 15 .

LI L , XU Y , ZHANG Z , et al . A prediction-based charging policy and interference mitigation approach in the wireless powered Internet of things [J ] . IEEE Journal on Selected Areas in Communications , 2019 , 37 ( 2 ): 439 - 451 .

SUN Y , XU D , NG D W K , et al . Optimal 3D-trajectory design and resource allocation for solar-powered UAV communication systems [J ] . IEEE Transactions on Communications , 2019 , 67 ( 6 ): 4281 - 4298 .

ZENG Y , ZHANG R . Energy-efficient UAV communication with trajectory optimization [J ] . IEEE Transactions on Wireless Communications , 2017 , 16 ( 6 ): 3747 - 3760 .

BRESLAU L , CAO P , FAN L , et al . Web caching and Zipf-like distributions:evidence and implications [C ] // International Conference on Computer Communications . Piscataway:IEEE Press , 1999 :1.

HASSLINGER G , NTOUGIAS K , HASSLINGER F , et al . Performance evaluation for new Web caching strategies combining LRU with score based object selection [J ] . Computer Networks , 2017 ( 125 ): 172 - 186 .

HE S , TIAN H , LYU X C . Edge popularity prediction based on social-driven propagation dynamics [J ] . IEEE Communications Letters , 2017 , 21 ( 5 ): 1027 - 1030 .

HOU L , LEI L , ZHENG K , et al . A Q-learning based proactive caching strategy for non-safety related services in vehicular networks [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 3 ): 4512 - 4520 .

WANG R , PENG X , ZHANG J , , et al . Mobility-aware caching for content-centric wireless networks:modeling and methodology [J ] . IEEE Communications Magazine , 2016 , 54 ( 8 ): 77 - 83 .

RHEE I , . CRAWDAD dataset [DB ] .(2009-06)[2019-10-17 ] .

GONZALEZ M C , HIDALGO C A , BARABASI A L . Understanding individual human mobility patterns [J ] . Nature , 2008 , 453 ( 7196 ): 779 - 782 .

LEE J , SUN M X , LEBANON G . A comprehensive study of collaborative filtering algorithms [J ] . Cornell University,arXiv:Dos.3193 ,(2012-05-14)[2019-10-17 ] .

KOHONEN T . Self-organized formation of topologically correct feature maps [J ] . Biological Cybernetics , 1982 , 43 ( 1 ): 59 - 69 .

KOHONEN T . An introduction to neural computing [J ] . Neural Networks , 1988 , 1 ( 1 ): 3 - 16 .

KOHONEN T . Self-organizing maps [M ] . 3rd ed . Berlin : SpringerPress , 2001 .

KAUFMAN L , ROUSSEEUW P J . Clustering by means of medoid [M ] . Amsterdam : ElsevierPress , 1987 .

KAUFMAN L , ROUSSEEUW P J . Finding groups in data:an introduction to cluster analysis [M ] . New York : John Weiley ＆ SonsPress , 1990 .

ZHANG T , RAMAKRISHNAN R , LIVNY M . BIRCH:an efficient data clustering method for very large databases [C ] // Proceedings of the ACM SIGMOD International Conference on Management of Data . New York:ACM Press , 1996 : 103 - 114 .

GUHA S , RASTOGI R , SHIM K . ROCK:a robust clustering algorithm for categorical attributes [C ] // Proceedings of the 15th International Conference on Data Engineering . Piscataway:IEEE Press , 1999 : 512 - 521 .

周志华 . 机器学习 [M ] . 北京 : 清华大学出版社 , 2016 .

ZHOU Z H . Machine learning [M ] . Beijing : Tsinghua University PressPress , 2016 .

GOLREZAEI N , SHANMUGAM K , DIMAKIS A G , et al . FemtoCaching:wireless video content delivery through distributed caching helpers [C ] // International Conference on Computer Communications . Piscataway:IEEE Press , 2012 : 1107 - 1115 .

NEMHAUSER G L , WOLSEY L A , FISHER M L . An analysis of approximations for maximizing submodular set functions I [J ] . Mathematical Programming , 1978 , 14 ( 1 ): 265 - 294 .

MAXWELL H F , JOSEPH A K . The MovieLens datasets:history and context [J ] . ACM Transactions on Interactive Intelligent Systems , 2015 , 5 ( 4 ): 1 - 19 .

CHO E , MYERS S A , LESKOVEC J . Friendship and mobility:user movement in location-based social networks [C ] // ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York:ACM Press , 2011 : 1 - 9 .

Views

1614

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Optimization of air-ground cooperative communication performance for UAV-mounted STAR-RIS

Security-driven service caching and computation offloading strategy in air-ground collaborative edge computing networks

Edge caching strategy based on multi-agent deep reinforcement learning in cloud-edge-end scenarios

Multi-agent caching distribution strategy for content freshness guarantee in IoV

Research on task offloading and resource allocation in edge computing network of RIS assisted UAV based on Lyapunov

Related Author

Wang Erfu

Zhou Tao

Han Zhengjiang

GUO Lei

LU Weidang

SI Peiyuan

LU Haiquan

HAN Huimei

Related Institution

Electronic Engineering College, Heilongjiang University

Institute of Intelligent Communication and Network Security, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications

School of Computing, Nanyang Technological University

National Mobile Communications Research Laboratory, Southeast University

College of Information Engineering, Zhejiang University of Technology

AI问答

⁰