期刊文献+

A Caching Strategy Based on Many-to-Many Matching Game in D2D Networks 被引量:1

原文传递
导出
摘要 Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.
出处 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2021年第6期857-868,共12页 清华大学学报(自然科学版(英文版)
基金 supported by the Fundamental Research Funds for the Central Universities (Nos.FRF-DF-20-12 and FRF-GF-18-017B)。
  • 相关文献

参考文献6

二级参考文献36

  • 1X. Zheng, Z. Cai, J. Li, and H. Gao, Scheduling flows with multiple service frequency constraints, IEEE Internet of Things, 2016, doi: 10.1109/JIOT.2016.2577630.
  • 2J. Li, Z. Cai, M. Yan, and Y. Li, Using crowdsourced data in location-based social networks to explore influence maximization, in Proc. 2016 IEEE Conference on Computer Communications (INFOCOM), San Francisco, CA, USA, 2016.
  • 3Z. Duan, M. Yan, Z. Cai, X. Wang, M. Han, and Y. Li, Truthful incentive mechanisms for social cost minimization in mobile crowdsourcing systems, Sensors, vol. 16, no. 4, pp. 481--493, 2016.
  • 4X. Zheng, Z. Cai, J. Li, and H. Gao, An application- aware scheduling policy for real-time traffic, in Proc. 35th International Conference on Distributed Computing Systems (ICDCS), Columbus, OH, USA, 2015, pp. 421- 430.
  • 5S. Li, J. Xu, M. D. Schaar, and W. Li, Popularity- driven content caching, in Proc. 2016 IEEE Conference on Computer Communications (INFOCOM), San Francisco, CA, USA, 2016.
  • 6Amazon CloudFront, http://aws.amazon.corn/cloudfront/ details/, 2016.
  • 7. E. Nygren, R. K. Sitaraman, and J. Sun, The akamai network: A platform for high-performance internet applications, ACM SIGOPS Operating Systems Review, vol. 44, no. 3, pp. 2-19, 2010.
  • 8L. Muscariello, G. Carofiglio, and M. Gallo, Bandwidth and storage sharing performance in information centric networking, in Proc. 2011 SIGCOMM Workshop on Information-Centric Networking, Toronto, ON, Canada, 2011, pp. 26-31.
  • 9B. Tan and L. Massoulile, Optimal content placement for peer-to-peer video-on-demand systems, Transactions on Networking (TON), vol. 21, no. 2, pp. 566-579, 2013.
  • 10M. Dehghan L. Massoulie, D. Towsley, D. Menasche, and Y. C. Tay, A utility optimization approach to network cache design, in Proc. 2016 IEEE Conference on Computer Communications (1NFOCOM), San Francisco, CA, USA, 2016.

共引文献7

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部