Design of in-network caching scheme in CCN based on grey relational analysis

doi:10.1016/S1005-8885(14)60279-X

中国邮电高校学报(英文) ›› 2014, Vol. 21 ›› Issue (2): 1-8.doi: 10.1016/S1005-8885(14)60279-X

• Networks • 下一篇

Design of in-network caching scheme in CCN based on grey relational analysis

崔现东,黄韬,刘江, LI Li ,陈建亚,刘韵洁

1.State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
2. Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing 100876, China
3. Future Network Industry Innovation Center of China, Nanjing 211100, China

收稿日期:2013-09-22 修回日期:2014-01-03 出版日期:2014-04-30 发布日期:2014-04-30
通讯作者: 崔现东 E-mail:cuixdbupt@gmail.com
基金资助:
国家973项目;国家973项目;中央高校基本科研业务费专项资金

Design of in-network caching scheme in CCN based on grey relational analysis

Received:2013-09-22 Revised:2014-01-03 Online:2014-04-30 Published:2014-04-30
Contact: cui xiandong E-mail:cuixdbupt@gmail.com
Supported by:
National Basic Research Programs of China (2012CB315801, 2011CB302901), the Fundamental Research Funds for the Central Universities (2013RC0113, 2012RC0120).

摘要/Abstract

摘要：

In-network caching is one of the most important issues in content centric networking (CCN), which may extremely influence the performance of the caching system. Although much work has been done for in-network caching scheme design in CCN, most of them have not addressed the multiple network attribute parameters jointly during caching algorithm design. Hence, to fill this gap, a new in-network caching based on grey relational analysis (GRA) is proposed. The authors firstly define two newly metric parameters named request influence degree (RID) and cache replacement rate, respectively. The RID indicates the importance of one node along the content delivery path from the view of the interest packets arriving. The cache replacement rate is used to denote the caching load of the node. Then combining hops a request traveling from the users and the node traffic, four network attribute parameters are considered during the in-network caching algorithm design. Based on these four network parameters, a GRA based in-network caching algorithm is proposed, which can significantly improve the performance of CCN. Finally, extensive simulation based on ndnSIM is demonstrated that the GRA-based caching scheme can achieve the lower load in the source server and the less average hops than the existing the betweeness (Betw) scheme and the ALWAYS scheme.

关键词:

CCN, in-network caching, request influence degree, cache replacement rate, grey relational analysis

Abstract:

Key words:

CCN, in-network caching, request influence degree, cache replacement rate, grey relational analysis

参考文献

1. Jacobson V, Smetters D K, Thornton J D, et al. Networking named content. Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies (CoNEXT’09), Dec 1-4, 2009, Rome, Italy. New York, NY, USA: ACM, 2009:12p

2. Jelenkovic P, Radovanovic A, Squillante M S. Critical sizing of LRU caches with dependent requests. Journal of Applied Probability, 2006, 43(4): 1013-1027

3. Laoutaris N, Smaragdakis G, Bestavros A, et al. Distributed selfish caching. IEEE Transactions on Parallel and Distributed Systems, 2007, 18(10): 1361-1376

4. Psaras I, Clegg R G, Landa R, et al. Modelling and evaluation of CCN-caching trees. Proceedings of the 10th International IFIP TC6 Conference on Networking (NETWORKING’11): Vol 1, May 9-13, 2011,Valencia, Spain. Berlin, Germany: Springer, 2011: 78-91

5. Cho K, Lee M, Park K, et al. WAVE: popularity-based and collaborative in-network caching for content-oriented networks. Proceedings of the 2012 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS’12), Mar 25-30, 2012, Orlando, CA, USA. Piscataway, NJ, USA: IEEE, 2012: 316-321

6. Psaras I, Chai W K, Pavlou G. Probabilistic in-network caching for information-centric networks. Proceedings of the 2nd edition of the ICN Workshop on Information-centric Networking (ICN’12), Aug 13-17, 2012, Helsinki, Finland. New York, NY, USA: ACM, 2012: 55-60

7. Chai W K, He D L, Ioannis P, et al. Cache ‘less for more’ in information-centric networks. Proceedings of the 11th International IFIP TC6 Conference on Networking (NETWORKING’12), May 21-25, 2012, Prague. Berlin, Germany: Springer, 2012: 27, Czech Republic-40

8. Chai W K, He D, Psaras I, et al. Cache ‘less for more’ in Information-centric networks (extended version). Computer Communications, 2013, 36(7): 758-770

9. Deng J L. Introduction to grey system theory. The Journal of Grey System, 1989, 1(1): 1-24

10. Kuo Y, Yang T, Huang G W. The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & Industrial Engineering, 2008, 55(1): 80-93

11. Olson D L, Wu D. Simulation of fuzzy multi-attribute models for grey relationships. European Journal of Operational Research, 2006, 175(1): 111-120

12. Wu D D. Supplier selection in a fuzzy group setting: a method using grey related analysis and Dempster-Shafer theory. Expert Systems with Applications, 2009, 36(5): 8892-8899

13. Fung C P. Manufacturing process optimization for wear property of fiber-reinforced polybutylene terephthalate composites with grey relational analysis. Wear, 2003, 254(3): 298-306

14. Afanasyev A, Moiseenko I, Zhang L. ndnSIM: NDN simulator for NS-3. Technical Report NDN-0005. Los Angeles, CA, USA: University of California, 2012

15. Huang Y P, Chu H C. Simplifying fuzzy modeling by both gray relational analysis and data transformation methods. Fuzzy Sets and Systems, 1999, 104(2): 183-197

16. Spring N, Mahajan R, Wetherall D. Measuring ISP topologies with Rocketfuel. ACM SIGCOMM Computer Communication Review, 2002, 32(4): 133-145

Design of in-network caching scheme in CCN based on grey relational analysis

Design of in-network caching scheme in CCN based on grey relational analysis

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价