Dynamical replacement policy based on cost and popularity in named data networking

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (12): 3369-3372.

• Network and communications • Next Articles

Dynamical replacement policy based on cost and popularity in named data networking

HUANG Sheng,TENG Mingnian,CHEN Shenglan,LIU Huanlin,XIANG Jinsong

Key Laboratory of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Received:2014-06-19 Revised:2014-08-09 Online:2014-12-31 Published:2014-12-01
Contact: TENG Mingnian

命名数据网络中基于数据请求代价与流行度的动态替换策略

黄胜,滕明埝,陈胜蓝,刘焕淋,向劲松

重庆邮电大学光纤通信技术重点实验室,重庆 400065

通讯作者: 滕明埝
作者简介:黄胜(1974-),男,湖北英山人,教授,博士,主要研究方向:未来互联网体系结构、计算机网络、光网络；滕明埝(1991-),男,重庆人,硕士研究生,主要研究方向:未来互联网数据存储策略；陈胜蓝(1986-),男,重庆人,硕士研究生,主要研究方向:未来互联网数据存储策略；刘焕淋(1970-),女,重庆人,教授,博士,主要研究方向:宽带网络技术、光纤通信、光交换技术；向劲松(1975-),男,重庆人,副教授,博士,主要研究方向:空间光通信。
基金资助:
国家自然科学基金资助项目;重庆市自然科学基金资助项目;重庆市教委科学技术研究项目

Abstract

Abstract:

In view of the problem that data for Named Data Networking (NDN) cache is replaced efficiently, a new replacement policy that considered popularity and request cost of data was proposed in this paper. It dynamically allocated proportion of popularity factor and request cost factor according to the interval time between the two requests of the same data. Therefore, nodes would cache data with high popularity and request cost. Users could get data from local node when requesting data next time, so it could reduce the response time of data request and reduce link congestion. The simulation results show that the proposed replacement policy can efficiently improve the in-network hit rate, reduce the delay and distance for users to fetch data.

摘要：

针对怎样高效地对命名数据网络(NDN)缓存中的数据进行替换的问题,提出了一种综合考虑数据流行度与数据请求代价的数据替换策略。该策略根据数据的请求时间间隔动态地分配数据流行度因子与数据请求代价因子的比重,使节点缓存高流行度与高请求代价的数据。当用户下次请求数据时能够从本节点获取,降低数据请求的响应时间并减少链路拥塞。仿真结果表明,本策略能够有效提高网内存储命中率,降低用户获取数据的时间以及缩短用户获取数据的距离。

CLC Number:

TP393

HUANG Sheng TENG Mingnian CHEN Shenglan LIU Huanlin XIANG Jinsong. Dynamical replacement policy based on cost and popularity in named data networking[J]. Journal of Computer Applications, 2014, 34(12): 3369-3372.

黄胜滕明埝陈胜蓝刘焕淋向劲松. 命名数据网络中基于数据请求代价与流行度的动态替换策略[J]. 计算机应用, 2014, 34(12): 3369-3372.

References

［1］XIE G, ZHANG Y, LI Z, et al. A survey on future Internet architecture［J］. Chinese Journal of Computers,2012,35(6):1109-1119.(谢高岗, 张玉军, 李振宇, 等. 未来互联网体系结构研究综述［J］. 计算机学报, 2012, 35(6): 1109-1119.)
［2］JACOBSON V, SMETTERS D K, THORNTON J D, et al. Networking named content［C］// Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies. New York: ACM, 2009: 1-12.
［3］JACOBSON V, SMETTERS D K, THORNTON J D, et al. Networking named content［J］. Communications of the ACM, 2012, 55(1):117-124.
［4］ZHANG L, ESTRIN D, BURKE J, et al. Named data networking project, NDN-0001［R/OL］.[2014-06-27]. http://named-data.net/wp-content/uploads/TR001ndn-proj.pdf.
［5］PSARAS I, CLEGG R G, LANDA R, et al. Modeling and evaluation of CCN-caching trees［C］// Proceedings of the 10th International IFIP TC 6 Conference on Networking. Berlin: Springer, 2011: 78-91.
［6］CAROFIGLIO G, GALLO M, MUSCARIELLO L, et al. Modeling data transfer in content-centric networking［C］// Proceedings of the 23rd International Teletraffic Congress. Piscataway: IEEE, 2011: 111-118.
［7］CAROFIGLIO G, GALLO M, MUSCARIELLO L. Bandwidth and storage sharing performance in information centric networking［C］// Proceedings of the 2011 ACM SIGCOMM Conference. New York: ACM, 2011: 1-6.
［8］CAO P, IRANI S. Cost-aware WWW proxy caching algorithms［C］// Proceedings of the USENIX Symposium on Internet Technologies and Systems. Berkeley: USENIX Association, 1997: 193-206.
［9］WANG J M, BENSAOU B. Improving content-centric networks performance with progressive, diversity-load driven caching［C］// Proceedings of the 2012 1st IEEE International Conference on Communications in China. Piscataway: IEEE, 2012: 85-90.
［10］CHEN X, FAN Q, YIN H. Caching in information-centric networking: from a content delivery path perspective［C］// Proceedings of the 2013 9th International Conference on Innovations in Information Technology. Piscataway: IEEE, 2013: 48-53.
［11］AHLGREN B, DANNEWITZ C, IMBRENDA C, et al. A survey of information-centric networking［J］.IEEE Communications Magazine, 2012, 50(7): 26-36.
［12］XYLOMENOS G, VERVERIDIS C, SIRIS V, et al. A survey of information-centric networking research［J］. IEEE Communications Surveys and Tutorials, 2013, 16(2): 1024-1049.
［13］AFANASYEV A, MOISEENKO I, ZHANG L. NDNSIM: NDN simulator for NS-3, NDN-0005［R/OL］.[2014-06-27]. http://named-data.net/publications/techreports/trndnsim/.

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Dynamical replacement policy based on cost and popularity in named data networking

命名数据网络中基于数据请求代价与流行度的动态替换策略

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