An Interest Forwarding Scheme for Information Centric Network Driven by Content Residence Probability
Keywords:
ICN, ICN Routing, Named data networking, Probability based interest forwarding, Betweenness centralityAbstract
The interest packet forwarding is an important area of research in Information Centric Network (ICN). A well-designed forwarding approach considerably improves the end users’ satisfaction by reducing content retrieval delay. It also reduces overhead for data retrieval. In this paper, a probabilistic time driven forwarding strategy for ICN is described. The proposed approach takes into account the probabilistic time of residing the desired data in a particular location. It also exploits centrality measure related to content routers in the network to find the location of cached content. Performance evaluation of the said protocol is done within ndnSIM 2.0 simulator. The comparative outcome analysis with integration of protocol to state-of-the-art caching protocols. Various parameters chosen for comparison includes data retrieval delay, cache hit rate, network load, network overhead and average hop distance. The simulation results conclude that integrating proposed method of forwarding to existing protocols improve the performance around 10-35%.
Downloads
References
M. Aggarwal, K. Nilay, and K. Yadav, “Survey of named data networks: future of internet,” Inter Jou of Information Technology (Singapore), Vol. 9, No. 2, pp. 197–207, 2017.
H. Jin, D. Xu, C. Zhao, and D. Liang, “Information-centric mobile caching network frameworks and caching optimization: a survey,” Eurasip Journal on Wireless Communications and Networking, Vol. 2017, No. 1. 2017.
N. Dutta. An approach for FIB construction and Interest packet forwarding in information centric network. Future Generation Computer Systems 2022; 130:269-278.
K. Delvadia, N. Dutta, and G. Ghinea. An efficient routing strategy for information centric networks. In Proc. IEEE ANTS, India, pp. 1-6, 2019.
F. Al-Turjman, “Fog-based caching in software-defined information-centric networks,” Computers & Electrical Engineering, Vol. 69, pp. 54–67, 2018.
K. Delvadia, N. Dutta, and R. Jadeja. CCJRF-ICN: A Novel Mechanism for Coadjuvant Caching Joint Request Forwarding in Information Centric Networks. IEEE Access 2021; 9:84134 - 84155.
N. Dutta. A bargain game theory assisted interest packet forwarding strategy for information centric network. Journal of Network and Computer Applications 2023; 209: 103546.
Lal KN, Kumar A, “An efficient lookup search and forwarding mechanism for information-centric networking (ICN)”, Arab J Sci Eng, Vol. 43, pp.1–13, 2017.
Lan Wang, A K M Mahmudul Hoque, Cheng Yi, Adam Alyyan, Beichuan Zhang, “OSPFN: An OSPF Based Routing Protocol for Named Data Networking,” NDN Technical Report NDN-0003, July 2012.
A. K. M. M. Hoque, S. O. Amin, A. Alyyan, B. Zhang L. Zhang, and L. Wang, “NLSR: Named-data Link State”, 3rd ACM SIGCOMM workshop on Information-centric networking, Hong Kong, China, August, 2013, pp. 15-23.
J. V. Torres, I. D. Alvarenga, R. Boutaba, and O. C. M. B. Duarte, “An autonomous and efficient controller-based routing scheme for networking Named-Data mobility”, Computer Communication., Vol. 103, pp. 94–103, 2017.
C. Ghasemi, H. Yousefi, K. G. Shin, and B. Zhang., “MUCA: New Routing for Named Data Networking”, IFIP Networking, Zurich, Switzerland, May, 2018, pp. 289–297.
N. Dutta., “An approach for FIB construction and Interest packet forwarding in information centric network”, Future Generation Computer Systems, Vol. 130, pp. 269-278, 2022.
J. J. Garcia, Luna-Aceves, “Name-based content routing in information centric networks using distance information”, ACM Int. Conf. on Information-centric Networking, Paris, France, September, 2014.
K. Delvadia, N. Dutta and R. Jadeja, "CCJRF-ICN: A Novel Mechanism for Coadjuvant Caching Joint Request Forwarding in Information Centric Networks," IEEE Access, Vol. 9, pp. 84134-84155, 2021.
N. Dutta et al., “Deep learning inspired routing in ICN using Monte Carlo Tree Search algorithm”, Journal of Parallel and Distributed Computing, Vol. 150, pp. 104-111, 2021.
A. Narayanan et al., “DEEPCACHE: A deep learning based framework for content caching”, In Proc.of ACM SIGCOMM Workshop on Network Meets AI & ML, Hungary, pp.48–53, 2018.
R. Boutaba et al., “A comprehensive survey on machine learning for networking: evolution, applications and research opportunities”, Journal of Internet Services and Applications, Vol. 9, pp. 1-16, 2018.
R. Yuan, Z. Li, X. Guan, and L. Xu, “An SVM-based machine learning method for accurate Internet traffic classification”, Information Systems Frontiers, Vol. 12, pp 149-156, 2010.
X. Chen, G. Zhang, Q. Gao, H. Cui, “Improving NDN Forwarding Engine Performance by Rendezvous-based Caching and Forwarding”, Comput. Netw., Vol. 145, pp. 232-242, 2018.
G. Carofiglio et al.,”Joint forwarding and caching with latency awareness in information-centric networking,” Comput. Netw., Vol. 110, pp. 133-153, 2016.
H. Che, Y. Tung, Z. Wang, “Hierarchical web caching systems: modeling, design and experimental results”, IEEE Journal on Selected Areas in Communications, Vol. 20, No. 7, pp. 1305–1314, 2002.
Banerjee, B., Seetharam, A., Mukherjee, A., & Naskar, M. K., “Characteristic time routing in information centric networks”, Computer Networks, Vol. 113, pp. 148–158, 2017.
K. V. Katsaros, G. Xylomenos and G. C. Polyzos, "GlobeTraff: A Traffic Workload Generator for the Performance Evaluation of Future Internet Architectures," 5th International Conference on New Technologies, Mobility and Security (NTMS), 2012, pp. 1-5.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
