Document Type : Review Article

Authors

1 Department of Computer Engineering, Najafabad Branch, Islamic Azad university, Najafabad, Iran.

2 1- Faculty of Computer Engineering, Najafabad Branch, Islamic Azad university, Najafabad, Iran. 2-Big Data Research Center, Najafabad Branch, Islamic Azad university, Najafabad, Iran.

3 1- Depertment of Computer Engineering, Najafabad Branch, Islamic Azad university, Najafabad, Iran. 2-Big Data Research Center, Najafabad Branch, Islamic Azad university, Najafabad, Iran.

Abstract

Although Named Data Network (NDN) has made a bright future in Internet for high volume of requests by many users, how to send a request package (I-Pkt) consciously from the consumer to the Producer and returning the data package (D-Pkt) inversely is still one of its most important challenges. According to the recent limited researches, using service quality parameters beside an optimization algorithm like ant colony to find the optimal path has been an appropriate response to solve this problem. Not considering the service quality parameters sufficiently to find an optimal path is a problem to be focused more on. In line with this, this study has addressed the Intelligent Water Drops (IWD) optimization algorithm. In this algorithm, the best possible path based on many parameters related to path quality like cost, delay and number of steps taken by the package (I-Pkt) will be selected. In other words, the water drop movement tries to find the optimal path through the amount of soil collection in the path or the velocity rate. The results of simulating in ndnSIM simulator show that comparing the ant colony, it has improved in cost parameter on average by 23%, in hit ratio parameter by 24% and in hop count parameter by 13%. The general result is increasing service level quality in NDNs.

Keywords

[1] D. Saxena, V. Raychoudhury, N. Suri, C. Becker, and J. Cao, “Named Data Networking: A survey,” Comput. Sci. Rev., vol. 19, pp. 15–55, 2016.
[2] L. Zhang et al., “Named Data Networking,” SIGCOMM Comput. Commun. Rev., vol. 44, no. 3, pp. 66–73, Jul. 2014.
[3] E. Lee, “Categories and Subject Descriptors,” Proc. 47th Des. Autom. Conf. (DAC),ACM, pp. 737–742, 2010.
[4] Z. Rezaeifar, J. Wang, H. Oh, S.-B. Lee, and J. Hur, “A reliable adaptive forwarding approach in named data networking,” Futur. Gener. Comput. Syst., vol. 96, pp. 538–551, 2019.
[5] A. Kalghoum and L. A. Saidane, “FCR-NS: a novel caching and forwarding strategy for Named Data Networking based on Software Defined Networking,” Cluster Comput., vol. 22, no. 3, pp. 981–994, 2019.
[6] M. Zhang, X. Wang, T. Liu, J. Zhu, and Q. Wu, “AFSndn: A novel adaptive forwarding strategy in named data networking based on Q-learning,” Peer-to-Peer Netw. Appl., vol. 13, no. 4, pp. 1176–1184, 2020.
[7] C. Li, K. Okamura, and W. Liu, “Ant colony based forwarding method for content-centric networking,” Proc. - 27th Int. Conf. Adv. Inf. Netw. Appl. Work. WAINA 2013, pp. 306–311, 2013.
[8] Q. Huang and F. Luo, “Ant-colony optimization based QoS routing in named data networking,” J. Comput. Methods Sci. Eng., vol. 16, no. 3, pp. 671–682, 2016.
[9] A. Kerrouche, M. R. Senouci, A. Mellouk, and T. Abreu, “AC-QoS-FS: Ant colony based QoS-aware forwarding strategy for routing in Named Data Networking,” 2017 IEEE Int. Conf. Commun., pp. 1–6, 2017.
[10] A. Kerrouche, M. R. Senouci, and A. Mellouk, “QoS-FS: A new forwarding strategy with QoS for routing in Named Data Networking,” 2016 IEEE Int. Conf. Commun. ICC 2016, 2016.
[11] X. Zeng and Z. H. Gao, “Rank-based routing strategy for named data network,” Appl. Mech. Mater., vol. 543–547, pp. 3320–3323, 2014.
[12] C. Yi, A. Afanasyev, I. Moiseenko, L. Wang, B. Zhang, and L. Zhang, “A case for stateful forwarding plane,” Comput. Commun., vol. 36, no. 7, pp. 779–791, 2013.
[13] M. Kuai, X. Hong, and Q. Yu, “Delay-tolerant forwarding strategy for named data networking in vehicular environment,” Int. J. Ad Hoc Ubiquitous Comput., vol. 31, no. 1, pp. 1–12, 2019.
[14] Y. Tao, Y. Fan, and R. Huang, “A probability forwarding strategy for Named Data Networking based on congestion level of interface,” Int. J. Smart Eng., vol. 3, pp. 1–6, 2019.
[15] Z. Qureshi et al., “Fuzzy Logic-based Efficient Interest Forwarding (FLEIF) in Named Data Networking,” Trans. Emerg. Telecommun. Technol., vol. 30, no. 9, p. e3577, 2019.
[16] T. Cheng, Y. Yang, and D. Qu, “A Forwarding Strategy Based on Recommendation Algorithm in Named Data Networking,” in 2019 IEEE 21st International Conference on High Performance Computing and Communications, 2019, pp. 51–53.
[17] M. Abdelaal, M. Karadeniz, F. Durr, and K. Rothermel, “LiteNDN: QoS-Aware Packet Forwarding and Caching for Named Data Networks,” 2020 IEEE 17th Annu. Consum. Commun. Netw. Conf. CCNC 2020, no. January, pp. 10–13, 2020.
[18] S. Mastorakis, A. Afanasyev, and L. Zhang, “Public Review for On the Evolution of ndnSIM Artifacts Review for On the Evolution of ndnSIM,” ACM SIGCOMM Comput. Commun. Rev., vol. 47, no. 3, pp. 19--33, 2017.
[19] A. Afanasyev, I. Moiseenko, and L. Zhang, “ndnSIM: NDN simulator for NS-3,” NDN, Tech. Rep. NDN-0005, pp. 1–7, 2012.
[20] S. Mastorakis, A. Afanasyev, I. Moiseenko, and L. Zhang, “ndnSIM 2 : An updated NDN simulator for NS-3,” Dept. Comput. Sci., Univ. California, Los Angeles, Los Angeles, CA, USA, Tech. Rep. NDN-0028, pp. 1–8, 2016.