A fair dynamic content store-based congestion control strategy for named data networking. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Liu, Yan-Hong; Huang, Feng-Hua; Yang, Hua
• Is Part Of: Systems science & control engineering. Volume 10:Issue 1(2022)
• Page Start: 73
• Page End: 78
• Publication Date: 2022-12-31
• Subjects: NDN -- congestion control -- dynamic content store -- fairness; System theory -- Periodicals; Automatic control -- Periodicals; 003.05
• DOI: 10.1080/21642583.2022.2031335
• Languages: English
• ISSNs: 2164-2583

Abstract

Abstract : In this paper, the congestion control for named data networking (NDN) is studied. A novel dynamic content store-based congestion control strategy is proposed on account of the characteristic of in-network cache in NDN. A queuing network model is constructed to judge whether congestion occurs. If the network has the tendency of congestion or the congestion happened, the buffer of the output queue is dynamically expanded by borrowing NDN content store (CS), and the forwarding rates of data packets and corresponding interest packets are reduced so as to prevent or alleviate network congestion. In order to reflect fairness, the CS to be borrowed by the data output queue in the port is calculated in terms of the data output queue length and its weight. The simulation results based on ndnSIM show that the given scheme improves the bottleneck link utilization and maintains a low packet loss rate and average flow completion time.