Fuzzy Logic‐based Efficient Interest Forwarding (FLEIF) in Named Data Networking

Abstract

Content centric or Named Data Networking (NDN) is expected to replace IP‐based communication in the future Internet architecture. Here, connections are established based on data instead of host addresses. This flexibility helps in decreasing the end‐to‐end delay, as the requested data may be available in any intermediate router's cache. In NDN, a small Interest packet sent on a link results in large sized incoming Data packets on the same link. Therefore, sending multiple Interest packets on a single outgoing face may cause congestion on the returning path. Hence, regulation of Interest packets based on link characteristics is important to avoid congestion. In this paper, an intelligent mechanism based on Neuro‐Fuzzy Logic is proposed for calculating outgoing link prices of each intermediate node. The class of each outgoing link on a router is determined for Interest forwarding in order to avoid congestion. Comparison results show that the proposed method effectively improves throughput by decreasing packet loss ratio.

An Enhanced Forwarding Method based on Intelligent Water Drops Algorithm in Named Data Network

“…To prevent the congestion in forwarding the I-Pkt, in [14], a probability method has been used to compute interface congestion control and then, forwarding the packet through an optimized interface. In [15], a packet forwarding method has been used in which through sharing the information of a router with a request packet, the same is done for the other request packets. This method causes better performance in not having unwanted congestion in the network and effective packet restore (D-Pkt) from adjacent nodes comparing the current methods of packet forwarding in NDNs.…”

Machine Learning/AI for IoT, M2M, and Computer Communication

“…Data‐driven networking issues together with ML techniques are investigated by the next two papers. Kong et al suggested the use of long short‐term ML algorithm on big data to predict traffic flow in the 13th paper, “Big data‐driven machine learning‐enabled traffic flow prediction.” Article 14, “Fuzzy logic‐based efficient interest forwarding (FLEIF) in named data networking” by Qureshi et al, proposes a neuro‐fuzzy logic technique to reduce congestion caused by sending multiple interest packet in Named Data Networking (NDN).…”