FSCN: A Novel Forwarding Method based on Shannon Entropy and COPRAS Decision Process in Named Data Networking

Abstract

Abstract One of the next-generation Information-Centric Networking (ICN) architectures for the future Internet is Named Data Networking (NDN). The appropriate output interface (forwarding) has recently emerged as a key challenge affecting the performance of this network and has received a lot of attention from researchers due to its importance. Although efforts have been made through the methods introduced so far to address this challenge, the neglect of effective network load balancing parameters, non-dynamic weighting, and the use of only a few criteria have been suggested for selecting the output interface have made it vital to further improve the network delay, congestion, and ultimately the network's throughput. Regarding this matter, a new strategy is presented in this article based on the COPRAS Decision-Making Process with the dynamic weighting of Shannon's entropy called FSCN for transmitting request packets through the optimal output interface. The essential parameters identified in the suggested approach such as bandwidth, delay, and the number of hops can be dynamically weighted using the Shannon entropy technique and conditions. Then, the interfaces are scored using the COPRAS method, and the suitable output interface is ascertained. The advantages of the proposed method include considering influential criteria to characterize the path's performance and the dynamic weighting of criteria. The simulation outcomes in NDNsim demonstrated enhancements in critical parameters, including interest throughput, satisfaction ratio, packet drop, and delivery time when compared to comparable approaches.