INF-NDN IoT: An Intelligent Naming and Forwarding in Name Data Networking for Internet of Things

Abstract

Internet of things (IoT) has emerged as a quintessential paradigm of communication systems. Current literature introduces notion of a named data network for IoT (NDN-IoT), optimizing IoT communication by employing name-based networking. However, the advancements introduced by this approach are inadequate when dealing with URL-based naming and forwarding. For instance, length and ambiguities in content names are still open challenges. In addition, the intelligent exploration of content names to discern a forwarding clue is a significant research gap. To achieve intelligent communication, understanding the interest name and acquiring a forwarding clue is crucial. Focusing on this gap, an intelligent naming scheme called INF-NDN IoT is proposed that correlates with a forwarding mechanism as well. The proposed INF-NDN IoT improves the NDN naming schemas by utilizing natural language processing (NLP) techniques and selecting supernodes and ordinary nodes in the network. INF-NDN IoT assigns (forwarding clue) semantic tags to content names as well as to supernodes that in turn perform the semantic forwarding. Experimental results have shown that INF-NDN IoT outperformed existing work, and has better results in terms of name length, name memory utilization, interest satisfaction rate, retrieval time, hop count, and energy consumption.

Keywords

• Named data network
• Internet of Things
• natural language processing
• supernodes
• naming
• forwarding