Distributed Mobility Management Support for Low-Latency Data Delivery in Named Data Networking for UAVs

Mohammed Bellaj (), Najib Naja () and Abdellah Jamali
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Mohammed Bellaj: National Institute of Posts and Telecommunications, Rabat 10000, Morocco
Najib Naja: National Institute of Posts and Telecommunications, Rabat 10000, Morocco
Abdellah Jamali: National School of Applied Sciences of Berrechid, University of Hassan I, Settat 26000, Morocco

Future Internet, 2024, vol. 16, issue 2, 1-26

Abstract: Named Data Networking (NDN) has emerged as a promising architecture to overcome the limitations of the conventional Internet Protocol (IP) architecture, particularly in terms of mobility, security, and data availability. However, despite the advantages it offers, producer mobility management remains a significant challenge for NDN, especially for moving vehicles and emerging technologies such as Unmanned Aerial Vehicles (UAVs), known for their high-speed and unpredictable movements, which makes it difficult for NDN to maintain seamless communication. To solve this mobility problem, we propose a Distributed Mobility Management Scheme (DMMS) to support UAV mobility and ensure low-latency content delivery in NDN architecture. DMMS utilizes decentralized Anchors to forward proactively the consumer’s Interest packets toward the producer’s predicted location when handoff occurs. Moreover, it introduces a new forwarding approach that combines the standard and location-based forwarding strategy to improve forwarding efficiency under producer mobility without changing the network structure. Using a realistic scenario, DMMS is evaluated and compared against two well-known solutions, namely MAP-ME and Kite, using the ndnSIM simulations. We demonstrate that DMMS achieves better results compared to Kite and MAP-ME solutions in terms of network cost and consumer quality-of-service metrics.

Keywords: named data networking; producer mobility management; distributed mobility (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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