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Modeling and Improving Named Data Networking over IEEE 802.15.4

Published

Author(s)

Amar Abane, Paul Muhlethaler, Samia Bouzefrane, Abdella Battou

Abstract

Enabling NDN in real-world IoT deployments becomes essential to benefit from ICN/NDN features in current IoT systems. To design realistic NDN-based communication solutions for IoT, revisiting mainstream technologies such as low-power wireless standards may be the key. In this paper, we explore the NDN forwarding over IEEE 802.15.4 according to two steps. First, we mathematically model a broadcast-based NDN wireless forwarding strategy over constrained networks. The model considers content popularity and estimates the average number of frames transmitted per request and the mean round-trip time. Second, based on mathematical and experimental observations of the broadcast-based forwarding at network level, we elaborate an adaptation of the CSMA algorithm used in the IEEE 802.15.4. The objective is to improve wireless forwarding with NDN while reducing broadcast effects in terms of packet redundancy, round-trip time and energy consumption. Preliminary results show that an adaptation of the CSMA algorithm may be envisioned to improve NDN efficiency and current technologies support of the ICN/NDN approach.
Proceedings Title
2019 8th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN)
Conference Dates
November 26-28, 2019
Conference Location
Paris, FR
Conference Title
IFIP/IEEE 8th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks

Keywords

NDN, ICN, IoT, IEEE 802.15.4, Mathematical Model, CSMA, Low-power wireless

Citation

Abane, A. , Muhlethaler, P. , Bouzefrane, S. and Battou, A. (2020), Modeling and Improving Named Data Networking over IEEE 802.15.4, 2019 8th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN), Paris, FR, [online], https://doi.org/10.23919/PEMWN47208.2019.8986906 (Accessed October 13, 2024)

Issues

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Created February 10, 2020, Updated April 13, 2024