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An Efficient RPL-Based Mechanism for Node-to-Node Communications in IoT - 2021

Research Area:  Internet of Things

Abstract:

Routing discovery is a pivotal component of the communication stack in low-power and lossy networks (LLNs). The IPv6 routing protocol for LLNs, termed RPL, has been recently standardized to provide routing discovery in a wide range of LLN-based deployments realizing the Internet-of-Things (IoT) vision. RPL was mainly designed with the assumption that the predominant traffic flow would be gathering data toward a single destination, typically the root node. However, node-to-node (N2N) communication, where the root is neither a source nor destination, is a prime requirement in most of the LLN-based applications, such as actuating, decision making, and controlling applications. RPL in its current form does not cater well to such applications where there is a good number of inward N2N traffic flows. In this article, we propose a hybrid routing mechanism based on RPL for high N2N communications in LLNs referred to by HRPL. HRPL is implemented on Contiki and evaluated through extensive simulations on Cooja. HRPL is fully backward compatible with RPL where HRPL and RPL nodes can work together seamlessly in a hybrid network. Results show that HRPL provides a considerable improvement in the packet delivery ratio relative to the standardized RPL-based modes and to the RPL-based opportunistic routing approach. While HRPL requires a slightly larger memory footprint more than that for RPL, HRPL manages to significantly reduce the control plane packets, number of hops, and MAC transmissions needed to successfully deliver N2N data packets. Accordingly, this is translated to lower packet delay and less energy consumption.

Author(s) Name:  Mohammed Mahyoub; Ashraf S. Hasan Mahmoud; Marwan Abu-Amara; Tarek R. Sheltami King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Journal name:  IEEE Internet of Things Journal

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/JIOT.2020.3038696

Volume Information:  Volume: 8, Issue: 9, Pages: 7152 - 7169