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RPLIE: RPL for Indoor Environments under Midterm Link Fluctuations

Cited 2 time in Web of Science Cited 5 time in Scopus

Kim, Hyung-Sin; Paek, Jeongyeup; Bahk, Saewoong

Issue Date
Journal of Communications and Networks, Vol.23 No.3, pp.201-211
Link dynamics due to environmental change is a critical challenge for wireless networking, and handling it is essential for wireless protocols, especially for low-power and lossy multihop wireless networks (LLNs). Prior work have only studied methods to detect and cope with short-term and long-term link dynamics in LLN. In this work, we tackle the midterm dynamics due to the opening and closing of doors and windows that can happen in a time scale of a few minutes to hours in an indoor LLN. Specifically, we study how midterm link fluctuations impact the performance of standard IPv6 routing protocol for LLN (RPL), and design 'RPLIE,' a novel and backward-compatible lightweight enhancement to RPL that detects and overcomes the negative impact of such dynamics. We define 'opportunistic links' and propose a novel routing metric, expected breakage cost (EBC), which represents the expected number of link transmissions required from a link breakage to a routing parent change. We implement RPLIE on real embedded devices, and evaluate its performance against the standard RPL via experiments on a 31-node testbed to show that RPLIE achieves significantly better packet delivery performance while using less overhead.
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  • Graduate School of Data Science
Research Area Distributed machine learning, Edge, Mobile AI


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