Expressive Data-Centric Multicast on RPL in Low-Power Networks

Abstract

Applications for the Internet of Things (IoT)are often data-centric. Data-centric routing then enables messages to reach relevant consumers while avoiding flooding and explicit resource discovery. This kind of routing thus provides energy savings as well as a convenient programming abstraction: messages can be addressed to nodes that advertise features matching a constraint. In low-power wireless mesh networks, such feature-oriented routing traditionally relies on costly and inflexible network overlays. Recent work establishes lightweight support for diverse data-centric traffic patterns, but sacrifices expressiveness of feature-oriented functionality and hence applicability. It is also unclear whether the energy consumption advantages offered by data-centric routing extend to this new lightweight approach. To address these concerns, this paper introduces the SMRFET system. SMRFET improves the expressiveness of state-of-the-art feature-oriented routing by supporting numeric rather than binary features. The system integrates data-centric functionality into group-based multicast and thus adds only a small amount of overhead: experiments show that SMRFET significantly reduces the required amount of message passing relative to alternative systems for group communication. Additionally, SMRFET can be reconfigured to handle memory constraints: its performance degrades gracefully as the amount of memory allocated to it decreases. SMRFET therefore brings lightweight and expressive group communication to the wireless IoT.