Expressive Feature-oriented Multicast for the Internet of Things

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 reduces the amount of transmissions required to support relevant applications and 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. This paper overcomes that trade-off by introducing SMRFET, a multicasting system that integrates data-centric functionality into a standard low-power network stack. SMRFET thus improves over the art: it offers more expressive addressing mechanics (range queries over a node's features) at lower implementation and runtime cost (no additional networking mechanisms). Additionally, SMRFET can be configured to handle memory constraints: its performance degrades gracefully as the designated amount of memory decreases. SMRFET therefore brings lightweight and expressive group communication to wireless IoT networks.