Towards programmable IoT with ActiveNDN

Abstract

We propose to perform robust distributed computation, such as analysing and filtering raw data in real time, as close as possible to sensors in an environment with intermittent Internet connectivity and resource-constrained computable IoT nodes. To enable this computation, we deploy a named data network (NDN) for IoT applications, which allows data to be referenced by names. The novelty of our work lies in the inclusion of computation functions in each NDN router and allowing functions to be treated as executable Data objects. Function call is expressed as part of the NDN Interest names with proper name prefixes for NDN routing. With the results of the function computation returned as NDN Data packets, a normal NDN is converted to an ActiveNDN node. Distributed function executions can be orchestrated by an ActiveNDN program to perform required computations in the network. In this paper, we describe the design of ActiveNDN with a small prototype network as a proof of concept. We conduct extensive simulation experiments to investigate the performance and effectiveness of ActiveNDN in large-scale wireless IoT networks. Two programmable IoT air quality monitoring applications on our real-world ActiveNDN testbed are described, demonstrating that programmable IoT devices with on-site execution are capable of handling increasingly complex and time-sensitive IoT scenarios.