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Programming distributed applications in the IoT-edge environment is a cumbersome challenge. Developers are expected to seamlessly handle issues in dynamic reconfiguration, routing, state management, fault tolerance, and heterogeneous device capabilities. This demo presents DDFLOW, a macroprogramming abstraction and accompanying runtime that offers appropriate distributed system tooling to properly isolate application semantics from arbitrary deployment environments. Using DDFLOW leads to portable, visualizable, and intuitive applications. The accompanying runtime enables dynamic adaptation to improve end-to-end latency while preserving application behavior despite device failures. We evaluate DDFLOW on the Heliot platform, a hybrid emulation testbed for learning-enabled IoT systems. This demo complements the paper "DDFLOW: Visualized Declarative Programming for Heterogeneous IoT Networks" that is to be presented at IoTDI 2019 [6].

DDF LOW visualized declarative programming for heterogeneous IoT networks on Heliot testbed platform