Fluid computing: interest-based communication in dataflow/multiset rewriting computing.

Among the existing computational parallel models, Gamma and Dynamic Dataflow are equivalent models where parallel programs can be developed in a natural way. However, the implementation of Gamma paradigm poses several communication and architectural challenges. On the other hand, interest-based protocols have emerged as possible solutions of communication routing enabling an efficient communication in IoT environments. An interesting property of Gamma is the possibility of locality exploration in a non-complex way that sounds quite suitable for IoT applications. This work proposes a novel execution model for Gamma programs integrating the Radnet --- an interest-based protocol --- as communication protocol. Since the interest processing using Gamma paradigm is not a trivial task, a dynamic dataflow graph is used to express the interest as edges between vertices. We explore the equivalence results between Gamma and dataflow and, also, provide experiments showing the potential of Gamma when used to implement approximate computing techniques.