Decentralized Data Flows in Algebraic Service Compositions for the Scalability of IoT Systems

With the advent of the Internet of Things, scalability becomes a significant concern due to the huge amount of data involved in IoT systems. A centralized data exchange is not desirable as it leads to a single performance bottleneck. Although a distributed exchange removes the central bottleneck, it has network performance issues as data passes among multiple coordinators. A decentralized data flow exchange is the only solution that fully enables the realization of efficient IoT systems as there is no single performance bottleneck and the network overhead is minimized. In this paper, we present an approach that leverages the algebraic semantics of DX-MAN for realizing decentralized data flows in IoT systems. As data flows are not mixed with control flows in algebraic service compositions, we developed an algorithm that smoothly analyzes data dependencies for the generation of a direct relationship between data consumers and data producers. The result prevents passing data alongside control among multiple coordinators because data is only read and written on a data space. We validate our approach using the Blockchain as the data space and conducted experiments to evaluate the scalability of our approach. Our results show that our approach scales well with the size of IoT systems.