Decentralized Data Flows for the Functional Scalability of Service-Oriented IoT Systems

Abstract Horizontal and vertical scalability have been widely studied in the context of computational resources. However, with the exponential growth in the number of connected objects, functional scalability (in terms of the size of software systems) is rapidly becoming a central challenge for building efficient service-oriented Internet of Things (IoT) systems that generate huge volumes of data continuously. As systems scale up, a centralized approach for moving data between services becomes infeasible because it leads to a single performance bottleneck. A distributed approach avoids such a bottleneck, but it incurs additional network traffic as data streams pass through multiple mediators. Decentralized data exchange is the only solution for realizing totally efficient IoT systems, since it avoids a single performance bottleneck and dramatically minimizes network traffic. In this paper, we present a functionally scalable approach that separates data and control for the realization of decentralized data flows in service-oriented IoT systems. Our approach is evaluated empirically, and the results show that it scales well with the size of IoT systems by substantially reducing both the number of data flows and network traffic in comparison with distributed data flows.