Graph of Virtual Actors (GOVA): a Big Data Analytics Architecture for IoT

摘要

With the emergence of cloud computing and sensor technologies, Big Dataanalytics for the Internet of Things (IoT) has become the main force behindmany innovative solutions for our society's problems. This paper providespractical explanations for the question "why is the number of Big Dataapplications that succeed and have an effect on our daily life so limited,compared with all of the solutions proposed and tested in the literature?",with examples taken from Smart Grids. We argue that "noninvariants" are themost challenging issues in IoT applications, which can be easily revealed if weuse the term "invariant" to replace the more common terms such as"information", "knowledge", or "insight" in any Big Data for IoT research. Fromour experience with developing Smart Grid applications, we produced a list of"noninvariants", which we believe to be the main causes of the gaps between BigData in a laboratory and in practice in IoT applications. This paper alsoproposes Graph of Virtual Actors (GOVA) as a Big Data analytics architecturefor IoT applications, which not only can solve the noninvariants issues, butcan also quickly scale horizontally in terms of computation, data storage,caching requirements, and programmability of the system.