A Survey of Distributed Stream Processing Systems for Smart City Data Analytics

The widespread grow of big data and the evolution of Internet of Things (IoT) technologies enable cities to obtain valuable intelligence from a large amount of real-time produced data. In a Smart City various IoT devices generate data continuously which needs to be analyzed within a short period of time, using some big data technique. In this paper, we examine applicability of employing distributed stream processing frameworks at the data processing layer of Smart City and appraising the current state of their adoption and maturity among the Smart City use cases. Our experiments focuses on evaluating the performance of three SDPSs, namely Apache Storm, Apache Spark Streaming, and Apache Flink. According to our obtained results, choosing proper framework at the data analytics layer of a Smart City, depends on characteristics of the target IoT applications. Finally, we present a category of applications that suit each framework.