Performance-aware scheduling of streaming applications using genetic algorithm
Pavel Smirnov, Mikhail Melnik, Denis A. Nasonov · Procedia Computer Science · 2017
The main objective of Decision Support Systems is detection of critical states and response on them in time. Such systems can be based on constant monitoring of continuously incoming data. Stream processing is carried out on the basis of computing infrastructure and specialized frameworks such as Apache Storm, Flink, Spark Streaming. However, to provide the necessary system performance at high load incoming data, additional data processing mechanisms are required. In particular, the efficient scheduling of streaming applications plays an important role in the data stream processing. Therefore, this paper is devoted to investigation of genetic algorithm to improve the performance of data stream processing system. The proposed genetic algorithm is developed and integrated into Apache Storm platform, and its efficiency is compared with heuristic algorithm for scheduling of Storm streaming applications.