Concurrent real-time optimization of detecting unexpected tasks in IoT design process using GA

In this paper we present a genetic algorithm for concurrent real-time optimization for detecting unexpected tasks in IoT design process. The process can be split into two phases which impact each other in real-time. Modification of one phase modifies the second one. The algorithm detects unexpected tasks as a connection of parts of predicted tasks. Therefore, there can exist more than one way to resolve the unexpected situation. The algorithm searches for optimal solution making concurrent optimization of two phases of the design process. Use of genetic algorithm helps also to eliminate connections of subtasks which do not give a good result.