Integrative Modeling, Simulation, and Optimization Techniques for Efficient Data-Intensive Applications in Edge Computing Infrastructures

Abstract

The fusion of technologies that characterizes the Fourth Industrial Revolution (4IR) is blurring the boundaries between the physical and digital worlds. New solutions are increasingly complex and involve expertise in multiple domains. Thus, they are no longer considered stand-alone but as a System of Systems (SoS) comprising devices, users, and other supporting systems. The conception, design, and deployment of today's SoS require an exhaustive analysis of the scenario for succeeding. Modeling and Simulation-Based Systems Engineering (MSBSE) techniques are a variant of Systems Engineering (SE) that apply advanced Modeling and Simulation (M&S) procedures to ensure a logical, robust, and reliable incremental design, allowing us to assess the technical risks of the system while decreasing the operational and capital costs of the solution under development. However, these methods still present deficiencies that require further research to cover more use cases and achieve greater adoption in industry and academia. Using a monolithic computational model for describing the entire system usually incurs high simulation times. Usually, simulating a single scenario of a complex system takes considerably longer than the simulated time interval. Therefore, an in-depth exploration of all the possible hypotheses becomes unbearable. For that reason, we need to establish a new Modeling, Simulation, and Optimization (M&S&O) workflow for assisting in the conception, design, implementation, and operation phases of modern complex systems that tackle the problems presented above without compromising the robustness of the solution.