Infracomposer: Policy-driven adaptive and reflective middleware for the cloudification of simulation & optimization workflows

Abstract

The simulation and optimization of complex engineering designs in automotive or aerospace involves multiple mathematical tools, long-running workflows and resource-intensive computations on distributed infrastructures. Finding the optimal deployment in terms of task distribution, parallelization, collocation and resource assignment for each execution is a step-wise process involving both human input with domain-specific knowledge about the tools as well as the acquisition of new knowledge based on the actual execution history. In this paper, we present a policy-driven adaptive and reflective middleware that supports smart cloud-based deployment and execution of engineering workflows. This middleware supports deep inspection of the workflow task structure and execution, as well as of the very specific mathematical tools, their executions and used parameters. The reflective capabilities are based on multiple meta-models to reflect workflow structure, deployment, execution and resources. Adaptive deployment is driven by both human input as meta-data annotations as well as adaptation policies that reason over the actual execution history of the workflows. We validate and evaluate this middleware in real-life application cases and scenarios in the domain of aeronautics.

Research on legacy monolith applications decomposition into microservice architecture

“…The International Data Corporation predicts that 90% of all new applications will be developed based on microservice architecture. To remain competitive, companies have started to modernise their legacy monolithic systems by decomposing them into microservices (Francesco et al, 2018;Knoche et al, 2018;Wang et al, 2020;Wolfart et al, 2021;Beni et al, 2019;Mohamed et al, 2021).…”

“…Tarptautinė duomenų korporacija prognozuoja, kad 90 % visų naujų programų bus sukurtos remiantis mikroservisų architektūra. Įmonės, siekdamos išlikti konkurencingos rinkoje, pradėjo modernizuoti savo esamas monolitines sistemas, išskaidydamos jas į mikroservisus (Francesco et al, 2018;Knoche et al, 2018;Wang et al, 2020;Wolfart et al)., 2021;Beni et al, 2019;Mohamed et al, 2021). Nors monolitinės programinės įrangos perkėlimo į mikroservisų architektūrą tema yra nagrinėjama mokslininkų ir programinės įrangos inžinierių, tai vis dar palyginti naujas iššūkis.…”