Software engineering for the industrial Internet: Situation-aware smart applications

Abstract

Summary form only given. With the rise of the Industrial Internet the world entered a new era of innovation. At the heart of this new industrial revolution is the convergence of the global industrial system with computing power, low-cost sensing, big data, predictive analytics, and ubiquitous connectivity. The growing proliferation of smart devices and applications is accelerating the convergence of the physical and the digital worlds. Smart apps allow users, with the help of sensors and networks, to do a great variety of things, from tracking their friends to controlling remote devices and machines. At the core of such smart systems are self-adaptive systems that optimize their own behaviour according to high-level objectives and constraints to address changes in functional and non-functional requirements as well as environmental conditions. Self-adaptive systems are implemented using four key technologies: runtime models, context management, feedback control theory, and run-time verification and validation. The proliferation of highly dynamic and smart applications challenges the software engineering community in re-thinking the boundary between development time and run time and developing techniques for adapting systems at run time. The key challenge is to automate traditional software engineering, maintenance and evolution techniques to adapt and evolve systems at run time with minimal or no human interference. Hitherto, most developers did not instrument their software with sensors and effectors to observe whether requirements are satisfied in an evolving environment at run time. One way to break out of this mold is to make the four key technologies readily accessible at run time.