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Autonomic composition of software for smart cities

Grant number: 20/07193-2
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): June 01, 2020
Effective date (End): May 31, 2022
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computer Systems
Cooperation agreement: MCTI/MC
Principal researcher:Fábio Moreira Costa
Grantee:Roberto Vito Rodrigues Filho
Home Institution: Instituto de Informática. Universidade Federal de Goiás (UFG). Ministério da Educação (Brasil). Goiânia , SP, Brazil
Associated research grant:15/24485-9 - Future internet for smart cities, AP.TEM

Abstract

Contemporary systems are often deployed in highly volatile and heterogeneous operating environments which make them greatly complex. Smart Cities are a notable example that illustrates all aspects of the complexity of contemporary systems. In the software development process of Smart Cities, we often use technologies that aim to mitigate problems related to the creation and management of modern systems, such as the application of microservices to construct the software platform that abstracts the device infrastructure spread throughout the city, and Software Defined Networks (SDN) for the Internet of Things (IoT) to provide more flexibility for interconnecting devices. However, these technologies, when used to support software adaptation at runtime, still demand the definition of the system's adaptation logic that determines when and to which software configuration the system must adapt. The manual definition of the adaptation logic is not desirable when considering large scale systems, for which it is hard to predict the events in the operating environment that impact the system's performance and require adaptation. A promising approach that enables systems in any application domain to learn at runtime their own adaptation logic, and thus deals with uncertainty in the operating environment, is named Emergent Software Systems (ESS). Therefore, this proposal aims to explore the ESS concept in tandem with microservices and SDN for IoT to autonomously compose software modules for Smart Cities, dealing with the high dynamicity and uncertainty of the operating environment that is characteristic of this application domain. At last, we aim to contribute to the advancement of the state-of-the-art of self-adaptive/autonomic systems and their role in managing the complexity in the current software ecosystem of Smart Cities. (AU)

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