An Extension of the MiSCi Middleware for Smart Cities Based on Fog Computing

Abstract

In a Smart City is required computational platforms, which allow environments with multiple interconnected and embedded systems, where the technology is integrated with the people, and can respond to unpredictable situations. One of the biggest challenges in developing Smart City is how to describe and dispose of enormous and multiple sources of information, and how to share and merge it into a single infrastructure. In previous works, we have proposed an Autonomic Reflective Middleware with emerging and ubiquitous capabilities, which is based on intelligent agents that can be adapted to the existing dynamism in a city for, ubiquitously, respond to the requirements of citizens, using emerging ontologies that allow the adaptation to the context. In this work, we extend this middleware using the fog computing paradigm, to solve this problem. The fog extends the cloud to be closer to the things that produce and act on the smart city. In this paper, we present the extension to the middleware, and examples of utilization in different situations in a smart city.

Smart cities: Advances in research—An information systems perspective

“…Smart architecture and associated technologies is an integral aspect of the efficient functioning of smart cities (Aguilar et al 2017;Carvalho et al 2014). This theme includes many of the issues related to information security, data processing and storage and many of the issues surrounding cloud computing and big data.…”

“…By their nature smart cities have enormous and multiple source of information and studies have reviewed these complexities and the challenges of information exchange between different sources. These complexities can be communication between devices where trust is a key factor (Guo et al 2017), collaborative spaces and handling big data within the cloud (Aguilar et al 2017;Goyal et al 2018;Hawryszkiewycz, 2014). Carvalho et al (2014) presented a case study of company Living PlanIT that develops, test and sells smart cities software that helps to process realtime information collected through sensors embedded within building infrastructure.…”

Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context

“…Multi-agent systems can be useful for this task (Terán et al, 2017), or another platform, such as ROS Industrial (ROS Industrial, 2018). In this sense, a previous work conducted by Aguilar et al (2017d) details how to deal with issues related to the bidirectional communication of software agents and cloud-services, naturally. Next, a message queue management system is essential to allow the autonomic cycles to receive the information or events needed to make decisions, using the existing everything-mining models.…”

“…This layer is responsible for preparing all the knowledge bases needed to allow the functional and semantic interoperability in the system. This interoperability problem has been studied in previous researches (Aguilar et al, 2017d;Burns et al, 2019;Kalatzis et al, 2019;Liao et al, 2017;Obitko & Jirkovský, 2015;Pedone & Mezgár, 2018;Sanchez et al, 2019a;Vizcarrondo et al, 2017). Moreover, this layer allows the deployment of any self-* properties into the system to gain adaptability and autonomy capabilities to the manufacturing process.…”

From Elusive to Ubiquitous Understanding Smart Cities

“…However, such an infrastructure must also be capable of offering spontaneous, continuous and reliable bi-directional communication between each interconnected device within the respective grid [30]. Consequently, such an infrastructure assumes transmitting, processing and storing vast amount of data at an increased frequency, thus heavily relying on Cloud Storage, Cloud Computing and Big Data [31], [32]. Indeed, by using such services, one can expect important advantages, like cost savings, improved city management, reliable prediction, [11] etc.…”