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- Cognitive load balancing approach for 6G MEC serving IoT mashupsPublication . Attanasio, Barbara; Mazayev, Andriy; du Plessis, Shani; Correia, NoéliaThe sixth generation (6G) of communication networks represents more of a revolution than an evolution of the previous generations, providing new directions and innovative approaches to face the network challenges of the future. A crucial aspect is to make the best use of available resources for the support of an entirely new generation of services. From this viewpoint, the Web of Things (WoT), which enables Things to become Web Things to chain, use and re-use in IoT mashups, allows interoperability among IoT platforms. At the same time, Multi-access Edge Computing (MEC) brings computing and data storage to the edge of the network, which creates the so-called distributed and collective edge intelligence. Such intelligence is created in order to deal with the huge amount of data to be collected, analyzed and processed, from real word contexts, such as smart cities, which are evolving into dynamic and networked systems of people and things. To better exploit this architecture, it is crucial to break monolithic applications into modular microservices, which can be executed independently. Here, we propose an approach based on complex network theory and two weighted and interdependent multiplex networks to address the Microservices-compliant Load Balancing (McLB) problem in MEC infrastructure. Our findings show that the multiplex network representation represents an extra dimension of analysis, allowing to capture the complexity in WoT mashup organization and its impact on the organizational aspect of MEC servers. The impact of this extracted knowledge on the cognitive organization of MEC is quantified, through the use of heuristics that are engineered to guarantee load balancing and, consequently, QoS.
- A Comparative study of software architectures in constrained device IoT deploymentsPublication . du Plessis, Shani; Correia, NoéliaThe Internet of Things (IoT) is an area that has consistently seen growth and development and will no doubt continue to do so. One group of IoT devices - constrained devices - has seen significant developments in recent years. With the advent of constrained devices in almost every area of life, e.g. industrial, leisure and medical, this group of devices is well worth studying. Clearly, resource management is a critical aspect to ensure optimal use of such devices. A number of factors can have a significant impact on resource management, such as the operating system and the software architecture. This study aimed to compare the power consumption, runtime performance and memory consumption of two software architectures: microservices and monolithic. The study was conducted using a constrained device, and to ensure that the results are not language-specific, three different programming languages were used: Go, Python and C++. It was found that, for small-scale applications, the monolithic architecture performed better across most metrics. These results may provide valuable insights to engineers for the design and implementation of constrained-device IoT applications. It was recommended that additional research be conducted on larger-scale applications.