How could the findings and strategies proposed in this study impact the broader field of microservices architecture and load balancing, specifically in the context of 5G applications?
In the context of 5G applications, there are many 5G applications in which latency is a critical requirement, especially services that involve human health, human life, and high-speed high-accuracy facility control. For example, remote surgery, autonomous vehicles, and real-time interactive AR/VR experiences. If there were incidents while operating services, mostly it would affect to services' capacity. This results in the degrading of QoS. All end users may have a bad experience or even can not use the service. Failing to meet the requirements in SLA may incur a penalty (revenue loss) for the 5G network service provider (in our case we are the telco). The CNF applications implemented with our solution can self-adapt strategies and parameters to maintain URLL during the surge. For broader fields, self-adaptist strategies help the operators maximize resource usage, and increase service density, hence reducing CapEx and OpEx in computing infrastructure.
