| Περίληψη: | Nowadays network connectivity touches almost every aspect of our daily lives which
means the use of mobile data keeps growing thus creating the need for a more
sophisticated mobile technology, 5G. The next generation of wireless technology, 5G
is based on a cloud-native core (5GC), can utilize virtualization technologies and follow
a Service-based architecture thus taking advantage of all their benefits. However,
even on 5G networks, in order to fulfill the Quality of Service (QoS) requirements, it is
crucial for network providers to monitor various points in the network and detect any
faults. Testing network performance and collecting metrics helps a service provider to
define network resource utilization, predict future traffic demands, identify abnormal
traffic patterns, and offer suggestions for enhancing network performance. Network
administrators traditionally use monitoring tools to measure and analyze the network,
for instance a tool that uses client-server approach. Moreover, one of 5G’s key
technology is virtualization and while hypervisor-based virtualization is the prevailing
technology, the environment is altering recently, as a new form of virtualization that
has existed for a long-time gains popularity, called containerization. Since enterprises
grow more and more their adoption of Cloud Computing solutions, they also move
towards containerized technologies and microservices concepts because of the wide
range of benefits they offer, as better uptime, faster deployments, better hardware
utilization and lower costs are only a few of them.
The purpose of this thesis is to describe the basic concepts of these technologies, then
create a containerized and orchestrated toolkit, with which we could monitor and
make measurements throughout a 5G container-centric Cloud infrastructure to test
the network performance and collect metrics. To achieve that, Docker and Kubernetes
as the container technologies are used, along with a set of free open-source
monitoring tools like Iperf3 and Ookla Speedtest, resulting in a lightweight and easily
configurable implementation.
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