Abstract

The critical functions, such as autonomous vehicles, and industrial automation, are experiencing the growing needs of highly dependable, low-latency network services. These requirements are ideally aligned with the potentials that are offered by 5G network slicing. The paper presents a network slice management architecture that can be used to optimize quality of service (QoS) in relation to ultra-reliable low-latency communication (URLLC) and deterministic networking in relation to these critical use cases. This architecture is characterized with active management of resources, slice isolation, and prioritization algorithm to fulfil extreme service performance requirements. Using the realistic simulations of the vehicular traffic and the industrial automation scenarios, we evaluate the performance of the described architecture in response to the changing and demanding conditions of the network such as the peak load and the resource fragmentation. The findings show that network latency of 6 ms of vehicle slices and 12 ms of industrial automation slices can be guaranteed to ensure optimal QoS of the network even when the network is congested. The aggressive slice isolation ensures that non-critical slices will be negatively affected. The performance of non-critical slices is impaired in a manner that affects critical application performance slices, middle and low quality of service (QoS) slicing. The management of network slices on mission critical applications is also taken into consideration in the paper. In particular, the control of congestion, cyberattack, and data breach and denial of service (DoS) threats.