  The current trend in end-user devices' advancements in computing and
communication capabilities makes edge computing an attractive solution to pave
the way for the coveted ultra-low latency services. The success of the edge
computing networking paradigm depends on the proper orchestration of the edge
servers. Several Edge applications and services are intolerant to latency,
especially in 5G and beyond networks, such as intelligent video surveillance,
E-health, Internet of Vehicles, and augmented reality applications. The edge
devices underwent rapid growth in both capabilities and size to cope with the
service demands. Orchestrating it on the cloud was a prominent trend during the
past decade. However, the increasing number of edge devices poses a significant
burden on the orchestration delay. In addition to the growth in edge devices,
the high mobility of users renders traditional orchestration schemes
impractical for contemporary edge networks. Proper segmentation of the edge
space becomes necessary to adapt these schemes to address these challenges. In
this paper, we introduce a segmentation technique employing lax clustering and
segregated mobility-based clustering. We then apply latency mapping to these
clusters. The proposed scheme's main objective is to create subspaces
(segments) that enable light and efficient edge orchestration by reducing the
processing time and the core cloud communication overhead. A bench-marking
simulation is conducted with the results showing decreased mobility-related
failures and reduced orchestration delay.
