The compute capability of edge devices is expanding owing to the wide adoption of edge computing for various application scenarios and specialized hardware explicitly developed for an edge environ-ment. A container orchestration platform, Kubernetes is widely used to maintain edge computing resources efficiently, but it suf-fers from a limited scheduling capacity. We present a design and implementation of an accelerator information extraction module to improve the scheduling capability of a standard Kubernetes imple-mentation by providing rich hardware information. Furthermore, we present a plausible advancement of the Kubernetes scheduler by considering detailed workload characteristics and attached spe-cialized accelerator hardware information.