  This paper presents the case study of a non-intrusive porting of a monolithic
C++ library for real-time 3D hand tracking, to the domain of edge-based
computation. Towards a proof of concept, the case study considers a pair of
workstations, a computationally powerful and a computationally weak one. By
wrapping the C++ library in Java container and by capitalizing on a Java-based
offloading infrastructure that supports both CPU and GPGPU computations, we are
able to establish automatically the required server-client workflow that best
addresses the resource allocation problem in the effort to execute from the
weak workstation. As a result, the weak workstation can perform well at the
task, despite lacking the sufficient hardware to do the required computations
locally. This is achieved by offloading computations which rely on GPGPU, to
the powerful workstation, across the network that connects them. We show the
edge-based computation challenges associated with the information flow of the
ported algorithm, demonstrate how we cope with them, and identify what needs to
be improved for achieving even better performance.
