Proactive Edge Cloud Optimization for Mobile Augmented Reality Applications

Undoubtedly mobile augmented reality (MAR) applications are starting to attract significant attention due to enhanced capabilities from both the network and the end devices which can propel their realization. However, despite the progress on the end user devices, MAR applications are inherently extremely hungry in terms of CPU and memory requirements since they are performing, inter alia, intense computer vision algorithms. To this end, edge cloud computing is envisioned as a key and integrated technology for supporting such applications where part of the intensive algorithms are offloaded to suitably selected edge clouds. In this paper an edge cloud resource optimization framework is presented that takes explicitly into account user mobility to proactively allocate resources to satisfy the required strict latency requirements of MAR applications. Numerical investigations reveal that significant gains can be achieved by creating MAR offloading tasks using mobility awareness.