Mobile edge computing enables the provision of computationally demanding Augmented Reality (AR) applications on mobile devices. AR mobile applications have inherent collaborative properties in terms of data collection in the uplink, computing at the edge, and data delivery in the downlink. In this letter, we propose a resource allocation approach whereby transmitted, received and processed data are shared partially among the users to obtain an efficient utilization of the communication and computation resources. The approach, implemented via Successive Convex Approximation (SCA), is seen to yield considerable gains in mobile energy consumption as compared to the conventional independent offloading across users.
['Ali Najdi Al-Shuwaili', 'Osvaldo Simeone']
Optimal Resource Allocation for Mobile Edge Computing-Based Augmented Reality Applications