X-OAR: orchestration of access resources for extended reality educational applications

Extended reality offers unprecedented learning and training occasions, and unique challenges related not only to throughput and delay, but also to the characteristic spatial concentration of trainees. We have developed an algorithm for eXtended reality oriented Orchestration of Access Resources (X-OAR) grounding on next generation network technologies. X-OAR is designed to efficiently allocate edge computing facilities and cooperatively scheduled radio access network resources for extended reality applications. Building on the 3GPP guidelines on quality of experience in XR services, X-OAR meets the stringent XR delay requirements by leveraging edge and radio resources and employing cooperative scheduling within the radio access network. We introduce a graph model of the X-OAR optimization problem, and we present the X-OAR greedy algorithm, that reduces the orchestration complexity and the dependency on user subscription information. Experimental results show that X-OAR, with its cooperative scheduling technique, outperforms state-of-the-art competitors in terms of XR quality of experience. X-OAR paves the way for further studies extending the system orchestration to the application layer and the related resource charging policy.