| dc.description.abstract | We tackle the problem of how to support gaming at the edge of the cellular network. The reduced latency and higher bandwidth that the edge enjoys with respect to cloud-based solutions implies that transferring cloud-based games to the edge could be a premium service for end-users. The goal of this work is to design a scheme compatible with MEC and network slicing principles of 5G and beyond, and which maximizes the utility of a service/infrastructure provider with time-varying edge node capacities due to the access to intermittent renewable energy. We formulate a multi-dimensional integer linear programming problem, proving that it is NP-hard in the strong sense. We prove that our problem is sub-modular and propose an efficient heuristic, GREENING, which considers the allocation of gaming sessions and their migration. For the mentioned scenario, we analyze a wide variety of realistic configurations at the edge, studying how the performance depends on i) whether the games have a static or dynamic workload, ii) the distribution of renewable energy through nodes and time, or iii) the topology of the edge network. Through simulations, we show that our heuristic achieves performance close to that achieved by solving the NP-hard optimization problem, except with extremely lower complexity, and performs up to 25% better than state-of-the-art algorithms. | es |
