Reliability, timeliness and load reduction at the edge for cloud gaming

In this paper we study reliability, timeliness and load reduction in an hybrid Mobile Edge Computing (MEC)/Cloud game streaming infrastructure. In our scenario, a user plays a game streamed by the producer to their handheld device -- or User Equipment (UE). The UE communicates user actions to the edge/cloud via the mobile communication infrastructure; the object is to retrieve the latest game status, of which the most important information is the rendered frame. Particularly, we study reliability through replication in a number of MEC-servers, timeliness through Age of Information (AoI) and load reduction by leveraging the X2 interface at the edge, in order to abort useless frame rendering computations. We translate it as a scenario where a sink -- representing the UE -- is interested in the freshest possible update from distributed nodes. Each node sends updates following a Last Come First Served (LCFS) policy with preemption. We consider two scenarios; the first is $n$ parallel LCFS systems sending updates, and the second adds a feedback loop aimed at decreasing the number of jobs sent per second by the nodes, thus decreasing the load per node. We analyze the number of jobs sent per second and average peak Age of Information at the sink, showing that the second scheme achieves a significantly lower rate of jobs compared with the first, while maintaining constant AoI, thus reducing the load at the edge. We also find that using the feedback loop, we achieve the maximum saving in transmitted jobs per second when the average arrival rate per system is equal to the inverse of the average busy time in every node.