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Abstract-Age of Information (AoI) is a relatively new metric introduced to capture the freshness of a particular piece of information. While throughput and delay measurements are widely studied in the context of dense IEEE 802.11 Wireless LANs (WLANs), little is known in the literature about the AoI in this context. In this work we study the effects on the average AoI and its variance when a sensor node is immersed in a dense IEEE 802.11 WLAN. We also introduce a new cross layer MAC technique, called Latest UPdate MAC (LUPMAC), aimed at modifying the existing IEEE 802.11 in order to minimize the average AoI at the receiver end. This technique lets the MAC layer keep only the most up to date packets of a particular piece of information in the buffer. We show, through simulation, that this technique achieves significant advantages in the case of a congested dense IEEE 802.11 WLAN, and it is resilient to changes in the variance of the total network delay.

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 deviceor 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 MECservers, 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. Index Terms-Age of information; Queuing theory; Cloud gaming; Edge computing.

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