  Multi-access edge computing (MEC) enables placing video content at the edge
of the network aiming to improve the quality of experience (QoE) of the mobile
clients. Video content caching at edge servers also reduces traffic in the
backhaul of the mobile network, hence reducing operational costs for mobile
network operators (MNOs). However, minimizing the rate of cache misses and
maximizing the average video quality may sometimes be at odds with each other,
particularly when the cache size is constrained. Our objective in this article
is two fold: First, we explore the impact of fixed video content caching on the
optimal QoE of mobile clients in a setup where servers at mobile network edge
handle bitrate selection. Second, we want to investigate the effect of cache
replacement on QoE-traffic trade-off. An integer nonlinear programming (INLP)
optimization model is formulated for the problem of jointly maximizing the QoE,
the fairness as well as minimizing overall data traffic on the origin video
server. Due to its NP-Hardness, we then present a low complexity greedy-based
algorithm with minimum need for parameter tuning which can be easily deployed.
We show through simulations that the joint optimization indeed enables striking
a desired trade-off between traffic reduction and QoE. The results also reveal
that with fixed cached contents, the impact of caching on the QoE is
proportional to the desired operational point of MNO. Furthermore, the effect
of cache replacement on QoE is less noticeable compared to its effect on
backhaul traffic when cache size is constrained.
