  Video transmission over the backhaul link in cloudedge collaborative networks
usually suffers security risks. Only a few existing studies focus on ensuring
secure backhaul link transmission. However, video content characteristics,
which have significant effects on quality of experience (QoE), are ignored in
the study. In this paper, we investigate the QoE-driven crosslayer optimization
of secure video transmission over the backhaul link in cloud-edge collaborative
networks. First, we establish the secure transmission model for backhaul link
by considering video encoding and MEC-caching in a distributed cache scenario.
Then, based on the established model, a joint optimization problem is
formulated with the objective of improving user QoE and reducing transmission
latency under the constraints of MEC capacity. To solve the optimization
problem, we propose two algorithms: a near optimal iterative algorithm based on
relaxation and branch and bound method (MC-VEB), and a greedy algorithm with
low computational complexity (Greedy MC-VEB). Simulation results show that our
proposed MC-VEB can greatly improve the user QoE and reduce transmission
latency within security constraints, and the proposed Greedy MC-VEB can obtain
the tradeoff between the user QoE and the computational complexity.
