Cost-effective Distributed Edge vehicle selection for Multi-tier Video streaming over Vehicular network

Video traffic demands for vehicle infotainment services have rapidly increased in recent years. To reduce bandwidth costs and delays, content distributors (CD) use edge vehicles to distribute video contents over vehicular networks. CDs usually offer multiple subscription tiers of varying video qualities for their clients. A CD’s business goal is to make a minimal edge vehicle selection to maximize Internet traffic offloading while satisfying heterogeneous video quality requirements of clients belonging to different subscription tiers. This work proposes an optimum cost-effective solution for edge vehicle selection for delay-constrained live video streaming over vehicular networks with multi-tier bitrate agreements. The edge vehicle selection problem is formulated as the minimum set covering problem for optimum results, and a distributed approximation solution is proposed to increase scalability. Simulation results show that the proposed solution is cost-effective for CDs and saves significant control message overhead while satisfying delay constraints and multi-tier bitrate agreements.