Additive Logarithmic Weighting for Balancing Video Delivery over Heterogeneous Networks

The demand of media delivery services has increased with the popularity of social media and with the evolution of the user's devices (i.e., smartphones, laptops, and tablets) pushing towards new contents distribution models. The coexistence of go-live and on-demand media content requires a combined broadcast/unicast delivery model with the efficient management of the wireless access as a key issue. A twofold target needs to be reached: optimizing the load balance among coexisting networks and offering adequate quality of service (QoS) to users. To achieve this target for mobile video service delivery over heterogeneous networks (HetNet) scenarios, this paper proposes a solution based on an additive logarithmic weighting (ALOW) algorithm combining received signal power, network load, packet delay, user's equipment, and user's credit budget. ALOW is optimized by means of a cooperative game theory (GATH) approach. The proposed solution, named ALOWGATH (i.e., ALOW + GATH), has been tested on realistic HetNet scenarios and compared to the state of the art of the network selection and balancing algorithms. Results show an improved performance in terms of throughput, satisfaction index and overall video quality delivered, with reduced computational complexity.