Cooperative Bargaining Game Based Adaptive Video Multicast Over Mobile Edge Networks

Video delivery over wireless networks with limited network resources and dynamically changing channel quality is an important challenge, and one of the most promising solutions for tackling this problem is to employ multicast transmissions, which improves network resource utilization efficiency. This article focuses on delivering video concurrently to multiple users over mobile networks leveraging Multicast Broadcast Multimedia Service (MBMS) and Mobile Edge Computing (MEC) technology. We propose a
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-means clustering and cooperative bargaining game-based adaptive video multicast solution (KGS) over mobile edge networks, with the goal of providing high-quality video delivery service in an envisaged MBMS service area across multiple cell sites. By taking user subgrouping, resource allocation, and bitrate adaptation into account, we establish a Cooperative Bargaining Game (CBG) based joint optimization model for multiple Multicast Broadcast Synchronized Frequency Network (MBSFN) users in mobile edge networks. Then we transform this model into a two-stage convex optimization problem and a nonlinear integer programming problem. We propose a heuristic approach to solve them and achieve a Pareto optimal video delivery strategy for all users. Finally, the efficiency of the proposed scheme is evaluated through extensive simulations.