Dynamic Adaptive Streaming over HTTP(DASH) is becoming the defacto method for effective video traffic delivery at large scale.Its primer success factor returns to the full autonomy given to the streaming clients making them smarter and enabling decentralized logic of video quality decision at granular video chunks following a pull-based paradigm. However,the pure autonomy of the clients inherently results in an overall selfish environment where each client independently strives to improve its Quality of Experience (QoE). Consequently,the clients will hurt each other,including themselves,due to their limited scope of perception.This shortcoming could be addressed by employing a mechanism that has a global view,hence could efficiently manage the available resources.In this paper,we propose a game theoretical-based approach to address the issue of the client's selfishness in multi-server setup,without affecting its autonomy. Particularly,we employ the coalitional game framework to affect the clients to the best server,ultimately to maximize the overall average quality of the clients while preventing re-buffering.We validate our solution through extensive experiments and showcase the effectiveness of the proposed solution.
翻译:对HTTP(DASH) 的有效视频传输的动态适应性流正在成为大规模有效视频传输的自毁方法。 它使原始成功因素回归给流出客户的完全自主性,使其在颗粒视频块的视频质量决定上更加聪明,并能够根据基于拉动的范式进行分散的逻辑。 但是,客户的纯自主性必然导致一个总的自私环境,在这个环境中,每个客户都独立地努力提高自己的经验质量(QoE)。 因此,客户将相互伤害,包括自己。 可以通过使用一种具有全球观点的机制来弥补这一缺陷。 这样做可以有效地管理现有资源。 在这份文件中,我们提出一种基于游戏的理论方法,以解决客户在多服务器设置中的自私问题,而不影响其自主性。 特别是,我们利用联合游戏框架来影响客户获得最佳服务器(QoE) 。 因此,客户将因他们的认识范围有限而彼此伤害,包括他们自己。 我们通过广泛的实验来验证我们的解决办法,并展示拟议解决方案的有效性。