基于社交交互性和服务器配置优化的MEC游戏玩家分配

Athanasios Tsipis, K. Oikonomou
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引用次数: 2

摘要

在移动边缘计算(MEC)中,边缘服务器部署在基站(BSs)上,为附近用户提供高可访问性,减轻远程云的计算负担,显著降低网络延迟。然而,对于分布式交互应用程序(DIAs),例如云游戏,玩家组队并形成社交社区,一个基本挑战是发现最合适的玩家到服务器分配,在严格的接近性和容量限制下实现低延迟社交交互性和低成本服务器配置之间的平衡。本文利用混合整数线性规划方法对该问题进行了形式化建模。然而,它的解决方法是复杂的,属于现有容量设施选址问题的范畴。因此,我们提出了“基于交互性的边缘服务器分配”(IESA)算法,这是一种新的启发式方法,可以有效地分配并迭代改进玩家到服务器的分配。使用跟踪驱动模拟来评估IESA,以证明它如何优于基线和最先进的分配方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Player Assignment in MEC Gaming for Social Interactivity and Server Provisioning Optimization
In Mobile Edge Computing (MEC), edge servers are deployed on Base Stations (BSs) to provide high accessibility to nearby users, alleviating the computational burden of the remote cloud and significantly reducing network delays. Still, for distributed interactive applications (DIAs), such as cloud games, where players team up and form social communities, one fundamental challenge is the discovery of the most suitable player-to-server assignment, that achieves a balanced tradeoff between low-delay social interactivity and low-cost server provisioning, under strict proximity and capacity constraints. In this paper, we formally model the problem via mixed-integer linear programming. However, its solution is complex falling under the category of existing capacitated facility location problems. Thus, we present the “Interactivity-based Edge Server Allocation” (IESA) algorithm, a novel heuristic approach to efficiently assign and then iteratively improve the player-to-server allocation. IESA is evaluated using trace-driven simulations that demonstrate how it outperforms the baseline and state-of-the-art assignment alternatives.
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