Multi-access edge computing (MEC) is viewed as an integral part of future wireless networks to support new applications with stringent service reliability and latency requirements. However, guaranteeing ultra-reliable and low-latency MEC (URLL MEC) is very challenging due to uncertainties of wireless links, limited communications and computing resources, as well as dynamic network traffic. Enabling URLL MEC mandates taking into account the statistics of the end-to-end (E2E) latency and reliability across the wireless and edge computing systems. In this paper, a novel framework is proposed to optimize the reliability of MEC networks by considering the distribution of E2E service delay, encompassing over-the-air transmission and edge computing latency. The proposed framework builds on correlated variational autoencoders (VAEs) to estimate the full distribution of the E2E service delay. Using this result, a new optimization problem based on risk theory is formulated to maximize the network reliability by minimizing the Conditional Value at Risk (CVaR) as a risk measure of the E2E service delay. To solve this problem, a new algorithm is developed to efficiently allocate users' processing tasks to edge computing servers across the MEC network, while considering the statistics of the E2E service delay learned by VAEs. The simulation results show that the proposed scheme outperforms several baselines that do not account for the risk analyses or statistics of the E2E service delay.
翻译:多接入边缘计算(MEC)被视为未来无线网络的一个组成部分,以支持具有严格的服务可靠性和延迟性要求的新应用,但由于无线链接的不确定性、通信和计算资源有限以及动态网络通信流量的不确定性,保证超可靠和低纬度MEC(URLLL MEC)是极具挑战性的,因为无线链接、有限的通信和计算资源以及动态网络流量的不确定性,多接入边缘计算(MEC)是未来无线和边端计算系统(E2E2E)定位和可靠性的一个有机组成部分。在本文件中,提出了一个新框架,通过考虑E2E服务延迟的分布,优化MEC网络的可靠性,从而优化E2E服务网络的可靠性,包括超空传输和边端计算延迟。拟议框架利用这一结果,根据风险理论,形成了一个新的优化问题,以最大限度地提高网络的可靠性,最大限度地降低风险条件值(CVaR),作为E2E服务延迟性风险衡量尺度。为了解决这个问题,新的算算出E2E服务延迟性(E)服务延迟率,新的算算出电子电子电子电子服务器的升级的系统,同时考虑将电子用户对电子服务器的系统进行风险分析,以高效分析。