La R\'esistance: Harnessing Heterogeneous Resources for Adaptive Resiliency in 6G Networks

arxiv(2022)

引用 0|浏览2
暂无评分
摘要
Recent years have seen more critical applications designed to protect human lives (e.g., environmental sensing, emergency response, and tactical defense) being deployed over wireless networks. These critical deployments expect higher data rates, ultra-low latency, and ultra-high reliability. 6G wireless networks are expected to fill the gap in terms of the first two aspects (i.e., higher data rates and ultra-low latency), however providing ultra-high reliability is a wide open challenge. All is well when everything works but when there is a failure or a security attack, the entire system collapses exposing the associated human lives to imminent danger. Avoiding this requires the strongest of assurances that safety and security aspects are protected no matter what. Large scale critical applications are waiting for this piece of the puzzle to be solved. At this juncture, we envision the bold theme of La R\'esistance 6G (LR6G) that would pave the way for deploying mission-critical applications and services over 6G networks. It aims to achieve ultra-high reliability and resiliency to any disruptions, be it failures or security attacks. A few disruptions are easy to handle such as a cloud VM or primary link failure. In both of these cases, applications can be restored by activating the standby resource. However, some disruptions can be detrimental such as when a cut-vertex fails or when the disruption leaves the critical application to fail without access to a standby resource. These critical applications (e.g. Smart Manufacturing, Smart City, Ocean monitoring, Wildfire monitoring, etc.) are highly distributed in nature. They must continue to deliver their mission objectives during a disruption to protect human lives. In this paper, we present our LR6G vision and outline the challenges towards achieving this vision.
更多
查看译文
关键词
resiliency,heterogeneous resources,adaptive,networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要