The timely delivery of resource-intensive and latency-sensitive services (e.g., industrial automation, augmented reality) over distributed computing networks (e.g., mobile edge computing) is drawing increasing attention. Motivated by the insufficiency of average delay performance guarantees provided by existing studies, we focus on the critical goal of delivering next generation real-time services ahead of corresponding deadlines on a per-packet basis, while minimizing overall cloud network resource cost. We introduce a novel queuing system that is able to track data packets' lifetime and formalize the optimal cloud network control problem with strict deadline constraints. After illustrating the main challenges in delivering packets to their destinations before getting dropped due to lifetime expiry, we construct an equivalent formulation, where relaxed flow conservation allows leveraging Lyapunov optimization to derive a provably near-optimal fully distributed algorithm for the original problem. Numerical results validate the theoretical analysis and show the superior performance of the proposed control policy compared with state-of-the-art cloud network control.

翻译：对分布式计算网络(例如移动边缘计算)及时提供资源密集和对长期敏感的服务(例如工业自动化、扩大现实)正日益引起人们的注意,由于现有研究所提供的平均延迟性能保障不足,我们把重点放在关键目标上,即在每包相应最后期限之前提供下一代实时服务,同时尽量降低整个云网络资源成本;我们采用一种新的排队系统,能够跟踪数据包的寿命,在严格的最后期限限制下正式确定最佳云网络控制问题;在说明在将包交付到目的地之前因寿命到期而丢弃的主要挑战之后,我们设计了同等的配方,在宽松的流量保护下,能够利用Lyapunov优化,为原始问题取得可察觉的近于最佳的完全分布算法;数字结果验证了理论分析,并显示拟议的控制政策与最先进的云网络控制相比表现优异。