Tactile Internet is an emerging concept that focuses on supporting
high-fidelity, ultra-responsive, and widely available human-to-machine
interactions. To reduce the transmission latency and alleviate Internet
congestion, fog computing has been advocated as an important component of the
Tactile Internet. In this paper, we focus on energy-efficient design of fog
computing networks that support low-latency Tactile Internet applications. We
investigate two performance metrics: Service response time of end-users and
power usage efficiency of fog nodes. We quantify the fundamental tradeoff
between these two metrics and then extend our analysis to fog computing
networks involving cooperation between fog nodes. We introduce a novel
cooperative fog computing concept, referred to as offload forwarding, in which
a set of fog nodes with different computing and energy resources can cooperate
with each other. The objective of this cooperation is to balance the workload
processed by different fog nodes, further reduce the service response time, and
improve the efficiency of power usage. We develop a distributed optimization
framework based on dual decomposition to achieve the optimal tradeoff. Our
framework does not require fog nodes to disclose their private information nor
conduct back-and-forth negotiations with each other. Two distributed
optimization algorithms are proposed. One is based on the subgradient method
with dual decomposition and the other is based on distributed ADMM-VS. We prove
that both algorithms can achieve the optimal workload allocation that minimizes
the response time under the given power efficiency constraints of fog nodes.

该论文研究了支持低延迟触觉互联应用的能量高效雾计算网络的设计，引入了一种称为 offload forwarding 的新型合作雾计算概念，详细阐述了在集中式和分布式训练解决方案中的设计细节和优化算法。