The Lyapunov Optimization for Two-Tier Hierarchical-Based MAC in Cloud Robotics

Abstract

Cloud robotics can largely enhance the robot intelligence by offloading tasks to the cloud dynamically. However, the robots differ in their own hardware configuration such as battery and processing capacity, while the transmission frames are also a mixture of different quality of service (QoS) requirements. As the competition for limited channel resource is inevitable, how to optimize the system performance by effective resource allocation is a key problem. The paper proposes a two-tier hierarchical-based MAC (Two-Tier MAC) which means the classification exists not only in frames but also in robots. The Lyapunov optimization technique is used to maximize the time-averaged quality satisfaction. The experiments show the superior performance of the Two-Tier MAC compared with other MAC protocols especially in overloaded networks. Meanwhile, the system also presents a longer lifetime because the Two-Tier MAC takes energy balance into consideration.