Distributed Optimization for Mobile Robots under Mobile Edge Computing Environment

Hui Luo,Quan Yin,Xiao Ling Wang

doi:10.1155/2021/8342610

Abstract

Driven by the development of the Internet industry, mobile robots (MRs) technology has become increasingly mature and widely used in all walks of life. Since MRs are densely distributed in the network system, how to establish a reliable communication architecture to achieve good cooperation and resource sharing between MRs has become a research hotspot. In this respect, mobile edge computing (MEC) technology and millimeter wave (mmW) technology can provide powerful support. This paper proposes a mmW communication network architecture for distributed MRs in MEC environment. The mmW base station provides reliable communication services for MRs under the coverage of information cloud (IC). We design a joint resource and power allocation strategy aimed at minimizing network energy consumption. First, we use the Lyapunov optimization technique to transform the original infinite horizon Markov decision process (MDP) problem. Then, a semidistributed algorithm is introduced to solve the distributed optimization problem in the mmW network. By improving the autonomous decision-making ability of the mmW base station, the signaling overheads caused by information interaction are reduced, and information leakage is effectively avoided. Finally, the global optimal solution is obtained. Simulation results demonstrate the superiority of the proposed strategy.

Highlights

With the rapid development of the Internet industry, a variety of intelligent terminals emerge in an endless stream
Based on TCP and UDP in the local area network (LAN), the distributed communication method proposed in [2] allows robots to subscribe to target topics independently to achieve multirobot cross-platform communication
Each robot in [3] can establish communication paths to maintain a consistent communication with the cloud to effectively realize cooperative communication and link prediction. e authors in [4] proposed a scheme of mobile robot object recognition in Internet of ings (IOT) and used edge nodes to coordinate the data from robot vision

Summary

Introduction

With the rapid development of the Internet industry, a variety of intelligent terminals emerge in an endless stream. Based on the research above, we need to develop a distributed network resource management scheme which is more suitable for MRs network and has stronger autonomy and flexibility, higher security, and cost performance In this regard, Mobile Edge Computing (MEC) technology can sink elastic resources such as computing, network, and storage in cloud data center to the edge of distributed network, effectively relieving the pressure on core network, improving computing efficiency, and reducing service latency [9,10,11]. We introduce a semidistributed algorithm for distributed optimization issues on complex mmW MECs. Compared with traditional distributed programs, this scheme improves the independent decision-making capacity of mmW APs and only needs to exchange a small amount of Lagrangian parameters through IC without sharing global information, which greatly reduces signaling overheads and protects the users’ privacy.

System Model

Problem Formulation and Transformation

Semidistributed Resource and Power Allocation

Simulation and Evaluation