Joint Computation Offloading, Channel Access and Scheduling Optimization in UAV Swarms: A Game-Theoretic Learning Approach

Runfeng Chen,Yuli Zhang,Changhua Yao,Meng Wang,Kailing Yao,Li Cui,Yang Yang

doi:10.1109/ojcs.2021.3100870

Abstract

Coalition-based unmanned aerial vehicle (UAV) swarms havebeen widelyused in urgent missions. To fasten the completion, mobile edge computing (MEC) has been introduced into UAV networks where coalition leaders act as servers to help members with data computing. This paper investigates a relative delay optimization in MEC-assisted UAV swarms. Considering that the scheduling methods have great impact on the delay, some theoretical analyses are made and a scheduling method based on the shortest effective job first (SEJF) is proposed. Based on the coupled relationship between scheduling and resource allocation, the computation offloading and channel access problems are then jointly optimized. To solve the problem in distributed UAV networks, the optimization problem is formulated as an offloading game. It is proved that the game is an exact potential game (EPG) and it has at least one pure strategy Nash Equilibrium (PNE). To reach the PNE, a distributed offloading algorithm based on concurrent best-better response (CBBR) is designed. Finally, the simulations show that the performance of the proposed CBBR algorithm is better than traditional algorithms. Compared with other scheduling methods, the proposed scheduling method based on SEJF reduces the delay by up to 30%.

Highlights

With the advantages of flexibility, intelligence and diversity, coalition-based unmanned aerial vehicle (UAV) swarms have been widely applied in urgent missions, e.g., search and rescue [1]–[4]
The main contributions of this paper are summarized as follrowTso: shorten the relative delay of UAV networks, the impact of scheduling methods on delay is analyzed and the scheduling method based on shortest effective job first (SEJF) is proposed
A preliminary version of this work was [27] and the extensions of this paper are concluded as follows: 1) The heterogeneous data in UAV networks is considered and the optimization objective is adjusted to relative delay

Summary

INTRODUCTION

With the advantages of flexibility, intelligence and diversity, coalition-based unmanned aerial vehicle (UAV) swarms have been widely applied in urgent missions, e.g., search and rescue [1]–[4]. We jointly optimize computation offloading, channel access and scheduling in MEC-assisted UAV networks. The main contributions of this paper are summarized as follrowTso: shorten the relative delay of UAV networks, the impact of scheduling methods on delay is analyzed and the scheduling method based on SEJF is proposed. A preliminary version of this work was [27] and the extensions of this paper are concluded as follows: 1) The heterogeneous data in UAV networks is considered and the optimization objective is adjusted to relative delay.

RELATED WORK UA

SYSTEM MODEL AND PROBLEM FORMULATION

OFFLOADING AND LOCAL COMPUTING

INFLUENCE OF NUMBER OF MEMBERS

Findings

CONCLUSION