On-Demanding Information Acquisition in Multi-UAV-Assisted Sensor Network: A Satisfaction-Driven Perspective

Hua Yang,Cuntao Liu,Wendong Zhao,Jungang Yang,Alessandro Formisano

doi:10.1155/2021/2717733

Abstract

When multiple heterogeneous unmanned aerial vehicles (UAVs) provide service for multiple users in sensor networks, users’ diverse priorities and corresponding priority-related satisfaction are rarely concerned in traditional task assignment algorithms. A priority-driven user satisfaction model is proposed, in which a piecewise function considering soft time window and users’ different priority levels is designed to describe the relationship between user priority and user satisfaction. On this basis, the multi-UAV task assignment problem is formulated as a combinatorial optimization problem with multiple constraints, where the objective is maximizing the priority-weighted satisfaction of users while minimizing the total energy consumption of UAVs. A multipopulation-based cooperation genetic algorithm (MPCGA) by adapting the idea of “exploration-exploitation” into traditional genetic algorithms (GAs) is proposed, which can solve the task assignment problem in polynomial time. Simulation results show that compared with the algorithm without considering users’ priority-based satisfaction, users’ weighted satisfaction can be improved by about 47% based on our algorithm in situations where users’ information acquisition is tight time-window constraints. In comparison, UAVs’ energy consumption only increased by about 6%. Besides, compared with traditional GA, our proposed algorithm can also improve users’ weighted satisfaction by about 5% with almost the same energy consumption of UAVs.

Highlights

Nowadays, unmanned aerial vehicles (UAVs) are gaining increasing popularity in various fields [1], such as situation awareness, intelligence reconnaissance, data collection, and relaying
A large amount of studies have focused on this problem and several customized COP method-based problem-solving models, such as cooperative multiple task assignment problem (CMTAP)
Our goal is to find an optimal task allocation strategy that maximizes users’ satisfaction with the information obtained while minimizing the total energy consumption of the data collection UAVs. e constraints, data collection and transmission process, energy consumption model, user satisfaction model, and optimization objective are described as follows

Summary

Introduction

Nowadays, unmanned aerial vehicles (UAVs) are gaining increasing popularity in various fields [1], such as situation awareness, intelligence reconnaissance, data collection, and relaying. As the task execution capability of a single UAV is restricted by its limited flying capacity, battery capacity, reconnaissance capability, etc., it is imperative to use multiple UAVs to carry out cooperative data collection tasks. During this process, efficient task allocation [4,5,6,7] is one of the critical factors to improve the task execution efficiency of multiple UAVs effectively. As a typical COP with multiple constraints, the multi-UAV-based data collection task assignment problem is NP-hard [8] and usually cannot be solved directly to get the optimal solution. A large amount of studies have focused on this problem and several customized COP method-based problem-solving models, such as cooperative multiple task assignment problem (CMTAP)

Objectives

Results

Conclusion