scholarly journals Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Jie Chen ◽  
Kai Xiao ◽  
Kai You ◽  
Xianguo Qing ◽  
Fang Ye ◽  
...  
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Task Assignment ◽  
Search And Rescue ◽  
Small Scale ◽  
Assignment Strategy ◽  
Negotiation Mechanism ◽  
Decoupling Algorithm ◽  
Task Assignment Problem ◽  
Multi Uav

For the large-scale search and rescue (S&R) scenarios, the centralized and distributed multi-UAV multitask assignment algorithms for multi-UAV systems have the problems of heavy computational load and massive communication burden, which make it hard to guarantee the effectiveness and convergence speed of their task assignment results. To address this issue, this paper proposes a hierarchical task assignment strategy. Firstly, a model decoupling algorithm based on density clustering and negotiation mechanism is raised to decompose the large-scale task assignment problem into several nonintersection and complete small-scale task assignment problems, which effectively reduces the required computational amount and communication cost. Then, a cluster head selection method based on multiattribute decision is put forward to select the cluster head for each UAV team. These cluster heads will communicate with the central control station about the latest assignment information to guarantee the completion of S&R mission. At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. Simulation results and analyses comprehensively verify the feasibility and effectiveness of the proposed hierarchical task assignment strategy in large-scale S&R scenarios with dispersed clustering targets.

scholarly journals Multi-UAV Rapid-Assessment Task-Assignment Problem in a Post-Earthquake Scenario

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 74542-74557 ◽  
Author(s):  
Moning Zhu ◽  
Xiaoxia Du ◽  
Xuehua Zhang ◽  
He Luo ◽  
Guoqiang Wang
Keyword(s):  
Assignment Problem ◽  
Rapid Assessment ◽  
Task Assignment ◽  
Earthquake Scenario ◽  
Assessment Task ◽  
Task Assignment Problem ◽  
Multi Uav

Dynamic Dependent Tasks Assignment for Grid Computing

2011 ◽  
Vol 3 (2) ◽  
pp. 44-58 ◽  
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

A Hybrid Swarm Optimization Algorithm for Complex Assignment Problem

2010 ◽  
Vol 26-28 ◽  
pp. 1151-1154
Author(s):  
Zong Li Liu ◽  
Jie Cao ◽  
Zhan Ting Yuan
Keyword(s):  
Assignment Problem ◽  
Production Scheduling ◽  
Large Scale ◽  
Optimization Problems ◽  
Graph Model ◽  
Task Assignment ◽  
Hybrid Swarm ◽  
Swarm Optimization ◽  
Computing Technique ◽  
Task Assignment Problem

The optimization of complex systems, such as production scheduling systems and control systems, often encounters some difficulties, such as large-scale, hard to model, time consuming to evaluate, NP-hard, multi-modal, uncertain and multi-objective, etc. It is always a hot research topic in academic and engineering fields to propose advanced theory and effective algorithms. As a novel evolutionary computing technique, particle swarm optimization (PSO) is characterized by not being limited by the representation of the optimization problems, and by global optimization ability, which has gained wide attentation and research from both academic and industry fields. The task assignment problem in the enterprise with directed graph model is presented. Task assignment problem with buffer zone is solved via a hybrid PSO algorithm. Simulation result shows that the model and the algorithm are effective to the problem.

scholarly journals Task Assignment for Multi-UAV under Severe Uncertainty by Using Stochastic Multicriteria Acceptability Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoxuan Hu ◽  
Jing Cheng ◽  
He Luo
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Task Assignment ◽  
Uncertain Information ◽  
Simulation Experiments ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Severe Uncertainty ◽  
Task Assignment Problem ◽  
Multi Uav ◽  
Assignment Approach

This paper considers a task assignment problem for multiple unmanned aerial vehicles (UAVs). The UAVs are set to perform attack tasks on a collection of ground targets in a severe uncertain environment. The UAVs have different attack capabilities and are located at different positions. Each UAV should be assigned an attack task before the mission starts. Due to uncertain information, many criteria values essential to task assignment were random or fuzzy, and the weights of criteria were not precisely known. In this study, a novel task assignment approach based on stochastic Multicriteria acceptability analysis (SMAA) method was proposed to address this problem. The uncertainties in the criteria were analyzed, and a task assignment procedure was designed. The results of simulation experiments show that the proposed approach is useful for finding a satisfactory assignment under severe uncertain circumstances.

scholarly journals An Optimal Task Assignment Strategy in Cloud-Fog Computing Environment

2021 ◽  
Vol 11 (4) ◽  
pp. 1909
Author(s):  
Jung-Fa Tsai ◽  
Chun-Hua Huang ◽  
Ming-Hua Lin
Keyword(s):  
Internet Of Things ◽  
Assignment Problem ◽  
Fog Computing ◽  
Task Assignment ◽  
The Internet ◽  
Computing Environment ◽  
Computing Systems ◽  
Assignment Strategy ◽  
The Internet Of Things ◽  
Task Assignment Problem

With the advent of the Internet of Things era, more and more emerging applications need to provide real-time interactive services. Although cloud computing has many advantages, the massive expansion of the Internet of Things devices and the explosive growth of data may induce network congestion and add network latency. Cloud-fog computing processes some data locally on edge devices to reduce the network delay. This paper investigates the optimal task assignment strategy by considering the execution time and operating costs in a cloud-fog computing environment. Linear transformation techniques are used to solve the nonlinear mathematical programming model of the task assignment problem in cloud-fog computing systems. The proposed method can determine the globally optimal solution for the task assignment problem based on the requirements of the tasks, the processing speed of nodes, and the resource usage cost of nodes in cloud-fog computing systems.

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

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hua Yang ◽  
Jungang Yang ◽  
Wendong Zhao ◽  
Cuntao Liu
Keyword(s):  
Energy Consumption ◽  
User Satisfaction ◽  
Assignment Problem ◽  
Information Acquisition ◽  
Time Window ◽  
Task Assignment ◽  
Total Energy Consumption ◽  
Time Window Constraints ◽  
Task Assignment Problem ◽  
Multi Uav

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.

scholarly journals A Two-Layer Task Assignment Algorithm for UAV Swarm Based on Feature Weight Clustering

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaowei Fu ◽  
Peng Feng ◽  
Bin Li ◽  
Xiaoguang Gao
Keyword(s):  
Large Scale ◽  
Task Assignment ◽  
Small Scale ◽  
Resource Assignment ◽  
Assignment Algorithm ◽  
Uav Swarm ◽  
Feature Weight ◽  
Bundle Algorithm ◽  
Aerial Vehicle ◽  
Simulation Results

For the large-scale operations of unmanned aerial vehicle (UAV) swarm and the large number of UAVs, this paper proposes a two-layer task and resource assignment algorithm based on feature weight clustering. According to the numbers and types of task resources of each UAV and the distances between different UAVs, the UAV swarm is divided into multiple UAV clusters, and the large-scale allocation problem is transformed into several related small-scale problems. A two-layer task assignment algorithm based on the consensus-based bundle algorithm (CBBA) is proposed, and this algorithm uses different consensus rules between clusters and within clusters, which ensures that the UAV swarm gets a conflict-free task assignment solution in real time. The simulation results show that the algorithm can assign tasks effectively and efficiently when the number of UAVs and targets is large.

Multi-UCAV Air Combat Task Assignment under Uncertain Information Environment

2014 ◽  
Vol 494-495 ◽  
pp. 1098-1101 ◽  
Author(s):  
Xia Chen ◽  
De Hui Wang
Keyword(s):  
Particle Swarm Optimization Algorithm ◽  
Task Assignment ◽  
Information Environment ◽  
Uncertain Information ◽  
Analysis Method ◽  
Discrete Particle Swarm Optimization ◽  
Allocation Model ◽  
Air Combat ◽  
Task Assignment Problem ◽  
Multi Uav

For UAV air combat task assignment problem, this paper presents an analysis method. Firstly, we analyzes the unmanned combat situation, establish the UAV air combat situation advantage function and interval information combat task allocation model. And then put forward multi-UAV air combat decision method of the discrete particle swarm optimization algorithm based on interval number sequence. Finally, we carry on the simulation, the simulation results show that the algorithm can effectively and reasonably solve the problem of multi-UAV air combat decision.

Task Assignment for Multiple-Application Workload with Streaming Ones in MPSoC Using Shared Memory

2012 ◽  
Vol 263-266 ◽  
pp. 1781-1785
Author(s):  
Qi Zuo
Keyword(s):  
Shared Memory ◽  
Large Scale ◽  
Task Assignment ◽  
Streaming Application ◽  
Streaming Applications ◽  
Multiple Application ◽  
Memory Contention ◽  
Assignment Strategy ◽  
Overall Performance ◽  
On Chip

Large scale Multi-Processor System-on-a-chip (MPSoC) based on Network on Chip (NoC) can support multiple applications running simultaneously. When the multiple-application workload includes streaming applications processing massive data, the communication concentrated on shared memory can't be ignored. In this paper, we propose a task assignment strategy for multiple-application workload which includes one streaming application on a NoC-based MPSoC. The proposed algorithm first assigns the streaming application centering the multi-port shared memory, and then assigns the other applications minimizing external communication congestion. By adopting the proposed algorithm, the memory-contention tasks are assigned to the PEs close to the shared memory and the overall congestion is minimized. This allows the system to provide better overall performance.

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