The timeliness of maritime rescue critically depends on the efficient generation of solutions and the execution of missions. Therefore, this study aims to implement maritime rescue task allocation and sequencing (MRTAS) while ensuring solution genera...
Real-time constrained multiprocessor systems have been widely applied across various domains. In this paper, we focus on the scheduling algorithm for directed acyclic graph (DAG) tasks under partitioned scheduling on multiprocessor systems. Effective...
This study proposes a task-offloading and resource allocation strategy in multidomain cooperation (TARMC) for the industrial Internet of Things (IIoT) to resolve the problem of the non-uniform distribution of task computation among various cluster do...
Mobile crowdsensing utilizes the devices of a group of users to cooperatively perform some sensing tasks, where finding the perfect allocation from tasks to users is commonly crucial to guarantee task completion efficiency. However, existing works us...
Satellite edge computing has attracted the attention of many scholars, but the limited resources of satellite networks bring great difficulties to the processing of edge-computing-dependent tasks. Therefore, under the system model of the satellite-te...
Cross-domain cooperative task allocation is a complex and challenging issue in the field of multi-agent task allocation that requires urgent attention. This paper proposes a task allocation method based on the multi-strategy improved dung beetle opti...
An AGV system can be used to transport different-size materials in an assembly line. The hybrid task allocation problem is involved in the assembly line, where both single-AGV tasks and multi-AGV tasks exist. However, there is little research on this...
To address load–energy dynamic coupling in heterogeneous unmanned aerial vehicle (UAV) emergency rescue, this paper proposes an energy-coupled heterogeneous UAV task allocation (EC-HUTA) model that explicitly characterizes nonlinear interdepend...
In modern supply chain systems, task allocation is indispensable to logistics transportation. Sound and efficient allocation strategies are key to improving distribution efficiency and resource utilization. To address the limitations of traditional o...
In recent years, the unmanned aerial vehicle-assisted internet of vehicles has been extensively studied to enhance communication and computation services in vehicular environments where ground infrastructures are limited or absent. However, due to th...
Maritime dynamic observation missions, such as environmental monitoring, marine ranching inspection, and emergency response, typically require large-scale and high-efficiency operations in complex and variable maritime environments. Unmanned Surface...
Leveraging non-terrestrial networks for edge computing is crucial for the development of 6G, the Internet of Things, and ubiquitous digitalization. In such scenarios, diverse tasks often exhibit continuously distributed attributes, while existing res...
With the continuous development of artificial intelligence, swarm control and other technologies, the application of Unmanned Aerial Vehicles (UAVs) in the battlefield is more and more extensive, and the UAV swarm is increasingly playing a prominent...
In practical applications, the utilization of multi-robot systems (MRS) is extensive and spans various domains such as search and rescue operations, mining operations, agricultural tasks, and warehouse management. The surge in demand for MRS has prom...
The rapid advancement of unmanned aerial vehicle (UAV) technology has led to its widespread adoption in military reconnaissance, disaster monitoring, environmental inspection, and related fields. However, a single UAV often faces limitations when exe...
With the emergence of increasingly computing-intensive and delay-sensitive tasks, the processing of computing tasks on cloud servers cannot meet the current needs any longer. The emergence of mobile edge computing (MEC) technology and the popularity...
Task offloading and resource allocation is a research hotspot in cloud-edge collaborative computing. Many existing pieces of research adopted single-agent reinforcement learning to solve this problem, which has some defects such as low robustness, la...
This work presents a comparison between several task distribution methods for load balancing with the help of an original implementation of a solution based on a multi-agent system. Among the original contributions, one can mention the design and imp...
Today, with the presence of 5G communication systems, including Internet of Things (IoT) technology, there is a high demand for mobile devices (especially smartphones, tablets, wearable technology, and so on). Regarding this proliferation and high de...
With the explosive growth of data at the edge in the Industrial Internet of Things (IIoT), edge devices are increasingly performing more data processing tasks to alleviate the load on cloud servers. To achieve this goal, Programmable Logic Controller...
With the rapid development of high-performance computing and parallel computing technology, by virtue of its cost-effectiveness, strong scalability, and easy programming, the multiprocessor system has gradually become the mainstream computing platfor...
The allocation of tasks among multiple Autonomous Underwater Vehicles (AUVs) with energy constraints in underwater environments presents an NP-complete problem with far-reaching consequences for marine exploration, environmental monitoring, and under...
Multi-robot systems, owing to their parallel operation and cooperative capabilities, have become an important means of improving the efficiency of complex workpiece machining. However, task allocation methods directly determine the overall system per...
In modern marine warfare, unmanned underwater vehicles (UUVs) have fast and efficient attack capabilities. However, existing research on UUV attack strategies is relatively limited, often ignoring the requirement for the effective allocation of diffe...
Autonomous air combat of unmanned aerial vehicles (UAVs) is a typical and difficult problem that must be studied in the field of military intelligence. The UAVs are required to work together to accomplish different tasks in the air combat. In this no...
Task offloading and resource allocation are the major elements of edge computing. A reasonable task offloading strategy and resource allocation scheme can reduce task processing time and save system energy consumption. Most of the current studies on...
Minimizing the schedule length of parallel applications, which run on a heterogeneous multi-core system and are subject to energy consumption constraints, has recently attracted much attention. The key point of this problem is the strategy to pre-all...
With the development of UAV technology, the task allocation problem of multiple UAVs is remarkable, but most of these existing heuristic methods are easy to fall into the problem of local optimization. In view of this limitation, deep transfer reinfo...
With the rapid development of sensor technology and mobile services, the service model of mobile crowd sensing (MCS) has emerged. In this model, user groups perceive data through carried mobile terminal devices, thereby completing large-scale and dis...
With the increasingly widespread application of unmanned aerial vehicle (UAV) systems in disaster monitoring, urban management, logistics transportation, and reconnaissance, efficient dynamic task allocation has become a key issue in improving task e...
With the rapid advancement of UAV technology and the increasing complexity of tasks, multi-UAV systems face growing challenges in task execution. Traditional task allocation algorithms often perform poorly when dealing with issues such as local optim...
To support multimedia and deep learning applications running on containers within a server, both processor cores and main memory space are critical resources for performance tuning. With the growing memory demands of applications to maintain intermed...
With the rapid advancement of unmanned aerial vehicle technology, the extensive application of multiple unmanned aerial vehicle systems in agriculture has led to significant innovations and benefits. Addressing the challenge of task allocation for mu...
Efficient task–channel allocation in satellite communication networks becomes particularly challenging when tasks are subject to both time and frequency constraints, and when resource failures or environmental changes invalidate an initially fe...
This paper develops a distributed method, namely, distributed allocation with time windows (DATW) for managing the multi-UAV task assignment problem (MTAP) with complex time window constraints. By aiming directly to minimize the average task completi...
In complex environments, Operators need to manage continuous, real-time information flows while handling unexpected situations within a limited timeframe. This can lead to high cognitive load, stress, fatigue, etc. To prevent such situations, Artific...
With the rapid development of e-commerce, warehousing and logistics systems are facing the dual challenges of increasing order processing demand and green and low-carbon transformation. Traditional manual and single-robot scheduling methods are not o...
Cooperative operations of Unmanned Underwater Vehicles (UUVs) have extensive applications in fields such as marine exploration, ecological observation, and subsea security. Path planning, as a key technology for UUV autonomous navigation, is crucial...
Artificial intelligence and distributed algorithms have been widely used in mechanical fault diagnosis with the explosive growth of diagnostic data. A novel intelligent fault diagnosis system framework that allows intelligent terminals to offload com...
Unmanned aerial vehicles (UAVs) are becoming more and more widely used in battlefield reconnaissance and target strikes because of their high cost-effectiveness, but task planning for large-scale UAV swarms is a problem that needs to be solved. To so...
The rapid proliferation of handheld intelligent devices and the advent of 5G technology have brought about convenient and fast services for people. In perception-oriented application services, participating users will upload sensitive mobile data in...
Introducing partial task offloading into vehicle edge computing networks (VECNs) can ease the burden placed on the Internet of Vehicles (IoV) by emerging vehicle applications and services. In this circumstance, the task offloading ratio and the resou...
Motivated by the inefficiencies where multi-agent systems fail to reconcile individual agent self-interest with global optimality and accommodate dynamic tasks as its population increases, this paper investigates a clustering allocation problem for l...
In UAV swarm adversarial applications, multi-agent task allocation requires high-level reasoning and accurate decision-making in dynamic environments. Although large language models (LLMs) have shown strong performance in zero-shot reasoning, they ca...
Edge computing is a promising technology to enable user equipment to share computing resources for task offloading. Due to the characteristics of the computing resource, how to design an efficient computation incentive mechanism with the appropriate...
To address the challenge of coordinated combat involving multiple UAVs in reconnaissance and search attacks, we propose the Multi-UAV Distributed Self-Organizing Cooperative Intelligence Surveillance and Combat (CISCS) strategy. This strategy employs...
Cooperative encirclement using multiple unmanned underwater vehicles (UUVs) is a critical task in underwater base defense, yet existing approaches typically rely on static risk rules that cannot fuse multi-source information dynamically and decouple...
A hierarchical mission planning method was proposed to solve a simultaneous attack mission planning problem for multi-unmanned aerial vehicles (UAVs). The method consisted of three phases aiming to decouple and solve the mission planning problem. In...
Mobile edge computing (MEC), which sinks the functions of cloud servers, has become an emerging paradigm to solve the contradiction between delay-sensitive tasks and resource-constrained terminals. Task offloading assisted by service caching in a col...
With the rapid increase of smart Internet of Things (IoT) devices, edge networks generate a large number of computing tasks, which require edge-computing resource devices to complete the calculations. However, unreasonable edge-computing resource all...
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