The opportunistic fog radio access network (OF-RAN) is a promising RAN architecture proposed for next-generation cellular networks. OF-RAN extends the current fog RAN (F-RAN) architecture by introducing virtual fog access points (v-FAPs) that can be...
Task assignment is a crucial problem in wireless sensor networks (WSNs) that may affect the completion quality of sensing tasks. From the perspective of global optimization, a transmission-oriented reliable and energy-efficient task allocation (TRETA...
Emergency event monitoring is a hot topic in wireless sensor networks (WSNs). Benefiting from the progress of Micro-Electro-Mechanical System (MEMS) technology, it is possible to process emergency events locally by using the computing capacities of r...
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...
This paper addresses multiple task assignment and path-planning problems for a multiple unmanned surface vehicle (USVs) system. Since it is difficult to solve multi-task allocation and path planning together, we divide them into two sub-problems, mul...
Heterogeneous graph embedding has become a hot topic in network embedding in recent years and has been widely used in lots of practical scenarios. However, most of the existing heterogeneous graph embedding methods cannot make full use of all the aux...
In healthcare applications, numerous sensors and devices produce massive amounts of data which are the focus of critical tasks. Their management at the edge of the network can be done by Fog computing implementation. However, Fog Nodes suffer from la...
Decentralized P2P networks have emerged as robust instruments to execute computing tasks, with enhanced security and transparency. Solutions such as Blockchain have proved to be successful in a large catalog of critical applications such as cryptocur...
With the increasing diversity and complexity of tasks assigned to unmanned aerial vehicles (UAVs), the demands on task assignment and sequencing technologies have grown significantly, particularly for large UAV tasks such as multi-target reconnaissan...
The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest...
Satellite edge computing (SEC) has garnered significant attention for its potential to deliver services directly to users. However, the uneven distribution of receiving tasks among satellites in the constellation can lead to uneven utilization of com...
Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging pr...
IoT-based smart transportation monitors vehicles, cargo, and driver statuses for safe movement. Due to the limited computational capabilities of the sensors, the IoT devices require powerful remote servers to execute their tasks, and this phenomenon...
The well known cloud computing is being extended by the idea of fog with the computing nodes placed closer to end users to allow for task processing with tighter latency requirements. However, offloading of tasks (from end devices to either the cloud...
In the process of the collaborative work of Unmanned Aerial Vehicle (UAV) clusters, the cluster communication node test is often carried out by a single-node test, which leads to poor topology and robustness of the overall network system, an imbalanc...
In volunteer computing (VC), the expected availability time and the actual availability time provided by volunteer nodes (VNs) are usually inconsistent. Scheduling tasks with precedence constraints in VC under this situation is a new challenge. In th...
This paper investigates the problem of coordinated resource allocation for multiple unmanned aerial vehicles (UAVs) to address the scarcity of communication resources in disaster-affected areas. UAVs carrying modules of free space optical (FSO) and r...
We consider the distributed stochastic gradient descent problem, where a main node distributes gradient calculations among n workers. By assigning tasks to all workers and waiting only for the k fastest ones, the main node can trade off the algorithm...
In this work, we investigate an energy-aware multi-robot task-allocation (MRTA) problem in a cluster of the robot network that consists of a base station and several clusters of energy-harvesting (EH) robots. It is assumed that there are
Edge computing (EC) plays a critical role in advancing the next-generation Industrial Internet of Things (IIoT) by enhancing production, maintenance, and operational outcomes across heterogeneous network boundaries. This study builds upon EC intellig...
This paper improves the timeliness of satellite mission planning to cope with the rapid response to changes. In this paper, satellite mission planning is investigated. Firstly, the satellite dynamics model and mission planning model are established,...
Multi-robot systems (MRSs) are currently being used to perform agricultural tasks. In this regard, the deployment of heterogeneous MRSs will be essential for achieving more efficient and innovative farming in the future. In this paper, we propose a m...
The network lifetime of wireless rechargeable sensor network (WRSN) is commonly extended through routing strategy or wireless charging technology. In this paper, we propose an optimization algorithm from the aspects of both charging and routing proce...
In real-time distributed systems, it is important to provide offline guarantee for an upper-bound of each real-time task’s end-to-end delay, which has been achieved by assigning proper intermediate deadlines of individual real-time tasks at eac...
In order to find a suitable designer team for the collaborative design crowdsourcing task of a product, we consider the matching problem between collaborative design crowdsourcing task network graph and the designer network graph. Due to the differen...
Sensor nodes perform missions based on the effectual invariable coverage of events, and it is commonly guaranteed by the determinate deployment for sensor nodes who deviate from the optimum site frequently. To reach the optimal coverage effect with t...
This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds...
The increase in computation and sensing capabilities as well as in battery duration of commercially availableWireless Sensors Network (WSN) nodes are making the paradigm of an horizontal ambient intelligence infrastructure feasible. Accordingly, the...
The analysis of network structure is essential to many scientific areas ranging from biology to sociology. As the computational task of clustering these networks into partitions, i.e., solving the community detection problem, is generally NP-hard, he...
The graph convolution network has received a lot of attention because it extends the convolution to non-Euclidean domains. However, the graph pooling method is still less concerned, which can learn coarse graph embedding to facilitate graph classific...
Deploying thousands of sensors across remote and challenging environments—such as the Amazon rainforest, Californian wilderness, or Australian bushlands—is a critical yet complex task for forest fire monitoring, while our backyard emulati...
Wireless multimedia sensor nodes sense areas that are uncorrelated to the areas covered by radio neighbouring sensors. Thus, node clustering for coordinating multimedia sensing and processing cannot be based on classical sensor clustering algorithms....
Due to the rapid development and popularity of the Internet, cloud computing has become an indispensable application service. However, how to assign various tasks to the appropriate service nodes is an important issue. Based on the reason above, an e...
Aspect-based sentiment analysis is a fine-grained task where the key goal is to predict sentiment polarities of one or more aspects in a given sentence. Currently, graph neural network models built upon dependency trees are widely employed for aspect...
This paper aims to propose a new fog cloud architecture that performs a joint energy-efficient task assignment (JEETA). The proposed JEETA architecture utilizes the dynamic application-partitioning algorithm (DAPTS), a novel algorithm that efficientl...
Fog computing has been prioritized over cloud computing in terms of latency-sensitive Internet of Things (IoT) based services. We consider a limited resource-based fog system where real-time tasks with heterogeneous resource configurations are requir...
These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Ta...
The IoT and cloud environment renders enormous quantities of geospatial information. Fog and mist computing is the scaling technology that handles geospatial data and sends it to the cloud storage system through fog/mist nodes. Installing a mist&ndas...
The unmanned aerial vehicle (UAV) has drawn increasing attention in recent years, especially in executing tasks such as natural disaster rescue and detection, and battlefield cooperative operations. Task assignment and path planning for multiple UAVs...
With the rapid development of digital intelligence, drones can provide many conveniences for people’s lives, especially in executing rescue missions in special areas. When executing rescue missions in remote areas, communication cannot be fully...
Link prediction in bipartite networks is a challenging task due to their distinct structural characteristics, where edges only exist between nodes of different types. Most existing methods are based on structural similarity, assigning similarity scor...
Wireless rechargeable sensor networks (WRSNs) address the energy scarcity problem in wireless sensor networks by introducing mobile chargers (MCs) to recharge energy-hungry sensor nodes. Scheduling MCs to charge the recharge nodes is the primary focu...
Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution lead...
The recent adoption of deep learning for diverse applications has required infrastructures to be scaled horizontally and hybrid configured vertically. As a result, efficient resource management for distributed deep learning (DDL) frameworks is becomi...
Although Convolutional Neural Networks (CNNs) have achieved remarkable accuracy in intelligent tasks, their increasing complexity hinders low-latency execution. While edge computing mitigates the wide-area network delays typical of cloud-based infere...
With the increasing popularity of wireless networks and the development of smart cities, the Mobile Crowdsourcing System (MCS) has emerged as a framework for automatically assigning spatiotemporal tasks to workers. The study of mobile crowdsourcing m...
With the rapid increase in computation-intensive tasks, the current research task is to minimize energy consumption due to resource constraints and increased cost. For complex computations where multiple computer systems are required to execute a sin...
Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these ap...
Over the past few years, decentralization of multi-agent robotic systems has become an important research area. These systems do not depend on a central control unit, which enables the control and assignment of distributed, asynchronous and robust ta...
Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying...
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