In recent years, due to the existence of intricate interactions between multiple entities in complex networks, ranging from biology to social or economic networks, community detection has helped us to better understand these networks. In fact, ...

In the fraud detection, fraudsters frequently engage with numerous benign users to disguise their activities. Consequently, the fraud graph exhibits not only homogeneous connections between the fraudsters and the same labeled nodes, but also ...

With the surge of transportation data and diversification of services, the resources for data processing in intelligent transportation systems become more limited. In order to solve this problem, this paper studies the problem of computation ...

Blockchain technology combined with Federated Learning (FL) offers a promising solution for enhancing privacy, security, and efficiency in medical IoT applications across edge, fog, and cloud computing environments. This approach enables multiple ...

The rapid proliferation of Android apps has given rise to a dark side, where increasingly sophisticated malware poses a formidable challenge for detection. To combat this evolving threat, we present an explainable hybrid multi-modal framework. ...

Crowdsourcing provides a new problem-solving paradigm that utilizes the intelligence of crowds to solve computer-hard problems. Task assignment is a foundation problem in crowdsourcing systems and applications. However, existing task assignment ...

• A two-stage cooperative task assignment framework for crowdsourcing is proposed.
• Minimizing the total cooperation cost under the workload constraint of workers.
• The Individual cooperation cost highly depends on the global task ...

Surveillance systems are very important to prevent situations where armed people appear. To minimize human supervision, there are algorithms based on artificial intelligence that perform a large part of the identification and detection tasks. ...

• Efficient distributed infrastructure using Fog Computing approach.
• Weapon detection in distributed environments.
• Reduced communication from Edge to Cloud.
• Lower power consumption than Edge Computing or Cloud Computing.

This survey delves into the synergy between Digital Twin technology and Task Offloading within safety-critical sectors, offering a nuanced understanding of their integration, potential benefits, and associated challenges. By defining fundamental ...

In this paper, we address the challenge of minimizing system energy consumption for task offloading within non-line-of-sight (NLoS) mobile edge computing (MEC) environments. Our approach integrates an active reconfigurable intelligent surface (...

The widespread adoption of the Internet of Things (IoT) and deep learning (DL) have facilitated a social paradigm shift towards smart cities, accelerating the rapid construction of smart facilities. However, newly constructed facilities often ...

• Proactive maintenance of smart facilities can be achieved with federated learning
• Privacy of FL model parameters can be preserved with fully homomorphic encryption
• Our proposed method FedSTMA outperforms other existing cutting-edge ...

The generation of trajectory data has increased dramatically with the advent and widespread use of GPS-enabled devices. This rich source of data provides invaluable insights for various applications such as traffic optimization, urban planning, ...

The increase in the demand for eXtended Reality (XR)/Virtual Reality (VR) services in the recent years, poses a great challenge for Wi-Fi networks to maintain the strict latency requirements. In VR over Wi-Fi, latency is a significant issue. In ...

Although Deep Neural Networks (DNN) have become the backbone technology of several Internet of Things (IoT) applications, their execution in resource-constrained devices remains challenging. To cater for these challenges, collaborative deep ...

In day-to-day activities, the advanced technology like Internet of Things (IoT) emerges to improve the lifestyle of people. In metropolitan cities, real-time parking is the long-lasting problem that we face in our daily life activities. Urban ...

Mobile edge computing (MEC) enables computation intensive applications in the Internet of Vehicles (IoV) to no longer be limited by device resources. However, the lack of an effective task scheduling strategy will seriously affect users’ quality ...

In this paper, we design a hybrid kitchen safety guarding framework using embedded devices and onboard sensors to detect abnormal events and block gas sources in time through the Internet of Things (IoT). According to the relevant literature we ...

To tackle task offloading and path planning challenges in multi-UAV-assisted mobile edge computing, this paper proposes a task offloading and path optimization approach via multi-agent deep reinforcement learning. The primary goal is to minimize ...

Context modeling and recognition represent complex tasks that allow mobile and ubiquitous computing applications to adapt to the user’s situation. The real advantage of context-awareness in mobile environments mainly relies on the ...

• On-device modeling of social relationships and familiar places from mobile sensors.

Social Networks' omnipresence and ease of use has revolutionized the generation and distribution of information in today's world. However, easy access to information does not equal an increased level of public knowledge. Unlike ...

As the commercial use of 5G technologies has grown more prevalent, smart vehicles have become an efficient platform for delivering a wide array of services directly to customers. The vehicular crowdsourcing service (VCS), for example, can provide ...

• A blockchain-based Vehicular Crowdsourcing Service framework, RC-chain, is proposed.
• A novel reputation model is designed to improve Crowdsourcing Service Quality.
• Queueing theory applied to generate an efficient configuration ...