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By offering shared computational facilities to which mobile devices can offload their computational tasks, the mobile edge computing framework is expanding the scope of applications that can be provided on resource-constrained devices. When…
This paper explores the growing need for task-oriented communications in warehouse logistics, where traditional communication Key Performance Indicators (KPIs)-such as latency, reliability, and throughput-often do not fully meet task…
Vehicular edge computing (VEC) is a promising technology to support real-time vehicular applications, where vehicles offload intensive computation tasks to the nearby VEC server for processing. However, the traditional VEC that relies on…
With the rapid development of vehicular networks, various applications that require high computation resources have emerged. To efficiently execute these applications, vehicular edge computing (VEC) can be employed. VEC offloads the…
Incorporating mobile edge computing (MEC) in Internet of Things (IoT) enables resource-limited IoT devices to offload their computation tasks to a nearby edge server. In this paper, we investigate an IoT system assisted by the MEC technique…
Edge computing offers the distinct advantage of harnessing compute capabilities on resources located at the edge of the network to run workloads of relatively weak user devices. This is achieved by offloading computationally intensive…
In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. Those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire.…
In the traditional cellular-based mobile edge computing (MEC), users at the edge of the cell are prone to suffer severe inter-cell interference and signal attenuation, leading to low throughput even transmission interruptions. Such edge…
Today's robotic systems are increasingly turning to computationally expensive models such as deep neural networks (DNNs) for tasks like localization, perception, planning, and object detection. However, resource-constrained robots, like…
Wearable devices, such as smartwatches and head-mounted displays, are increasingly used for prolonged tasks like remote learning and work, but sustained interaction often leads to user fatigue, reducing efficiency and engagement. This study…
Mobile virtual reality (VR) delivery is gaining increasing attention from both industry and academia due to its ability to provide an immersive experience. However, achieving mobile VR delivery requires ultra-high transmission rate, deemed…
Being an up-and-coming application scenario of mobile edge computing (MEC), the post-disaster rescue suffers multitudinous computing-intensive tasks but unstably guaranteed network connectivity. In rescue environments, quality of service…
Edge computing is deemed a promising technique to execute latency-sensitive applications by offloading computation-intensive tasks to edge servers. Extensive research has been conducted in the field of end-device to edge server task…
The mobile edge computing framework offers the opportunity to reduce the energy that devices must expend to complete computational tasks. The extent of that energy reduction depends on the nature of the tasks, and on the choice of the…
Predictive power allocation is conceived for energy-efficient video streaming over mobile networks using deep reinforcement learning. The goal is to minimize the accumulated energy consumption of each base station over a complete video…
Mobile edge computing (MEC) is an emerging paradigm that mobile devices can offload the computation-intensive or latency-critical tasks to the nearby MEC servers, so as to save energy and extend battery life. Unlike the cloud server, MEC…
Virtual reality finds various applications in productivity, entertainment, and training scenarios requiring working memory and attentional resources. Working memory relies on prioritizing relevant information and suppressing irrelevant…
In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an…
Edge computing plays an essential role in the vehicle-to-infrastructure (V2I) networks, where vehicles offload their intensive computation tasks to the road-side units for saving energy and reduce the latency. This paper designs the optimal…
Collaborative edge computing uses edge nodes in different locations to execute tasks, necessitating dynamic task offloading decisions to maintain low latency and high reliability, especially under unpredictable node failures. Although deep…