相关论文: Energy-Efficient Dynamic Edge Computing with Elect…
Multi-access edge computing (MEC) has already shown the potential in enabling mobile devices to bear the computation-intensive applications by offloading some tasks to a nearby access point (AP) integrated with a MEC server (MES). However,…
In this paper, we propose a novel offloading learning approach to compromise energy consumption and latency in multi-tier network with mobile edge computing. In order to solve this integer programming problem, instead of using conventional…
In mobile computation offloading (MCO), mobile devices (MDs) can choose to either execute tasks locally or to have them executed on a remote edge server (ES). This paper addresses the problem of assigning both the wireless communication…
Mobile edge computing (MEC) has recently emerged as a promising technology to release the tension between computation-intensive applications and resource-limited mobile terminals (MTs). In this paper, we study the delay-optimal computation…
Wireless powered mobile edge computing (WP-MEC) has been recognized as a promising solution to enhance the computational capability and sustainable energy supply for low-power wireless devices (WDs). However, when the communication links…
A promising technique to provide mobile applications with high computation resources is to offload the processing task to the cloud. Utilizing the abundant processing capabilities of the clouds, mobile edge computing enables mobile devices…
This work considers the problem of energy efficiency maximization in a RIS-based communication link, subject to not only the conventional maximum power constraints, but also additional constraints on the maximum exposure to electromagnetic…
Mobile edge computing (MEC) enables the provision of high-reliability and low-latency applications by offering computation and storage resources in close proximity to end-users. Different from traditional computation task offloading in MEC…
The growing number of wireless edge devices has magnified challenges concerning energy, bandwidth, latency, and data heterogeneity. These challenges have become bottlenecks for distributed learning. To address these issues, this paper…
In Federated Learning (FL), a global statistical model is developed by encouraging mobile users to perform the model training on their local data and aggregating the output local model parameters in an iterative manner. However, due to…
Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we…
In this paper, we propose a transmit covariance optimization method to maximize the energy efficiency (EE) for a single-user distributed antenna system, where both the remote access units (RAUs) and the user are equipped with multiple…
Providing femto-access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smart-phones to the so called femto-cloud. Such offloading promises to be beneficial…
Merging mobile edge computing with the dense deployment of small cell base stations promises enormous benefits such as a real proximity, ultra-low latency access to cloud functionalities. However, the envisioned integration creates many new…
This paper studies an optimal workload allocation problem for a network of renewable energy-powered edge clouds that serve users located across various geographical areas. Specifically, each edge cloud is furnished with both an on-site…
Mobile edge computing (MEC) paves the way to alleviate the burden of energy and computation of mobile users (MUs) by offloading tasks to the network edge. To enhance the MEC server utilization by optimizing its resource allocation, a…
This work presents a machine learning approach to optimize the energy efficiency (EE) in a multi-cell wireless network. This optimization problem is non-convex and its global optimum is difficult to find. In the literature, either simple…
Mobile-edge computing (MEC) has recently emerged as a prominent technology to liberate mobile devices from computationally intensive workloads, by offloading them to the proximate MEC server. To make offloading effective, the radio and…
International standards bodies define Electromagnetic field (EMF) emission requirements that can be translated into control of the base station actual Effective Isotropic Radiated Power (EIRP), i.e., averaged over a sliding time window. In…
Mobile edge computing (MEC) provides computational services at the edge of networks by offloading tasks from user equipments (UEs). This letter employs an unmanned aerial vehicle (UAV) as the edge computing server to execute offloaded tasks…