相关论文: Automated Application Offloading through Ant-inspi…
The base motivation of Mobile Cloud Computing was empowering mobile devices by application offloading onto powerful cloud resources. However, this goal can't entirely be reached because of the high offloading cost imposed by the long…
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…
The need for increased performance of mobile device directly conflicts with the desire for longer battery life. Offloading compu-tation to multiple devices is an effective method to reduce energy consumption and enhance performance for…
An increasing number of mobile applications rely on Machine Learning (ML) routines for analyzing data. Executing such tasks at the user devices saves the energy spent on transmitting and processing large data volumes at distant…
Since its conception, smart app market has grown exponentially. Success in the app market depends on many factors among which the quality of the app is a significant contributor, such as energy use. Nevertheless, smartphones, as a subset of…
Computation offloading is indispensable for mobile edge computing (MEC). It uses edge resources to enable intensive computations and save energy for resource-constrained devices. Existing works generally impose strong assumptions on radio…
To cope with recent exponential increases in demand for mobile data, wireless Internet service providers (ISPs) are increasingly changing their pricing plans and deploying WiFi hotspots to offload their mobile traffic. However, these…
Offloading work to cloud is one of the proposed solutions for increasing the battery life of mobile devices. Most prior research has focused on computation-intensive applications, even though such applications are not the most popular ones.…
Context-aware applications process context information to support users in their daily tasks and routines. These applications can adapt their functionalities by aggregating context information through machine-learning and data processing…
Computation offloading at lower time and lower energy consumption is crucial for resource limited mobile devices. This paper proposes an offloading decision-making model using federated learning. Based on the task type and the user input,…
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…
Mobile devices supporting the "Internet of Things" (IoT), often have limited capabilities in computation, battery energy, and storage space, especially to support resource-intensive applications involving virtual reality (VR), augmented…
The ever increasing demands for using resource-constrained mobile devices for running more resource intensive applications nowadays has initiated the development of cyber foraging solutions that offload parts or whole computational…
With the development of Internet-of-Things (IoT), we witness the explosive growth in the number of devices with sensing, computing, and communication capabilities, along with a large amount of raw data generated at the network edge. Mobile…
The advent of 5G networking technologies has increased the expectations from mobile devices, in that, more sophisticated, computationally intense applications are expected to be delivered on the mobile device which are themselves getting…
We present a model for measuring the impact of offloading soft real-time jobs over multi-tier cloud infrastructures. The jobs originate in mobile devices and offloading strategies may choose to execute them locally, in neighbouring devices,…
Mobile devices such as smartphones and tablets have become ubiquitous in today's modern computing landscape. The applications that run on these mobile devices (often referred to as "apps") have become a primary means of computing for…
Mobile edge computing is a provisioning solution to enable Augmented Reality (AR) applications on mobile devices. AR mobile applications have inherent collaborative properties in terms of data collection in the uplink, computing at the…
To cope with the unprecedented surge in demand for data computing for the applications, the promising concept of multi-access edge computing (MEC) has been proposed to enable the network edges to provide closer data processing for mobile…
We constructed an open multi-access network platform using open-source hardware and software. The open multi-access network platform is characterized by the flexible utilization of network functions, integral management and control of wired…