Related papers: Faster Offloads by Unloading them -- The RDMA Case
The development of mobile services has impacted a variety of computation-intensive and time-sensitive applications, such as recommendation systems and daily payment methods. However, computing task competition involving limited resources…
Due to the high performance and safety requirements of self-driving applications, the complexity of modern autonomous driving systems (ADS) has been growing, instigating the need for more sophisticated hardware which could add to the energy…
In this paper, we investigate a non-orthogonal multiple access (NOMA) based mobile edge computing (MEC) network, in which two users may partially offload their respective tasks to a single MEC server through uplink NOMA. We propose a new…
Offloading is a popular way to overcome the resource and power constraints of networked embedded devices, which are increasingly found in industrial environments. It involves moving resource-intensive computational tasks to a more powerful…
The rapid growth of mobile devices and the increasing complexity of tasks have made energy efficiency a critical challenge in Multi-Access Edge Computing (MEC) systems. This paper explores energy-efficient offloading strategies in…
We investigate the problem of computation offloading in a mobile edge computing architecture, where multiple energy-constrained users compete to offload their computational tasks to multiple servers through a shared wireless medium. We…
Over the years, significant contributions have been made by the research and industrial sectors to improve wearable devices towards the Internet of Wearable Things (IoWT) paradigm. However, wearables are still facing several challenges.…
Application partitioning and code offloading are being researched extensively during the past few years. Several frameworks for code offloading have been proposed. However, fewer works attempted to address issues occurred with its…
Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) systems can use different multiple access schemes to coordinate multi-user task offloading. However, it is still unknown which scheme is the most energy-efficient, especially…
In recent years, with the prediction of Moore's law slowing down, utilization of hardware other than CPU such as FPGA which is energy effective is increasing. However, when using heterogeneous hardware other than CPUs, barriers of technical…
Heterogeneous multi-core architectures combine a few "host" cores, optimized for single-thread performance, with many small energy-efficient "accelerator" cores for data-parallel processing, on a single chip. Offloading a computation to the…
In this paper, the task offloading from vehicles with random velocities is optimized via a novel dynamic improvement framework. Particularly, in a vehicular network with multiple vehicles and base stations (BSs), computing tasks of vehicles…
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…
As multimodal and AI-driven services exchange hundreds of megabytes per request, existing IPC runtimes spend a growing share of CPU cycles on memory copies. Although both hardware and software mechanisms are exploring memory offloading,…
Artificial intelligence and distributed algorithms have been widely used in mechanical fault diagnosis with the explosive growth of diagnostic data. A novel intelligent fault diagnosis system framework that allows intelligent terminals to…
The increasing size of large language models (LLMs) challenges their usage on resource-constrained platforms. For example, memory on modern GPUs is insufficient to hold LLMs that are hundreds of Gigabytes in size. Offloading is a popular…
Heterogeneous multi-core architectures combine on a single chip a few large, general-purpose host cores, optimized for single-thread performance, with (many) clusters of small, specialized, energy-efficient accelerator cores for…
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…
In recent years, with the prediction of Moore's law slowing down, utilization of hardware other than CPU such as FPGA which is energy effective is increasing. However, when using heterogeneous hardware other than CPUs, barriers of technical…
This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, multiple base stations, and a malicious eavesdropper. Specifically, the users adopt the partial offloading strategy by partitioning the…