mobile computingmobile IPOur need to stay connected even when we are away from our home-networks is becoming increasingly important. This is not limited to the ability to send to and retrieve information from home servers, but also, the ability of others to connect to the mobile hosts and ...
Recent studies have shown the latency and energy consumption of deep neural networks can be significantly improved by splitting the network between the mobile device and cloud. This paper introduces a new deep learning architecture, called BottleNet, for reducing the feature size needed to be sent ...
Cloud exploitation by mobile devices breeds a new research domain called Mobile Cloud Computing (MCC). However, issues like portability and interoperability should be addressed for mobile augmentation which is a non-trivial task using component-based approaches. Service Oriented Architecture (SOA) is a...
A Survey on Mobile Cloud Computing Architecture , Applications and Challenges With an explosive growth of Mobile applications and emergence of Cloud Computing concept, Mobile Cloud Computing (MCC) has been introduced to be a potential technology. Hence it drives a strong demand for mobile cloud appli...
摘要原文 The article researches and analyzes the architecture and application fields of mobile computing clouds. Advantages of these technologies and problems occurring during their use are analyzed. At the same time, issues related to provision of demand for computing and memory resources of mobile de...
ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classificationarxiv2019 Seesaw-Net: Convolution Neural Network With Uneven Group Convolutionarxiv2019 ISBNet: Instance-aware Selective Branching Networkarxiv2019 Multinomial Distribution Learning for Effective Neural Architecture Searcharxi...
Such delay is inconvenient and make the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling to...
②在这方面,作者提出了一种基于Lyapunov优化的低复杂度动态计算卸载(LODCO)算法。LODCO在每个时隙中做出卸载决策,然后为UE分配CPU周期(如果执行本地执行)或分配传输功率(如果执行计算卸载)。该建议能够完全防止卸载的应用程序被丢弃的情况。 上述文章的缺点:由于快速的电池耗尽在当代网络中构成了重大障碍,因此卸载决策并...
[Feb. 2024] FedCache is featured on Phoenix Tech.缓存驱动联邦学习架构来了!专为个性化边缘智能打造 (The Cache-Driven Federated Learning Architecture is Coming! Built for Personalized Edge Intelligence). [Feb. 2024] FedCache is accepted byIEEE Transactions on Mobile Computing (TMC).FedCache: A Kno...
9. A Better Architecture for Mobile In Summary, It’s Worth the Effort Want to Learn More? From One to Three Tiers In the early days of computing, developers built applications that were running on a single computer. As technology progressed, most non trivial applications migrated towards a ...