A Supplemental Zero-Energy Downlink Air-Interface Enabling 40-Year Battery Life in IoT Devices
RESEARCH PAPER / Dec 2020 / 5G, Computing and Optimization, Network and Communications
DiagSys: a dataset collection framework for root cause analysis from end-devices
RESEARCH PAPER / Dec 2020 / Network and Communications, 5G, Wireless communication, Computing and Optimization
For Internet operators, on-line service providers and end-users, representative operational measurements are crucial to monitor and diagnose the performance of networks and on-line services. While numerous approaches have been proposed to measure performance, only a few works fully adopt an end-user perspective by taking measurements from within web browsers. In...
A Machine Learning-Based Task Assignment Framework for Cooperative Mobile Edge Computing
RESEARCH PAPER / Nov 2020 / 5G, Wireless communication, Network and Communications, Computing and Optimization
This paper investigates the task management for cooperative mobile edge computing (MEC), where a set of geographically distributed heterogeneous edge nodes not only cooperate with remote cloud data centers but also help each other to jointly process tasks and support real-time IoT applications at the edge of the network. Especially,...
Quality of Service Optimization in Mobile Edge Computing Networks via Deep Reinforcement Learning
RESEARCH PAPER / Sep 2020 / Wireless communication, Network and Communications, Computing and Optimization
Mobile edge computing (MEC) is an emerging paradigm that integrates computing resources in wireless access networks to process computational tasks in close proximity to mobile users with low latency. In this paper, we propose an online double deep Q networks (DDQN) based learning scheme for task assignment in dynamic MEC...
Accelerated Nearest Neighbor Search with Quick ADC
RESEARCH PAPER / Jun 2017 / Computing & Optimization, Machine/Deep Learning/AI
Efficient Nearest Neighbor (NN) search in high-dimensional spaces is a foundation of many multimedia retrieval systems. Because it offers low responses times, Product Quantization (PQ) is a popular solution. PQ compresses high-dimensional vectors into short codes using several sub-quantizers, which enables in-RAM storage of large databases. This allows fast answers...
Combining dimensionality reduction with random forests for multi-label classification under interactivity constraints
RESEARCH PAPER / May 2017 / Machine learning/ Deep learning /Artificial Intelligence, Computing and Optimization
Learning from multi-label data in an interactive framework is a challenging problem as algorithms must withstand some additional constraints: in particular, learning from few training examples in a limited time. A recent study of multi-label classifier behaviors in this context has identified the potential of the ensemble method “Random Forest...