9 citations · 26 across the 16 of their papers we have counts for
17 papers
Energy-Efficient Timely Relevant IoT Data Retrieval with Wireless Memory Approximation
Junya Shiraishi, Zihang Song, Morten Andersen +1
Collecting relevant data from Internet of Things devices under freshness and energy constraints is a key challenge in 6G edge networks. A lightweight neural network on the device f…
Online Continual Learning for Anomaly Detection in IoT under Data Distribution Shifts
Matea Marinova, Shashi Raj Pandey, Junya Shiraishi +3
In this work, we present OCLADS, a novel communication framework with continual learning (CL) for Internet of Things (IoT) anomaly detection (AD) when operating in non-stationary e…
Link-Aware Energy-Frugal Continual Learning for Fault Detection in IoT Networks
Henrik C. M. Frederiksen, Junya Shiraishi, Cedomir Stefanovic +2
The use of lightweight machine learning (ML) models in internet of things (IoT) networks enables resource constrained IoT devices to perform on-device inference for several critica…
Wireless Memory Approximation for Energy-efficient Task-specific IoT Data Retrieval
Junya Shiraishi, Shashi Raj Pandey, Israel Leyva-Mayorga +1
The use of Dynamic Random Access Memory (DRAM) for storing Machine Learning (ML) models plays a critical role in accelerating ML inference tasks in the next generation of communica…
Online Reliable Anomaly Detection via Neuromorphic Sensing and Communications
Junya Shiraishi, Jiechen Chen, Osvaldo Simeone +1
This paper proposes a low-power online anomaly detection framework based on neuromorphic wireless sensor networks, encompassing possible use cases such as brain-machine interfaces…
Low-Power and Accurate IoT Monitoring Under Radio Resource Constraint
Takaho Shimokasa, Hiroyuki Yomo, Federico Chiariotti +2
This paper investigates how to achieve both low-power operations of sensor nodes and accurate state estimation using Kalman filter for internet of things (IoT) monitoring employing…
Dual-Mode Wireless Devices for Adaptive Pull and Push-Based Communication
Sara Cavallero, Fabio Saggese, Junya Shiraishi +4
This paper introduces a dual-mode communication framework for wireless devices that integrates query-driven (pull) and event-driven (push) transmissions within a unified time-frame…
Medium Access for Push-Pull Data Transmission in 6G Wireless Systems
Shashi Raj Pandey, Fabio Saggese, Junya Shiraishi +2
Medium access in 5G systems was tailored to accommodate diverse traffic classes through network resource slicing. 6G wireless systems are expected to be significantly reliant on Ar…
Time-constrained Federated Learning (FL) in Push-Pull IoT Wireless Access
Van Phuc Bui, Junya Shiraishi, Petar Popovski +1
Training a high-quality Federated Learning (FL) model at the network edge is challenged by limited transmission resources. Although various device scheduling strategies have been p…
Content-based Wake-up for Energy-efficient and Timely Top-k IoT Sensing Data Retrieval
Junya Shiraishi, Anders E. Kalør, Israel Leyva-Mayorga +3
Energy efficiency and information freshness are key requirements for sensor nodes serving Industrial Internet of Things (IIoT) applications, where a sink node collects informative…
Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems
Merim Dzaferagic, Marco Ruffini, Nina Slamnik-Krijestorac +21
Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will…
EcoPull: Sustainable IoT Image Retrieval Empowered by TinyML Models
Mathias Thorsager, Victor Croisfelt, Junya Shiraishi +1
This paper introduces EcoPull, a sustainable Internet of Things (IoT) framework empowered by tiny machine learning (TinyML) models for fetching images from wireless visual sensor n…
Coexistence of Push Wireless Access with Pull Communication for Content-based Wake-up Radios
Junya Shiraishi, Sara Cavallero, Shashi Raj Pandey +2
This paper considers energy-efficient connectivity for Internet of Things (IoT) devices in a coexistence scenario between two distinctive communication models: pull- and push-based…
Coexistence of Pull and Push Communication in Wireless Access for IoT Devices
Sara Cavallero, Fabio Saggese, Junya Shiraishi +3
We consider a setup with Internet of Things (IoT), where a base station (BS) collects data from nodes that use two different communication modes. The first is pull-based, where the…
Control Aspects for Using RIS in Latency-Constrained Mobile Edge Computing
Fabio Saggese, Victor Croisfelt, Francesca Costanzo +4
This paper investigates the role and the impact of control operations for dynamic mobile edge computing (MEC) empowered by Reconfigurable Intelligent Surfaces (RISs), in which mult…
TinyAirNet: TinyML Model Transmission for Energy-efficient Image Retrieval from IoT Devices
Junya Shiraishi, Mathias Thorsager, Shashi Raj Pandey +1
This letter introduces an energy-efficient pull-based data collection framework for Internet of Things (IoT) devices that use Tiny Machine Learning (TinyML) to interpret data queri…
Query Timing Analysis for Content-based Wake-up Realizing Informative IoT Data Collection
Junya Shiraishi, Anders E. Kalør, Federico Chiariotti +3
Information freshness and high energy-efficiency are key requirements for sensor nodes serving Industrial Internet of Things (IIoT) applications, where a sink node must collect inf…