Large language model (LLM) inference on edge systems must exploit heterogeneous central processing unit (CPU) and neural processing unit (NPU) resources under tight memory and latency constraints. Because prefilling and autoregressive decoding have d...
This paper investigates a fairness-aware task assignment problem, where traditional models prioritize operational effectiveness while overlooking workload fairness. Motivated by real-world airport operations, we propose a multi-objective task assignm...
AI accelerators increasingly operate under tight power, thermal, voltage, and timing margins, making workload-dependent thermal nonuniformity an important reliability concern. In systolic AI accelerators, localized activity concentration can create s...
The widening performance gap between processor speed and memory access latency has made data locality a critical bottleneck in high-performance computing. In Non-Uniform Memory Access (NUMA) and distributed memory systems, remote accesses incur penal...
Data centers can provide demand-side flexibility by coordinating computing workloads, cooling systems, and on-site energy resources. However, facility demand varies with information technology (IT) load and cooling operation, making a fixed power usa...
This study numerically investigates the transient thermal response of a raised-floor data center under dynamic AI server loads. Power profiles of DGX A100 servers running GEMM, VGG-19, and ResNet-152 workloads were used as time-varying boundary condi...
Nuclear power plants increasingly utilize digitalized systems, including computer-based procedures (CBPs) and automation. These novel technologies require human factors’ evaluation to ensure safety. Potentially, automation contributes to safety...
Collaborative flight formations represent a promising operational model, but the integration of multi-source information in manned interfaces often results in cognitive overload and reduced situation awareness. This study evaluates the effectiveness...
Data centers are continuously expanding due to AI workload growth, leading to increasingly prominent high-energy-consumption issues. In heterogeneous data centers, the diversity of IT and cooling equipment complicates holistic energy optimization. Th...
Smartphone battery drain is governed by coupled effects of workload, electrochemical aging, and thermal feedback. Nonlinear behaviors such as voltage collapse remain challenging for traditional models. An electrochemical-informed equivalent-circuit a...
Inadequate resources and facilities with zero latency affect the efficiencies of task scheduling (TS) and resource allocation (RA) in the fog paradigm. Only the incoming tasks can be completed within the deadline if the resource availability in the c...
Cloud computing has transformed the delivery of modern applications and services by providing scalable, flexible, and cost-effective access to computing resources. One of the most critical challenges in cloud environments is the efficient distributio...
The rapid proliferation of AI-enabled Industrial Internet of Things (IIoT) applications has significantly increased the energy consumption of shared edge computing infrastructures. Despite this sustainability challenge, contemporary resource pricing...
The tremendous growth of big data analysis and IoT (Internet of Things) has made cloud computing an integral part of society. The prominent problem associated with data centers is the growing energy consumption, which results in environmental polluti...
Distributed Kubernetes clusters provide robust solutions for geo-redundancy and fault tolerance in modern cloud architectures. However, default scheduling mechanisms primarily optimize for resource availability, often neglecting network topology, int...
Multi-bit upsets (MBUs) are a growing reliability threat in high-density SDRAM, particularly in radiation-prone embedded systems. This paper presents a large-scale FPGA-based fault injection (FI) study targeting external SDRAM in a cache-enabled LEON...
Mobile application workloads are inherently driven by user interactions and are characterized by short execution phases and frequent behavioral changes. These properties make it difficult for traditional micro-architecture analysis approaches, which...
Microservice deployment and request routing can help improve server efficiency and the performance of large-scale mobile edge computing (MEC). However, the joint optimization of microservice deployment and request routing is extremely challenging, as...
The emergence of Building Information Modelling, Internet of Things, and Cave Automatic Virtual Environments (CAVEs) has created new opportunities for remote monitoring and decision-making in the operational built environment, yet empirical evidence...
Modern flight decks incorporate advanced automation and real-time data systems to improve safety and efficiency. However, maintaining situational awareness under a high workload remains a critical challenge, particularly when attentional resources ar...
This paper presents a controlled comparative evaluation of SQL and NoSQL persistence mechanisms in containerized microservice architectures under variable workload conditions. Three persistence configurations—SQL with indexing, SQL without inde...
Air traffic controllers have to make quick decisions to keep air traffic safe. Their behaviors have a significant impact on the operation of the air traffic management (ATM) system. Automation tools have enhanced the ATM system’s capability by reduci...
With the rapid development of edge-intelligence systems, multi-UAV platforms have become vital for large-scale 3D reconstruction. However, efficient task scheduling remains a critical challenge due to constraints on UAV energy, communication range, a...
Serverless computing has gained significant attention in recent years. However, the cold start problem remains a major challenge, not only because of the substantial latency it introduces to function execution time, but also because frequent cold sta...
The non-uniform memory access (NUMA) architecture is the de facto norm in modern server processors. Applications running on NUMA processors may suffer significant performance degradation (NUMA effect) due to the non-uniform memory accesses, including...
Assistant Based Speech Recognition (ABSR) systems for air traffic control radiotelephony communication have shown their potential to reduce air traffic controllers’ (ATCos) workload. Related research activities mainly focused on utterances for...
The fast growth of AI and large-scale industrial compute infrastructures has led to unsustainable increases in energy consumption and greenhouse gas emissions on a global scale, creating serious sustainability issues in today’s modern cloud com...
Sensing the interaction between the pilot and the control inceptors can provide important information about the pilot’s activity during flight, potentially enabling the objective measurement of the pilot workload, the application of preventive...
Ensuring excellent Quality of Service (QoS) while limiting financial expenses is seriously challenged by the growing scope and complexity of the Internet of Things (IoT). Though established under ETSI, the OneM2M standard provides a consistent middle...
Enhancing transparency through interface design is an effective method for improving driving safety while reducing driver workloads, potentially fostering human–machine collaboration. However, to ensure system usability and safety, operator psy...
Efficient resource allocation and task scheduling remain fundamental challenges in cloud computing because of resource heterogeneity, dynamic workload characteristics, and the increasing demand for scalable, energy-efficient, and sustainable cloud in...
The Social Internet of Things (SIoT) has emerged as a promising paradigm for addressing interoperability, adaptability, and intelligent collaboration challenges in smart city environments. However, existing solutions often provide only partial suppor...
We propose a new NAND programming scheme called the lazy reprogramming scheme (LazyRS) which divides a program operation into two stages, where the second stage is delayed until it is needed. LazyRS optimizes the program latency by skipping the secon...
This study presents a data-driven analysis of navigator stress and workload levels in simulated ship encounters within restricted waters, leveraging real-world automatic identification system (AIS) data from Makassar Port, Indonesia. Six close-quarte...
The latest cloud resource management research has revealed that virtual machine (VM) consolidation allows for effectively managing the physical resources of cloud data centers. However, a tremendous waste of power and physical resources has been poin...
Transformers are the cornerstone of natural language processing and other much more complicated sequential modelling tasks. The training of these models, however, requires an enormous number of computations, with substantial economic and environmenta...
2 August 2019
This paper presents the study on the association between in-vehicle music listening, physiological and psychological response, and driving performance, using the driving simulator approach, with which personality (temperament) was considered. The per...
The emergence of chiplet-based architectures represents a paradigm shift in post-Moore’s Law computing systems, offering substantial cost and yield advantages through functional disaggregation. However, the heterogeneity of inter-chiplet commun...
Sepsis early warning is hindered by data silos, temporal leakage, and threshold choices that obscure operational performance. We present a leakage-aware federated-learning evaluation pipeline that enforces group/temporal separation and compares model...
Elastic cloud systems are increasingly employing machine learning (ML) to automate resource scaling in response to variable workloads and stringent service-level objectives. However, current ML-based autoscalers are fragmented across different platfo...
Solid-State Drives (SSDs) have become the dominant storage medium in performance-sensitive systems due to their high throughput, reliability, and energy efficiency. However, inherent constraints in NAND flash memory—such as out-of-place writes,...
This article presents an ontology-driven Digital Twin (DT) for hotel front-desk operations that fuses two real-time data streams: (i) physiological and activity signals from wrist-worn wearables assigned to staff, and (ii) 3D people-positioning and o...
Dynamic edge-server allocation in mobile edge computing (MEC) networks is a challenging multi-objective optimization problem due to highly dynamic user demands, spatiotemporal traffic variations, and the need to simultaneously minimize service latenc...
The explosive growth of artificial intelligence (AI) services has led to massive scaling of GPU computing clusters, causing sharp rises in power consumption and carbon emissions. Although hardware-level accelerator enhancements and deep neural networ...
Federated learning (FL) enables collaborative maritime perception without transferring raw observations, but solar-powered clients must preserve energy for platform-specific duties. Existing energy-aware FL generally applies a common battery constrai...
Physical activity has been shown to improve the health and well-being of students, athletes and the general population, especially when it is properly monitored and responses are evaluated. However, data are mostly gathered without considering a valu...
Understanding and accurately estimating cognitive workload is crucial for the development of adaptive, user-centered interactive systems across a variety of domains including augmented reality, automotive driving assistance, and intelligent tutoring...
Directed acyclic graph (DAG)-aware task scheduling algorithms have been studied extensively in recent years, and these algorithms have achieved significant performance improvements in data-parallel analytic platforms. However, current DAG-aware task...
While automated driving has attracted more and more attention, human drivers still play an important role. Drivers must be aware of their surroundings and potential danger to take over the vehicle’s control immediately when the automation syste...
Fog computing has recently emerged as an extension of cloud computing in providing high-performance computing services for delay-sensitive Internet of Things (IoT) applications. By offloading tasks to a geographically proximal fog computing server in...
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