Edge Computing
22 articles · search the full text for this term
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Carbon-Aware Autonomous AI Systems: Reinforcement Learning for Sustainable Cloud and Edge Computing
Abstract: The field of communication and information technology is expanding quickly. Because of this, a significant amount of carbon emissions are produced by cloud data centres and edge computing nodes. In fact they are now responsible for 3 to 4 percent of the worlds total greenhouse gas emissions. Most of the time people who manage these resources focus on how they are working and how quickly they can get things done.. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 2, 2026 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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Recent Trends and Techniques in the Advanced Microcontroller Bus Architecture (AMBA) Protocol: A Comprehensive Review
Abstract: ARM has created the Advanced Microcontroller Bus Architecture (AMBA) that is used as the main method for communication on chips in today’s embedded systems. Since AMBA is built to scale and combine with other components, it allows data transfer to high-performance and low-power components easily. The paper discusses how AMBA protocols have evolved and presents new trends of producing higher data rates, conserving energy, and lowering latency. This study offers …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 9–15 Read article
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Offloading Computation to the Cloud
Abstract: Mobile devices are increasingly relied upon for complex and resource-intensive applications such as real-time video processing, augmented reality, and machine learning. However, their limited computational power, storage capacity, and battery life pose significant challenges. Computation offloading to the cloud has emerged as a promising solution to overcome these limitations by transferring demanding tasks from mobile devices to remote cloud servers. This approach enables improved performance, reduced energy consumption, and enhanced …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 27–37 Read article
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Emerging Trends in 5G and Beyond-5G Wireless Networks
Abstract: Wireless networks have evolved in the blink of an eye from 4G to 5G and are progressing towards beyond-5G (B5G) frameworks, leading to revolutionary changes in connectivity, speed, and network smarts. This review discusses trending features, challenges, and future trends of 5G and B5G wireless communications technologies. It presents chief goals of 5G, such as ultra-low latency, high spectral efficiency, massive machine-type communication, and up to 10 Gbps user data …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 11–19 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Smart Trolley Billing System
Abstract: The Smart Trolley Billing System is an advanced automation solution designed to enhance retail efficiency by integrating IoT, embedded systems, and real-time data processing. Utilizing a GROW GM65 Barcode Scanner Module, Raspberry Pi 4, and a Capacitive Touchscreen display, the system streamlines checkout by capturing product data, dynamically updating a preloaded SQLite database, and displaying an itemized bill in real-time. Its Python-based software stack ensures efficient barcode processing, database management, …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 3, 2025 · pp. 29–36 Read article
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Energy Efficiency and Awareness in Edge Computing: A Critical Review of Challenges, Strategies, and Future Directions"
Abstract: Edge computing enhances distributed systems by processing data near its source, yet its rapid growth, driven by IoT, 5G, and smart applications, escalates energy consumption across billions of devices. This study critically analyzes energy-saving techniques across hardware, software, and network layers, highlighting the role of AI tools and user education in promoting energy awareness. It explores trade offs between energy efficiency and system performance, identifies scalability challenges in large-scale deployments, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 32–36 Read article
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Next-Gen Techniques for Bottleneck Detection in High-Performance Computing
Abstract: Modern computing systems face new challenges in bottleneck detection and mitigation due to their increasing complexity which stems from multi-core architectures alongside distributed platforms and real-time processing needs. Traditional methods like hardware profiling and static analysis which used to work well now struggle to keep up with the changing conditions of dynamic system behaviors and diverse computing environments along with variable workload patterns. The current limitations restrict their capability to …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 09–14 Read article
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The Role of IoT in Shaping Smart Cities with Architectural Perspective
Abstract: The integration of IoT in smart cities is revolutionizing the development of cities through interconnected systems that enhance efficiency, sustainability, and quality of life. Real-time data collection,communication, and processing are facilitated by IoT technology through its layered architecture:sensing, network, and application layers. These interlinked ecosystems help solve such serious problems of urbanization as the efficient allocation of resources, smooth flow of traffic, efficient utilization of energy, and the handling of …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 1–10 Read article
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Autonomous Scripting: The Future of AI-Enhanced Shell Programming for DevOps and Security
Abstract: The evolution of operating systems has seen a paradigm shift with the integration of artificial intelligence, quantum computing, and edge computing technologies. Autonomous scripting, driven by AI, is transforming DevOps workflows and security paradigms, enabling self-healing systems, predictive automation, and intelligent threat detection. This study explores the role of AI-enhanced shell programming in the automation landscape, discussing its implications for next-generation operating systems. It further delves into the integration of …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 1, 2025 · pp. 28–39 Read article
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Next-generation Operating Systems: AI-driven Autonomy, Quantum Integration, and Edge Computing
Abstract: The rapid evolution of computing paradigms is driving the need for next-generation operating systems that seamlessly integrate artificial intelligence, quantum computing, and edge processing. Traditional operating systems, while efficient for classical computation, lack the necessary capabilities to handle real-time AI-driven decision-making, quantum processing, and decentralized edge networks. This study explores how future operating systems will incorporate AI-driven autonomy to enhance resource management, quantum integration to leverage superior computational power, and …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 25–36 Read article
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Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article
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Implementing and Analyzing Network Commands in Cloud and Edge Computing Environments with Cisco Simulators
Abstract: The present review examines edge and cloud topologies and compares them according to latency. Instead of using distant data centers like cloud computing platforms, edge computing designs process data physically close to the source. Increased demand for Internet of Things (IoT) devices, which are growing more concerned with real-time data processing and analysis, has fueled the expansion of edge computing and cloud computing. In essence, each of these designs offers …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 62–69 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Edge Computing in IoT: Challenges and Opportunities for Engineers
Abstract: The internet of things (IoT) has revolutionized how we interact with our environment, collect data, and make decisions. However, the exponential growth of IoT devices has led to significant challenges in data processing, latency, and bandwidth usage. Edge computing provides an effective solution to these issues by bringing computation and data storage nearer to the source of data generation. This paper provides a comprehensive exploration of the challenges and opportunities …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 14–19 Read article