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44 articles for “adaptive scheduling”
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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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Real-time Operating Systems in the Era of IoT: Challenges and Solutions for Time-Critical Applications
Abstract: Real-time operating systems (RTOS) are essential in the Internet of Things (IoT), as they ensure timely responses to events, which is critical for the performance and reliability of connected devices. This paper delves into the unique challenges faced by RTOS in IoT environments, highlighting issues such as limited computational resources, strict latency requirements, and the increasing need for robust security mechanisms. The resource constraints inherent in many IoT devices, which …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 13–24 Read article
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An Optimised CPU Scheduling Algorithm with Adaptive Time Quantum Approach
Abstract: CPU scheduling is an essential mechanism implemented by the operating system to determine the execution of multiple processes by the CPU. The primary objective of the scheduling algorithms is to optimize the systems’ performance efficiently. The performance of a CPU scheduling algorithm depends on various factors and can be evaluated on various criteria like average turnaround time, average waiting time, throughput, fairness etc. This paper aims to present an optimal …
Published in Journal of Operating Systems Development & Trends Read article
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A Hybrid Algorithm for Processor Scheduling Using Game Theory Variants
Abstract: This study proposes a novel hybrid algorithm for processor scheduling in modern operating systems, integrating the strengths of traditional scheduling methods with game theory variants. Traditional schedulers often struggle to adapt to dynamic workload changes, leading to suboptimal performance. Our hybrid approach addresses this by treating processes as "players" in a game, where the "payoff" is CPU time. A base scheduler (e.g., Weighted Fair Queuing, Earliest Deadline First) provides a …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 48–56 Read article
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Hybrid Graceful QoS Degradation in Distributed Operating Systems
Abstract: Maintaining Quality of Service (QoS) in distributed operating systems is a critical challenge, especially in dynamic and resource-constrained environments. Traditional QoS mechanisms often fail to adapt effectively to unforeseen failures or load spikes, leading to abrupt service disruptions. This study reviews the concept of hybrid graceful QoS degradation, a paradigm that combines multiple strategies to ensure continuous, albeit potentially reduced, service availability. By intelligently integrating techniques like resource reservation, priority-based …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Smart Agriculture: IoT-Based Automation and Monitoring for Enhanced Farming Efficiency
Abstract: This paper presents the development of an innovative agriculture automation and monitoring system designed to improve farming efficiency through the integration of low-cost sensors and microcontrollers. The system utilizes components such as PIR motion sensors, soil moisture sensors, DHT11 humidity sensors, and a relay motor pump for precise automation of irrigation and environmental monitoring. NodeMCU (ESP8266) acts as the primary controller, facilitating real-time data gathering and decision-making. Results show significant …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Optimization of Supply Chain Management Cost Reduction and Delivery Time Improvement
Abstract: Management of the supply chain is vital for every company's success. Businesses can cut expenses and speed up delivery by effectively regulating the flow of goods and services. In this study, we will explore the various strategies and best practices in supply chain management that can help achieve these objectives. We will delve into the importance of efficient sourcing, inventory management, and logistics to streamline operations and optimize the supply …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 15–21 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
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The Daily Architect: A Personal Guide to Mastering Time and Building Productive Routines
Abstract: In today's fast-paced world, individuals face increasing challenges in managing their time, tasks, and personal responsibilities effectively. The concept of "My Daily Helper" is introduced as an intelligent, user-friendly system designed to streamline daily activities and enhance personal productivity. This research explores the design, functionality, and potential impact of such a digital assistant, emphasizing its role in task organization, time management, and decision support. The study investigates how a daily …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 37–50 Read article
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Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article
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Calendar Application That Manages Events and Appointments
Abstract: This article introduces an innovative approach to enhancing the overall user experience of digital calendars by addressing key challenges related to scheduling and conflict management. The proposed solution leverages the capabilities of Flutter and Firebase technologies to streamline event planning and organization using intelligent, adaptive algorithms. These algorithms are specifically designed to resolve scheduling conflicts efficiently while tailoring the experience to individual user preferences. The system supports smooth operation across …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 6–10 Read article
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Approximation-Aware Computation for Graceful QoS Degradation in Modern Multiprocessor Operating Systems
Abstract: Modern multiprocessor operating systems face unprecedented challenges in maintaining Quality of Service (QoS) guarantees under dynamic workload conditions and resource constraints. Traditional approaches to resource management often result in abrupt service degradation or complete task failure when system resources become scarce. This study presents a comprehensive framework for approximation-aware computation that enables graceful QoS degradation in multiprocessor environments. We explore the integration of approximate computing paradigms with operating system schedulers, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Work–Life Balance Among Professional Nurses – A Mixed Methods Study
Abstract: Background & Objectives: Work–life balance (WLB) is an essential component of nurses’ psychological well-being and professional effectiveness. Nurses in India frequently experience heavy workloads, shift duties, and emotional strain that disrupt personal–professional harmony. This study aimed to assess the level of WLB among professional nurses, determine its association with coping practices, and explore their lived experiences in managing work and personal responsibilities across healthcare settings. Methods: A mixed-methods descriptive design …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 · pp. 21–30 Read article
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Task Scheduling in Cloud Computing using Hippopotamus Optimization Algorithm
Abstract: Cloud computing, which provides remote clients with on-demand services, has emerged as a crucial component of contemporary technology. It is still difficult to schedule tasks effectively in such diverse and dynamic situations. Motivated by the hippopotamus's balanced exploration and exploitation behavior, this research suggests a unique work scheduling method utilizing the hippopotamus optimization algorithm (HOA). In order to maximize resource usage and throughput while minimizing makespan and execution cost, the …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 22–29 Read article
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article