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Periodic Deterministic Sampling and scheduling algorithms for Minimum Age of Information in Time-Slotted Multihop Networks

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IEEE Internet of Things Journal 2025年第9期12卷 12958-12974页

作者： Raj, Nibin Vineeth, B.S. Sharma, Pratik Indian Institute of Space Science and Technology Department of Avionics Thiruvananthapuram695547 India

We consider a time-slotted multihop wireless sensor network used for a remote estimation application. Sensor nodes sample processes of interest and convergecast the sampled data to a sink over the multihop wireless network. The processes are remotely estimated at the sink. For such applications, the Age of Information (AoI) is a relevant performance metric. Motivated by real-world protocols, such as 802.15.4e TSCH, we design novel periodic deterministic sampling and scheduling algorithms for minimizing the average AoI (AAoI) for convergecast in tree network topologies with K-hop interference constraints. We obtain an analytical characterization of the AAoI in terms of the period of the policy as well as hop distances of the source nodes to the sink. For periodic deterministic policies, the AAoI minimization problem is formulated as an integer programming problem which is relaxed to a linear programming problem to obtain numerical lower bounds. Novel analytical lower bounds on the AAoI for periodic deterministic policies in tree networks with K-hop interference constraints are obtained. We simulate and compare the AAoI performance of our periodic deterministic policies and show that they have an AAoI close to the lower bounds for that period. Through simulations, we also show that the AAoI of the proposed policies is smaller compared to other multihop AoI-minimizing policies in prior work, such as Age-Difference and Age-Debt. We also discuss extensions to the case of general functions of the AoI. © 2014 IEEE.

关键词： scheduling algorithms

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Task scheduling algorithms for Optical and SAR Satellite Collaboration in Wildfire Detection 10

Task scheduling Algorithms for Optical and SAR Satellite Col...

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10th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Wen, Zhijiang Wang, Chen Cai, Jingying Liu, Yan Zhang, Shengyu Hu, Haiying Innovation Academy for Microsatellites of Chinese Academy of Sciences China Shanghai Engineering Center for Microsatellites China University of Chinese Academy of Sciences China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

Wildfires are a significant environmental challenge, particularly during wildfire seasons when the frequency of incidents dramatically increases. Continuous monitoring of wildfires is essential for early detection, and remote sensing satellites offer a powerful tool for this purpose. However, as the number of wildfire targets rises during peak seasons, tasking of remote sensing satellite constellations becomes increasingly difficult. This complexity is further compounded by the growing number and type of satellites in modern constellations, each equipped with different payloads, such as optical and synthetic aperture radar (SAR) sensors. The need for coordinated observation between these heterogeneous satellite types poses significant challenges for task scheduling. In this context, developing effective collaborative tasking algorithms for satellite constellations becomes critical. This paper presents a novel approach to satellite collaborative tasking for wildfire detection by introducing a clustering algorithm based on a sliding window and a target window assignment method using a greedy strategy. First, the sliding window clustering algorithm dynamically adjusts the window position to identify the optimal clustering results, factoring in key satellite parameters such as the side-slant angle and field of view. Following this, the target window assignment method, driven by a greedy strategy, allocates observation tasks based on an optimized scoring mechanism. The method also incorporates a conflict detection mechanism to resolve task scheduling conflicts, ensuring the efficient utilization of satellite resources. This approach addresses the complex scheduling problems inherent in coordinating observations among heterogeneous multi-satellite constellations. The proposed algorithms effectively enhance the collaborative observation capabilities of both optical and SAR satellites, providing a robust solution for wildfire monitoring and response. © 2025 SPIE.

关键词： scheduling algorithms

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Energy and Security-Aware Task scheduling in Fog Computing: A Comparative Analysis of scheduling algorithms using IoT 4

Energy and Security-Aware Task Scheduling in Fog Computing: ...

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4th International Conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Sehgal, Nikita Bansal, Savina Bansal, R.K. Department of Electronics & Communication Engineering Maharaja Ranjit Singh Punjab Technical University Punjab Bathinda151001 India GianiZail Singh Campus College of Engineering & Technology Maharaja Ranjit Singh Punjab Technical University Punjab Bathinda151001 India

Efficient task scheduling in fog-cloud computing environments is essential for optimizing critical parameters such as energy efficiency, security, and real-time performance. Existing scheduling algorithms like Pure Random (PR) and Earliest Deadline First Random (EDF_R) often lack in generalization as its focus is primarily on individual aspects such as task deadlines or random task assignments, leading to inefficiencies in load balancing, resource utilization, and security management. The Security Aware scheduling (SAS) algorithm introduces a security-centric approach, prioritizing task assignment based on security requirements, thus ensuring tasks are allocated to nodes that meet or exceed their security needs. The Minimum Energy Security-Aware scheduling (MESA) algorithm addresses the energy constraints by minimizing energy consumption during task scheduling while maintaining security compliance. Furthermore, the Minimum Response Time Security-Aware scheduling (MRSA) algorithm aims to reduce response times by optimizing node selection based on both minimum response time and security requirements. Despite these advancements, there is a need for a more comprehensive solution that simultaneously addresses the challenges of energy efficiency, security, and real-time task execution. This research proposes the Optimal Energy-Security Aware scheduling (OESAS) framework, which integrates these critical factors, providing an adaptive and efficient scheduling solution for heterogeneous fog-cloud systems. © 2025 The Authors. Published by Elsevier B.V.

关键词： scheduling algorithms

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Real-Time scheduling algorithms for Improved Mobile Device Energy Efficiency

Real-Time Scheduling Algorithms for Improved Mobile Device E...

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2025 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2025

作者： Panchani, Ajaykumar Devrajbhai EBay Inc. Selling Department Liberty HillTX United States

ISBN: (纸本)9798331513894

In the era of real-time applications dominating mobile devices, balancing enhanced performance with prolonged battery life has become a significant challenge. This paper explores the complexities of real-time scheduling algorithms, focusing on Earliest Deadline First (EDF) and Rate Monotonic (RM) algorithms, and their impact on energy consumption. Additionally, variations of these algorithms are introduced in the context of Dynamic Voltage Scaling (DVS), a technique crucial for achieving optimal performance with improved battery efficiency. Through an in-depth analysis of various conditions, including task numbers and worst-case processor utilization, the study demonstrates the effectiveness of these algorithms, making them indispensable in scenarios where energy efficiency is paramount. © 2025 IEEE.

关键词： scheduling algorithms

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An Analytical Overview Of Virtual Machine Load Balancing scheduling algorithms with their Comparative Case Study

arXiv

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arXiv 2025年

作者： Vaidya, Priyank Sharma, Abhinav Patel, Murli Doshi, Nishant Department of Computer Science and Engineering Pandit Deendayal Energy University India

This paper contains the analysis of VM load balancing scheduling algorithms discussing its advantages, disadvantages along with applications. As the Industry shifts towards adapting cloud technologies, it is important to optimally load balance the client requests to the servers. It becomes important to the cloud providers to adapt technology so that its customers don’t fall behind of latency issues. The algorithm which is more often used in the load balancers are analytically discussed. The fundamentals regarding virtualisation & VM allocation concepts are also covered. © 2025, CC BY-NC-SA.

关键词： scheduling algorithms

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Real-Time scheduling algorithms for Improved Mobile Device Energy Efficiency

Real-Time Scheduling Algorithms for Improved Mobile Device E...

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International Conference on Computer, Electrical & Communication Engineering (ICCECE)

作者： Ajaykumar Devrajbhai Panchani Selling Department eBay Inc. Liberty Hill Texas USA

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

关键词： Performance evaluation Context scheduling algorithms Heuristic algorithms Real-time systems Energy efficiency Mobile handsets Dynamic voltage scaling Batteries Voltage control

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Job Generator for Evaluating and Comparing scheduling algorithms for Modern GPU Clouds

Job Generator for Evaluating and Comparing Scheduling Algori...

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15th International Conference on Cloud Computing and Services Science, CLOSER 2025

作者： Konopa, Michal Fesl, Jan Beránek, Ladislav Department of Data Science and Computing Systems Faculty of Agriculture and Technology University of South Bohemia České Budějovice Czech Republic

ISBN: (纸本)9789897587474

The steep technological and performance advances in GPU cards have led to their increasing use in data centers in the recent years, especially in machine learning jobs. However, high hardware performance alone does not guarantee (sub) optimal utilization of computing resources, especially when the cost associated with power consumption also needs to be increasingly considered. As consequence of these realities, various job scheduling algorithms have been and are being developed to optimize the power consumption in data centers with respect to defined constraints. Unfortunately, there is still no known, widely used, parametrizable dataset that serves as a de facto standard for simulating scheduling algorithms and the resulting ability to compare their performance against each other. The goal of this paper is to describe a simple job set generator designed to run on modern GPU architectures and to introduce the newly created data set suitable for evaluation the scheduling algorithms. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： scheduling algorithms

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Unifying scheduling algorithms for Group Completion Time

arXiv

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arXiv 2025年

作者： Lindermayr, Alexander Liu, Zhenwei Megow, Nicole University of Bremen Germany Zhejiang University China

We propose new abstract problems that unify a collection of scheduling and graph coloring problems with general min-sum objectives. Specifically, we consider the weighted sum of completion times over groups of entities (jobs, vertices, or edges), which generalizes two important objectives in scheduling: makespan and sum of weighted completion times. We study these problems in both online and offline settings. In the non-clairvoyant online setting, we give a novel O(log g)-competitive algorithm, where g is the size of the largest group. This is the first non-trivial competitive bound for many problems with group completion time objective, and it is an exponential improvement over previous results for non-clairvoyant coflow scheduling. Notably, this bound is asymptotically best-possible. For offline scheduling, we provide powerful meta-frameworks that lead to new or stronger approximation algorithms for our new abstract problems and for previously well-studied special cases. In particular, we improve the approximation ratio from 13.5 to 10.874 for non-preemptive related machine scheduling and from 4 + Ε to 2 + Ε for preemptive unrelated machine scheduling (MOR 2012), and we improve the approximation ratio for sum coloring problems from 10.874 to 5.437 for perfect graphs and from 11.273 to 10.874 for interval graphs (TALG 2008). © 2025, CC BY.

关键词： scheduling algorithms

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scheduling algorithms for 5G Networks and Beyond: Classification and Survey

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IEEE ACCESS 2022年 10卷 51643-51661页

作者： Mamane, Asmae Fattah, Mohammed El Ghazi, Mohammed El Bekkali, Moulhime Balboul, Younes Mazer, Said Sidi Mohammed Ben Abdellah Univ Lab Artificial Intelligence Data Sci & Emerging S Fes 30000 Morocco Moulay Ismail Univ IMAGE Lab Meknes 50050 Morocco

Over the years, several research groups have been developing effective and efficient scheduling algorithms to enhance the quality of service of mobile communication networks. The arrival of the fifth generation of mobile networks (5G) has demonstrated the importance of advanced scheduling techniques to manage the limited frequency spectrum available while achieving 5G transmission requirements. This issue has been picked up extensively within the research community due to the increasing demand for mobile communications and the desire for a fully connected world. Consequently, the scientific community has developed novel approaches and varied scheduling schemes to meet the needs of various applications and scenario conditions. In this context, this paper presents an overview of the state-of-the-art methods, highlights seminal and innovative research, and investigates the current state of 5G radio resource management. This review of literature compares emerging strategy methods based on their metrics, analyzes their performances, and emphasizes the existing works with a vision for the future of modern 5G and upcoming networks in terms of radio resource allocation to provide a thorough introspection of the literature. Furthermore, gaining a better understanding of the radio resource management state-of-the-art would provide valuable information for future work and might be helpful for new researchers in the field.

关键词： 5G mobile communication Resource management scheduling algorithms Quality of service Measurement Long Term Evolution Ultra reliable low latency communication 5G beyond 5G scheduling algorithms resource allocation radio resource management spectral efficiency scheduling schemes

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scheduling algorithms AND OPERATING-SYSTEMS SUPPORT FOR REAL-TIME SYSTEMS

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PROCEEDINGS OF THE IEEE 1994年第1期82卷 55-67页

作者： RAMAMRITHAM, K STANKOVIC, JA Dept. of Comput. Sci. Massachusetts Univ. Amherst MA

This paper summarizes the state of the real-time field in the areas of scheduling and operating system kernels. Given the vast amount of work that has been done by both the operations research and computer science communities in the scheduling al ea, we discuss four paradigms underlying the scheduling approaches and present several exemplars of each. The Soul paradigms are: static table-driven scheduling, static priority preemptive scheduling, dynamic planning-based scheduling, and dynamic best effort scheduling. In the operating system context, we argue that most of the proprietary commercial kernels as well as real-time extensions to time-sharing operating system kernels do not fit the needs of predictable real-time systems. We discuss several research kernels that al e currently being built to explicitly meet the needs of real-time applications.

关键词： computer science dynamic best effort scheduling dynamic planning-based scheduling operating systems operating systems (computers) operations research real-time systems real-time systems scheduling scheduling algorithms static priority preemptive scheduling static table-driven scheduling time-sharing programs

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