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Journal articles on the topic 'Adaptive resource management'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Pavan, A., R. Jha, L. Graba, et al. "Real-time adaptive resource management." Computer 34, no. 7 (2001): 99–101. http://dx.doi.org/10.1109/2.933517.

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2

Bharghavan, V., Kang-Won Lee, Songwu Lu, Sungwon Ha, Jin-Ru Li, and D. Dwyer. "The TIMELY adaptive resource management architecture." IEEE Personal Communications 5, no. 4 (1998): 20–31. http://dx.doi.org/10.1109/98.709366.

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3

Iftekhar, Md Sayed, and David J. Pannell. "“Biases” in Adaptive Natural Resource Management." Conservation Letters 8, no. 6 (2015): 388–96. http://dx.doi.org/10.1111/conl.12189.

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4

Salazar, Jos ́e, Ismael Gómez, and Antoni Gelonch. "Adaptive Resource Management and Flexible Radios for WiMAX." Journal of Telecommunications and Information Technology, no. 4 (June 26, 2023): 101–7. http://dx.doi.org/10.26636/jtit.2009.4.996.

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The availability of dynamic resource management will be crucial for the deployment of future wireless systems characterized by high data rate services with rigid quality of service demands. Flexible radios appear as the technological answer required to achieve constraint goals under different channel conditions and transmission scenarios. This paper is focused on enhancing another step of flexibility within the resource management by including an efficient handling of computing resources. This concept towards flexible architectures represents a key word for a real successful implementation due

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5

Kirk, Nicholas. "Constraints on the Use of Adaptive Management in New Zealand’s Resource Management." Case Studies in the Environment 3, no. 1 (2019): 1–5. http://dx.doi.org/10.1525/cse.2019.002246.

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This paper examines the development of adaptive management in New Zealand’s resource management case law. In particular, this paper investigates a Supreme Court decision (Sustain Our Sounds Inc v King Salmon New Zealand Co Ltd), which established a set of criteria for implementing adaptive management through New Zealand’s Resource Management Act. This paper describes King Salmon’s initial request for aquaculture permits, the Supreme Court appeal, and the Supreme Court’s justification for an adaptive management approach. Analyzing this justification, this paper explores the remaining constraint

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6

Yan, He Hua, Jia Fu Wan, and Hui Suo. "Adaptive Resource Management for Cyber-Physical Systems." Applied Mechanics and Materials 157-158 (February 2012): 747–51. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.747.

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Cyber-physical systems (CPSs) perfectly integrate computing with physical processes, and the emergence of CPSs has attracted significant interest in recent years. In order to fully utilize system resource and improve quality of service (QoS), the innovative resource management method for CPSs is essential. According to a representative case of CPSs (e. g., unmanned vehicle with wireless sensor network navigation), we propose a hierarchical architecture for CPSs, and further establish a system performance optimization model with resource constraints. The particle swarm optimization (PSO) algori

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7

Duran-Limon, H. A., G. S. Blair, and G. Coulson. "Adaptive resource management in middleware: a survey." IEEE Distributed Systems Online 5, no. 7 (2004): 1–13. http://dx.doi.org/10.1109/mdso.2004.11.

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8

Maurer, Michael, Ivona Brandic, and Rizos Sakellariou. "Adaptive resource configuration for Cloud infrastructure management." Future Generation Computer Systems 29, no. 2 (2013): 472–87. http://dx.doi.org/10.1016/j.future.2012.07.004.

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9

Tiwari, Shrish, Ramakrishna Ramaswamy, and J. Subba Rao. "Adaptive control in a resource management model." Ecological Modelling 84, no. 1-3 (1996): 53–62. http://dx.doi.org/10.1016/0304-3800(94)00143-x.

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10

Dimitrakopoulos, George, Klaus Moessner, Clemens Kloeck, et al. "Adaptive Resource Management Platform for Reconfigurable Networks." Mobile Networks and Applications 11, no. 6 (2006): 799–811. http://dx.doi.org/10.1007/s11036-006-0050-5.

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11

Halstead, Brian J., Glenn D. Wylie, Peter S. Coates, and Michael L. Casazza. "Bayesian adaptive survey protocols for resource management." Journal of Wildlife Management 75, no. 2 (2011): 450–57. http://dx.doi.org/10.1002/jwmg.55.

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12

Divsalar, Ahmad, Seyyed Jafar Mousavi, and Farshad Emami. "Exploring Adaptive Management Techniques in Coastal Resource Conservation." Journal of Resource Management and Decision Engineering 3, no. 1 (2024): 11–18. http://dx.doi.org/10.61838/kman.jrmde.3.1.3.

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This study explores the adaptive management techniques employed in coastal resource conservation, aiming to understand how different stakeholders integrate dynamic management practices to address these challenges effectively. This qualitative study involved semi-structured interviews with 27 stakeholders, including local community leaders, conservation experts, policymakers, and representatives from non-governmental organizations (NGOs). The participants were selected through purposive sampling to cover a broad range of experiences and insights. The interviews focused on their perspectives and

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13

Temnova, Natalia K., and Elena K. Markova. "PROSPECTS FOR THE USE OF ADAPTIVE HUMAN RESOURCE MANAGEMENT TECHNOLOGY IN HIGHER EDUCATION." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 10/2, no. 139 (2023): 154–60. http://dx.doi.org/10.36871/ek.up.p.r.2023.10.02.019.

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In this scientific work, the description and prospects of the application of adaptive human resource management technology in the higher education system are carried out. The authors analyze such adaptive methods as adaptive recruitment management, adaptive assessment methods, adaptive development, adaptive performance management, adaptive incentive system, adaptive organizational culture, adaptive motivation mechanisms, adaptive career management, adaptive conflict management. The integration of all these technologies into a single whole will allow a comprehensive approach to prospective huma

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14

Arjunan, Prabu. "A Framework for Resource-Efficient Large Language Model Fine-tuning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–8. https://doi.org/10.55041/ijsrem25112.

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This paper proposes a systematic framework for the fine-tuning process of Large Language Models. The proposed method addresses the computational challenges that naturally arise in LLM fine-tuning by incorporating a comprehensive architecture that effectively integrates intelligent resource management along with adaptive training strategies. Our framework introduces dynamic resource allocation mechanisms along with efficient data processing pipelines, thereby making LLM fine-tuning more accessible to organizations with limited computational resources. The methodology outlined focuses on model q

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15

Sadikin, Abdurrahman, Hefri Yodiansyah, Yanti Budiasih, Sugiarti Sugiarti, and Iwan Henri Kusnadi. "ADAPTIVE HUMAN RESOURCE MANAGEMENT IN CONFRONTATION OF GLOBALIZATION'S CHALLENGES." Jurnal Ekonomi 12, no. 02 (2023): 1761–67. http://dx.doi.org/10.54209/ekonomi.v12i02.2096.

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Globalization has created a dynamic and complex business environment, requiring organizations to adjust to unpredictable and rapid change. In this context, adaptive HR management is essential for sustaining the success and competitiveness of the organization. The method of research employed is a literature review, which entails gathering and analyzing literature on adaptive HR management and the challenges of globalization. The research findings indicate that adaptive human resource management necessitates the use of change-responsive strategies and practices, such as in recruitment, employee

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16

Zhou, Xinhuan. "Adaptive Financial Management and Teachers' Assessments of Resource Availability." World Journal of Educational Research 11, no. 5 (2024): p24. http://dx.doi.org/10.22158/wjer.v11n5p24.

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Adaptive financial management and teacher evaluation of resource availability are of vital significance in the sustainable development of educational institutions. Adaptive financial management is closely related to teachers’ evaluation of resources availability. In the education system, the adaptability of financial management directly determines the scale and type of resources that can be allocated to teachers. Effective financial management can accurately identify the resources needed for teacher evaluation. The lack of adaptability of financial management may lead to the shortage of teache

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17

Lin, Kai, Haohua Wang, Bingcai Chen, and Giancarlo Fortino. "Hypergraph-Based Autonomous Networks: Adaptive Resource Management and Dynamic Resource Scheduling." IEEE Communications Standards Magazine 6, no. 3 (2022): 16–22. http://dx.doi.org/10.1109/mcomstd.0001.2100109.

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18

Jin, Ying. "A Self-Adaptive Recommendation Method for Online Ideological and Political Teaching Resources Based on Deep Reinforcement Learning." Mobile Information Systems 2022 (August 29, 2022): 1–11. http://dx.doi.org/10.1155/2022/1702657.

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The online ideological as well as the political teaching resource management system structure is established in the view of information management in colleges and universities. Furthermore, the online ideological as well as the political teaching information level is improved by combining the optimized design of resource recommendation model. In this paper, an online ideological as well as political teaching resource adaptive recommendation system and algorithm, which is designed on deep reinforcement learning, is suggested. The cost relationship model between online ideological as well as the

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19

WEN, Yu, Dan MENG, and Jiang-Feng ZHAN. "Adaptive Virtualized Resource Management for Application’s SLO Guarantees." Journal of Software 24, no. 2 (2013): 358–77. http://dx.doi.org/10.3724/sp.j.1001.2013.04216.

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20

Lee, Kisong, and Howon Lee. "ARM: Adaptive Resource Management for Wireless Network Reliability." Journal of the Korea Institute of Information and Communication Engineering 18, no. 10 (2014): 2382–88. http://dx.doi.org/10.6109/jkiice.2014.18.10.2382.

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21

Harada, Fumiko, Toshimitsu Ushio, and Yukikazu Nakamoto. "Adaptive Resource Allocation Control for Fair QoS Management." IEEE Transactions on Computers 56, no. 3 (2007): 344–57. http://dx.doi.org/10.1109/tc.2007.39.

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22

Jeong, Young-Sik, Hyun-Woo Kim, and Haeng Jin Jang. "Adaptive resource management scheme for monitoring of CPS." Journal of Supercomputing 66, no. 1 (2013): 57–69. http://dx.doi.org/10.1007/s11227-013-0970-3.

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23

Li Lin and Jinpeng Huai. "QGrid: An Adaptive Trust Aware Resource Management Framework." IEEE Systems Journal 3, no. 1 (2009): 78–90. http://dx.doi.org/10.1109/jsyst.2008.2011312.

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24

Yuan, Xiaoqun, Geyong Min, Yi Ding, et al. "Adaptive resource management for P2P live streaming systems." Future Generation Computer Systems 29, no. 6 (2013): 1573–82. http://dx.doi.org/10.1016/j.future.2012.09.002.

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25

Wintenby, J., and V. Krishnamurthy. "Hierarchical resource management in adaptive airborne surveillance radars." IEEE Transactions on Aerospace and Electronic Systems 42, no. 2 (2006): 401–20. http://dx.doi.org/10.1109/taes.2006.1642560.

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26

Segovia, Vanessa R., Mikael Kralmark, Mikael Lindberg, and Karl-Erik Årzén. "Processor Thermal Control Using Adaptive Bandwidth Resource Management." IFAC Proceedings Volumes 44, no. 1 (2011): 1952–58. http://dx.doi.org/10.3182/20110828-6-it-1002.03275.

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27

Armitage, Derek. "Adaptive Capacity and Community-Based Natural Resource Management." Environmental Management 35, no. 6 (2005): 703–15. http://dx.doi.org/10.1007/s00267-004-0076-z.

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28

Huang, Chenn-Jung, Chih-Tai Guan, Heng-Ming Chen, et al. "An adaptive resource management scheme in cloud computing." Engineering Applications of Artificial Intelligence 26, no. 1 (2013): 382–89. http://dx.doi.org/10.1016/j.engappai.2012.10.004.

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29

Williams, Byron K., Mitchell J. Eaton, and David R. Breininger. "Adaptive resource management and the value of information." Ecological Modelling 222, no. 18 (2011): 3429–36. http://dx.doi.org/10.1016/j.ecolmodel.2011.07.003.

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30

Shamsitdinov, Salohiddin. "ADAPTIVE METHODS OF MANAGEMENT OF THE INTEGRATED LABOR MARKET." Technical Sciences 4, no. 1 (2021): 18–23. http://dx.doi.org/10.26739/2181-9696-2021-1-3.

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This article examines the methodology of information interaction with an integrated labor market, aswell as effective methods of labor management and ways to create mechanisms for coordinated management of labor market resources and the processes of training specialists. The specifics will determine how people will react to the changes and new opportunities that global trends bring with them. Trends determine how the labor market model will look in the future.Key words:adaptive management, labor market, regulation tools, rating, unemployment, labor, efficiency, adaptation, management, resource

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31

Lindkvist, Emilie, Örjan Ekeberg, and Jon Norberg. "Strategies for sustainable management of renewable resources during environmental change." Proceedings of the Royal Society B: Biological Sciences 284, no. 1850 (2017): 20162762. http://dx.doi.org/10.1098/rspb.2016.2762.

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As a consequence of global environmental change, management strategies that can deal with unexpected change in resource dynamics are becoming increasingly important. In this paper we undertake a novel approach to studying resource growth problems using a computational form of adaptive management to find optimal strategies for prevalent natural resource management dilemmas. We scrutinize adaptive management, or learning-by-doing, to better understand how to simultaneously manage and learn about a system when its dynamics are unknown. We study important trade-offs in decision-making with respect

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32

Armitage, Derek R. "Traditional agroecological knowledge, adaptive management and the socio-politics of conservation in Central Sulawesi, Indonesia." Environmental Conservation 30, no. 1 (2003): 79–90. http://dx.doi.org/10.1017/s0376892903000079.

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This paper illustrates the opportunity for conservation offered by linking traditional agroecological knowledge and advances in adaptive management theory and practice. Drawing on examples from the Banawa-Marawola region of Central Sulawesi, Indonesia, a suite of traditional resource management practices premised on principles of adaptive management are identified and assessed, including: (1) resource management practices and regulations that are associated with the dynamics of complex systems; (2) procedural, planning and decision-making processes that foster learning; (3) sanctions and taboo

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33

Hagmann, Jürgen, and Edward Chuma. "Enhancing the adaptive capacity of the resource users in natural resource management." Agricultural Systems 73, no. 1 (2002): 23–39. http://dx.doi.org/10.1016/s0308-521x(01)00098-1.

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34

Zhang, Mei. "Design of Multichannel Resource Adaptive Scheduling Algorithm for English Online Translation Teaching." Wireless Communications and Mobile Computing 2022 (March 29, 2022): 1–11. http://dx.doi.org/10.1155/2022/7257151.

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In order to optimize the multichannel resource scheduling of English online translation teaching and realize the goal of adaptive scheduling algorithm, a multichannel resource adaptive scheduling algorithm for English online translation teaching is designed. The clustering algorithm is used to sort out various English online translation teaching multichannel resources and remove redundancy. Build a unified standard specification; establish an English online translation teaching resource scheduling model with three modules of foundation layer, environment layer, and application layer; form an e

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35

London, Manuel. "Team Learning and the Human Resource Development/Human Resource Management Interface." Human Resource Development Review 21, no. 1 (2021): 15–23. http://dx.doi.org/10.1177/15344843211062677.

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This editorial reviews my work on team learning published in HRDR, celebrating the 20th anniversary of the journal. The articles conceptualized the value and need for member expansiveness; team’s and individual members’ readiness to change; and the effects of environmental pressures for adaptive, generative, and transformative team learning. I conclude this review with directions for future research and practice in HRD and HRM to support changing conditions, collective self-awareness, and variations in team interactions using advancing technologies.

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36

Lannan, James E., Graham A. E. Gall, John E. Thorpe, Colin E. Nash, and Brenda E. Ballachey. "Genetic resource management of fish." Genome 31, no. 2 (1989): 798–804. http://dx.doi.org/10.1139/g89-141.

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The diverse global ichthyofauna represents a wealth of genetic resources for adaptive evolution, for the development and harvest of present and future sources of human foods, and for germ plasm for aquaculture. Fish make an important contribution to human nutrition worldwide and the demand for fisheries products is increasing. Several production systems are employed in producing and harvesting fisheries products, including capture fisheries, aquaculture, and culture-based fisheries. There are risks of losing genetic variation inherent in each production system. However, genetic considerations

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37

Nataliia, Dotsenko. "METHODOLOGICAL PROVISION OF HUMAN RESOURCES MANAGEMENT IN A MULTI-PROJECT ENVIRONMENT." Technology audit and production reserves 1, no. 2 (45) (2019): 52–54. https://doi.org/10.15587/2312-8372.2019.160382.

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<em>The object of research is the processes of human resource management of projects in a multi-project environment. The studies are based on the use of a combinatorial-logical approach to the construction of formal models for the formation and functioning of project teams in a multi-project environment, a stakeholder-oriented approach to the formation of resource requirements, and a donor-acceptor approach to the distribution of resources between projects. The main hypothesis of research is the assumption that the effectiveness of project management depends on the effectiveness of human resou

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38

Tuncer, Daphne, Marinos Charalambides, Stuart Clayman, and George Pavlou. "Adaptive Resource Management and Control in Software Defined Networks." IEEE Transactions on Network and Service Management 12, no. 1 (2015): 18–33. http://dx.doi.org/10.1109/tnsm.2015.2402752.

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39

Charlish, Alexander, Folker Hoffmann, Christoph Degen, and Isabel Schlangen. "The Development From Adaptive to Cognitive Radar Resource Management." IEEE Aerospace and Electronic Systems Magazine 35, no. 6 (2020): 8–19. http://dx.doi.org/10.1109/maes.2019.2957847.

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40

Lu, Songwu, and Vaduvur Bharghavan. "Adaptive resource management algorithms for indoor mobile computing environments." ACM SIGCOMM Computer Communication Review 26, no. 4 (1996): 231–42. http://dx.doi.org/10.1145/248157.248177.

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41

Cordeschi, Nicola, Danilo Amendola, and Enzo Baccarelli. "Reliable Adaptive Resource Management for Cognitive Cloud Vehicular Networks." IEEE Transactions on Vehicular Technology 64, no. 6 (2015): 2528–37. http://dx.doi.org/10.1109/tvt.2014.2345767.

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42

Ahmad, Mushtaq, Muhammad Naeem, Ashfaq Ahmed, Muhammad Iqbal, and Alagan Anpalagan. "Mesh adaptive direct search approach for D2D resource management." Wireless Communications and Mobile Computing 16, no. 15 (2016): 2329–39. http://dx.doi.org/10.1002/wcm.2686.

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43

Li, Yan, Feng-Hong Chen, Xi Sun, et al. "Self-Adaptive Resource Management for Large-Scale Shared Clusters." Journal of Computer Science and Technology 25, no. 5 (2010): 945–57. http://dx.doi.org/10.1007/s11390-010-9379-0.

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44

Comden, Joshua, Jing Wang, and Andrey Bernstein. "Adaptive primal–dual control for distributed energy resource management." Applied Energy 351 (December 2023): 121883. http://dx.doi.org/10.1016/j.apenergy.2023.121883.

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45

Bayu, Teguh Indra, Yung-Fa Huang, and Jeang-Kuo Chen. "Reinforcement Learning Approach for Adaptive C-V2X Resource Management." Future Internet 15, no. 10 (2023): 339. http://dx.doi.org/10.3390/fi15100339.

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The modulation coding scheme (MCS) index is the essential configuration parameter in cellular vehicle-to-everything (C-V2X) communication. As referenced by the 3rd Generation Partnership Project (3GPP), the MCS index will dictate the transport block size (TBS) index, which will affect the size of transport blocks and the number of physical resource blocks. These numbers are crucial in the C-V2X resource management since it is also bound to the transmission power used in the system. To the authors’ knowledge, this particular area of research has not been previously investigated. Ultimately, thi

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46

Huh, Eui-Nam, and Lonnie R. Welch. "Adaptive resource management for dynamic distributed real-time applications." Journal of Supercomputing 38, no. 2 (2006): 127–42. http://dx.doi.org/10.1007/s11227-006-7554-4.

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47

Delaney, James, Steve Dowey, and Chi-Tsun Cheng. "Reinforcement-Learning-Based Robust Resource Management for Multi-Radio Systems." Sensors 23, no. 10 (2023): 4821. http://dx.doi.org/10.3390/s23104821.

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The advent of the Internet of Things (IoT) has triggered an increased demand for sensing devices with multiple integrated wireless transceivers. These platforms often support the advantageous use of multiple radio technologies to exploit their differing characteristics. Intelligent radio selection techniques allow these systems to become highly adaptive, ensuring more robust and reliable communications under dynamic channel conditions. In this paper, we focus on the wireless links between devices equipped by deployed operating personnel and intermediary access-point infrastructure. We use mult

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48

Prabakaran, M., and M. Parthiban. "Adaptive Workload Management for Efficient Energy Utilization on Cloud." COMPUSOFT: An International Journal of Advanced Computer Technology 03, no. 03 (2014): 604–8. https://doi.org/10.5281/zenodo.14682151.

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Cloud infrastructures must accommodate changing demands for different types of processing with workloads and time constraints. Dynamic consolidation of Virtual Machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in Cloud data centers. To find when it is best to rearrange VMs from an overloaded host is an aspect of dynamic VM consolidation that directly influences the resource utilization and Quality of Service (QOS) delivered by the system. 

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49

Narne, Harish. "Optimized Resource Management in Cloud Computing: A Unified Approach with Adaptive Allocation and Predictive Scaling." International Journal of Science and Research (IJSR) 11, no. 12 (2022): 1399–403. http://dx.doi.org/10.21275/sr221210105705.

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50

Owens, Philip N. "Adaptive management frameworks for natural resource management at the landscape scale: implications and applications for sediment resources." Journal of Soils and Sediments 9, no. 6 (2009): 578–93. http://dx.doi.org/10.1007/s11368-009-0137-2.

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