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Relevant bibliographies by topics / Adaptive resource allocation

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Academic literature on the topic 'Adaptive resource allocation'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Adaptive resource allocation"

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Pourebrahimi, Behnaz, and Koen Bertels. "Self-Adaptive Economic-Based Resource Allocation in Ad-Hoc Grids." International Journal of Embedded and Real-Time Communication Systems 3, no. 2 (2012): 111–30. http://dx.doi.org/10.4018/jertcs.2012040106.

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Resource allocation is the process of discovering and allocating resources to requested tasks in a way that satisfy both user jobs and resource administrators. In ad-hoc Grids, resource allocation is a challenging undertaking as tasks and resources are distributed, heterogeneous in nature, owned by different individuals or organizations and they may arise spontaneously at any time with various requirements and availabilities. In this paper, the authors address an economic-based framework for resource allocation in ad-hoc Grids to deal with the dynamic nature of such networks. Within the econom

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Busemeyer, Jerome R., Kenneth N. Swenson, and Alejandro Lazarte. "An adaptive approach to resource allocation." Organizational Behavior and Human Decision Processes 38, no. 3 (1986): 318–41. http://dx.doi.org/10.1016/0749-5978(86)90004-x.

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Stephens, Kenneth R., William R. Hutchison, Sharon S. Hormby, and Thomas M. Bell. "Dynamic resource allocation using adaptive networks." Neurocomputing 2, no. 1 (1990): 9–16. http://dx.doi.org/10.1016/0925-2312(90)90012-g.

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Avgeris, Marios, Dimitrios Dechouniotis, Nikolaos Athanasopoulos, and Symeon Papavassiliou. "Adaptive Resource Allocation for Computation Offloading." ACM Transactions on Internet Technology 19, no. 2 (2019): 1–20. http://dx.doi.org/10.1145/3284553.

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Huang, Binbin, Zhongjin Li, Yunqiu Xu, et al. "Deep Reinforcement Learning for Performance-Aware Adaptive Resource Allocation in Mobile Edge Computing." Wireless Communications and Mobile Computing 2020 (July 2, 2020): 1–17. http://dx.doi.org/10.1155/2020/2765491.

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Mobile edge computing (MEC) enables to provide relatively rich computing resources in close proximity to mobile users, which enables resource-limited mobile devices to offload workloads to nearby edge servers, and thereby greatly reducing the processing delay of various mobile applications and the energy consumption of mobile devices. Despite its advantages, when a large number of mobile users simultaneously offloads their computation tasks to an edge server, due to the limited computation and communication resources of edge server, inefficiency resource allocation will not make full use of th

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Petrovska, Inna, and Heorhii Kuchuk. "ADAPTIVE RESOURCE ALLOCATION METHOD FOR DATA PROCESSING AND SECURITY IN CLOUD ENVIRONMENT." Advanced Information Systems 7, no. 3 (2023): 67–73. http://dx.doi.org/10.20998/2522-9052.2023.3.10.

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Subject of research: methods of resource allocation of the cloud environment. The purpose of the research: to develop a method of resource allocation that will improve the security of the cloud environment. At the same time, effective data processing should be achieved. Method characteristics. The article discusses the method of adaptive resource allocation in cloud environments, focusing on its significance for data processing and enhanced security. A notable feature of the method is the consideration of external influences when calculating the characteristics of cloud resource requests and p

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ZHANG, Wei, Li RUAN, Mingfa ZHU, et al. "SLA_Driven Adaptive Resource Allocation for Virtualized Servers." IEICE Transactions on Information and Systems E95.D, no. 12 (2012): 2833–43. http://dx.doi.org/10.1587/transinf.e95.d.2833.

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Edmondson, James, and Douglas Schmidt. "Multi-agent distributed adaptive resource allocation (MADARA)." International Journal of Communication Networks and Distributed Systems 5, no. 3 (2010): 229. http://dx.doi.org/10.1504/ijcnds.2010.034946.

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Ramírez-Velarde, Raul, Andrei Tchernykh, Carlos Barba-Jimenez, Adán Hirales-Carbajal, and Juan Nolazco-Flores. "Adaptive Resource Allocation with Job Runtime Uncertainty." Journal of Grid Computing 15, no. 4 (2017): 415–34. http://dx.doi.org/10.1007/s10723-017-9410-6.

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Han, Bohyung, Seong-Wook Joo, and Larry S. Davis. "Multi-Camera Tracking with Adaptive Resource Allocation." International Journal of Computer Vision 91, no. 1 (2010): 45–58. http://dx.doi.org/10.1007/s11263-010-0373-3.

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Dissertations / Theses on the topic "Adaptive resource allocation"

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Ivan-Roşu, Daniela. "Dynamic resource allocation for adaptive real-time applications." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/9200.

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Tabatabaei, Yazdi Ehsan. "Adaptive Resource Allocation for Wireless Body Sensor Networks." Thesis, University of Canterbury. Computer Science and Software Engineering, 2014. http://hdl.handle.net/10092/9828.

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The IEEE 802.15.4 standard is an interesting technology for use in Wireless Body Sensor Networks (WBSN), where entire networks of sensors are carried by humans. In many environments the sensor nodes experience external interference for example, when the WBSN is operated in the 2.4 GHz ISM band and the human moves in a densely populated city, it will likely experience WiFi interference, with a quickly changing ``interference landscape''. In this thesis we propose Adaptive Resource Allocation schemes, to be carried out by the WBSN, which provided noticeable performance gains in such environments

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Dutta, Partha Sarathi. "Adaptive distributed resource allocation using cooperative information-sharing." Thesis, University of Southampton, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420239.

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Cardieri, Paulo. "Resource Allocation and Adaptive Antennas in Cellular Communications." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/29051.

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The rapid growth in demand for cellular mobile communications and emerging fixed wireless access has created the need to increase system capacity through more efficient utilization of the frequency spectrum, and the need for better grade of service. In cellular systems, capacity improvement can be achieved by reducing co-channel interference. Several techniques have been proposed in literature for mitigating co-channel interference, such as adaptive antennas and power control. Also, by allocating transmitter power and communication channels efficiently (resource allocation), overall co-chann

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sapkota, saroj. "EFFICIENT RESOURCE MANAGEMENT ON EMBEDDED DEVICES VIA ISOLATION AND ADAPTIVE RESOURCE ALLOCATION." OpenSIUC, 2021. https://opensiuc.lib.siu.edu/theses/2831.

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The advent of Chip Multiprocessor (CMP) with high performance, compact size and power efficiency has made many engineering marvel possible. CMPs has played great role in industrial automation, autonomous vehicle, embedded AI, and medical prognosis. In industrial autonomy or in autonomous vehicle there are many critical task which has to be run in isolation without any interference and delay. Virtualization software (Hypervisors) are being used for application isolation in CMPs. Hypervisors such as XEN, KVM are fully fledged hypervisor with many features and have their own scheduling scheme thu

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Shan, Lin. "Adaptive Radio Resource Allocation and Scheduling for Wireless Networks." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/158064.

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Khan, Aimal [Verfasser]. "Resource Allocation in Adaptive Parallel Relay Networks / Aimal Khan." Aachen : Shaker, 2013. http://d-nb.info/1048458032/34.

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Liu, Xiaoyan. "Adaptive resource allocation with packet retransmissions in OFDMA systems." Thesis, University of Kent, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.587567.

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In orthogonal frequency division multiple access (OFDMA) systems, the delay of packets has a great impact on quality of service (QoS), especially for real-time transmission. The basic concept of resource allocation in an OFDMA system is to allocate a subcarrier to the user with the best channel condition in that sub carrier. However, when a retransmission technique is used, the packet delay of successfully transmitting failed packets may be quite large in conventional retransmission schemes. In this paper, the packet combining technique in the downlink OFDMA system is introduced in conjunction

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Wu, Shaopeng. "Adaptive Bandwidth Resource Allocation in Mobile Ad Hoc Networks." Thesis, University of Newcastle Upon Tyne, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506533.

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Rojas, Cordova Alba Claudia. "Resource Allocation Decision-Making in Sequential Adaptive Clinical Trials." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/86348.

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Adaptive clinical trials for new drugs or treatment options promise substantial benefits to both the pharmaceutical industry and the patients, but complicate resource allocation decisions. In this dissertation, we focus on sequential adaptive clinical trials with binary response, which allow for early termination of drug testing for benefit or futility at interim analysis points. The option to stop the trial early enables the trial sponsor to mitigate investment risks on ineffective drugs, and to shorten the development time line of effective drugs, hence reducing expenditures and expediting p

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Books on the topic "Adaptive resource allocation"

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1971-, Chen Huan, ed. Radio resource management for multimedia QoS support in wireless networks. Kluwer Academic Publishers, 2004.

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Post, Eric. Time in Ecology. Princeton University Press, 2019. http://dx.doi.org/10.23943/princeton/9780691182353.001.0001.

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Ecologists traditionally regard time as part of the background against which ecological interactions play out. This book argues that time should be treated as a resource used by organisms for growth, maintenance, and offspring production. The book uses insights from phenology—the study of the timing of life-cycle events—to present a theoretical framework of time in ecology that casts long-standing observations in the field in an entirely new light. Combining conceptual models with field data, the book demonstrates how phenological advances, delays, and stasis, documented in an array of taxa, c

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Book chapters on the topic "Adaptive resource allocation"

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Anithakumari, S., and K. Chandrasekaran. "Adaptive Resource Allocation in Interoperable Cloud Services." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0344-9_19.

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Lim, Hock Beng, Di Ma, Cheng Fu, Bang Wang, and Meng Joo Er. "Adaptive Distributed Resource Allocation for Sensor Networks." In Computer Communications and Networks. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-218-4_14.

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Khdhir, Radhia, Kais Mnif, Aymen Belghith, and Lotfi Kamoun. "New Adaptive Resource Allocation Scheme in LTE-Advanced." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53480-0_74.

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Zhu, Ruiyi, Jian Yang, and Peng Si. "Adaptive Resource Allocation in LTE Downlink Transmission Systems." In Lecture Notes in Electrical Engineering. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1409-3_1.

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Mazumdar, Somnath, Alberto Scionti, and Anoop S. Kumar. "Adaptive Resource Allocation for Load Balancing in Cloud." In Computer Communications and Networks. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54645-2_12.

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Xian, Yue, Hao Yang, Yuwei Zhai, Kean Shi, and Wenzhuo Ma. "Adaptive Resource Allocation Algorithm for Multiuser OFDM System." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25128-4_81.

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Malek-Akhlagh, Mojtaba, and Jens H. Weber. "An Adaptive Resource Allocation Protocol for Dynamic Environments." In Complex, Intelligent and Software Intensive Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08812-4_21.

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She, Yingni, and Ho-fung Leung. "An Adaptive Strategy for Resource Allocation with Changing Capacities." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02469-6_21.

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Lim, Hock Beng, Vinh The Lam, Mao Ching Foo, and Yulian Zeng. "An Adaptive Distributed Resource Allocation Scheme for Sensor Networks." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11943952_65.

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Szeto, K. Y., and S. Y. Zhao. "Adaptive Spatial Allocation of Resource for Parallel Genetic Algorithm." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78987-1_35.

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Conference papers on the topic "Adaptive resource allocation"

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Baresi, Luciano, Marco Garlini, and Giovanni Quattrocchi. "Dynamic Resource Allocation for Deadline-Constrained Neural Network Training." In 2025 IEEE/ACM 20th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). IEEE, 2025. https://doi.org/10.1109/seams66627.2025.00013.

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Makarevitch, Boris. "Adaptive Resource Allocation for WiMAX." In 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2007. http://dx.doi.org/10.1109/pimrc.2007.4394449.

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Brown, Timothy X., and Hui Tong. "Adaptive resource allocation in telecommunications." In SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, edited by Bruno Bosacchi, David B. Fogel, and James C. Bezdek. SPIE, 1999. http://dx.doi.org/10.1117/12.367703.

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Wong, Ian C., and Brian L. Evans. "Adaptive downlink OFDMA resource allocation." In 2008 42nd Asilomar Conference on Signals, Systems and Computers. IEEE, 2008. http://dx.doi.org/10.1109/acssc.2008.5074826.

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ter Braak, Timon D., Hermen A. Toersche, Andre B. J. Kokkeler, and Gerard J. M. Smit. "Adaptive resource allocation for streaming applications." In 2011 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS XI). IEEE, 2011. http://dx.doi.org/10.1109/samos.2011.6045489.

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Bandyopadhyay, C., V. Rajasimman, and J. Veerasamy. "Adaptive Resource Allocation in Wireless Networks." In 2006 IEEE/IFIP Network Operations and Management Symposium NOMS 2006. IEEE, 2006. http://dx.doi.org/10.1109/noms.2006.1687607.

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Yau, Stephen S., and Ho G. An. "Adaptive resource allocation for service-based systems." In the First Asia-Pacific Symposium. ACM Press, 2009. http://dx.doi.org/10.1145/1640206.1640209.

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Satoh, Ichiro. "Self-Adaptive Resource Allocation in Cloud Applications." In 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing (UCC). IEEE, 2013. http://dx.doi.org/10.1109/ucc.2013.41.

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Bakanoglu, Kagan, Wu Mingquan, Liu Hang, and Mathur Saurabh. "Adaptive Resource Allocation in Multicast OFDMA Systems." In Networking Conference (WCNC). IEEE, 2010. http://dx.doi.org/10.1109/wcnc.2010.5506213.

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Renk, Tobias, Dimitar Iankov, and Friedrich K. Jondral. "Adaptive Resource Allocation in Wireless Relay Networks." In 2009 IEEE 69th Vehicular Technology Conference Spring. IEEE, 2009. http://dx.doi.org/10.1109/vetecs.2009.5073366.

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Reports on the topic "Adaptive resource allocation"

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Frank, Martin, and Pedro Szekely. Real-Time MARBLES: A Scheme for Adaptive Distributed Resource Allocation. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada427580.

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Friedman, Sam, John Jakeman, Michael Eldred, Lorenzo Tamellini, Alex Gorodestky, and Doug Allaire. Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1807453.

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Cedergren, Elin, Hilma Salonen, and Lumi Tomren. Rethinking population shrinkage: smart adaptation for Nordic municipalities and regions. Nordregio, 2025. https://doi.org/10.6027/pb2025:19.2001-3876.

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Many Nordic municipalities are experiencing population decline, ageing, and uneven demographic trends, creating challenges for economic sustainability, service provision, and infrastructure development. While growth has traditionally been the policy focus, these shifts require a different approach. Smart adaptation offers a way to rethink resource allocation, adjust services, and foster innovation to build more resilient communities. This policy brief explores how policymakers and planners can develop adaptive strategies to manage demographic change effectively. It highlights key principles of

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Djanibekov, Nodir, Hiroyuki Takeshima, Bakhrom Mirkasimov, and Kamiljon Akramov. Enhancing agricultural resilience in Uzbekistan through farmers’ decision-making autonomy. TOSHKENT SHAHRIDAGI XALQARO VESTMINSTER UNIVERSITETI, 2025. https://doi.org/10.70735/dutv1060.

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Greater farmer’s decision-making autonomy enhances resilience in technical efficiency during economic shocks. Technical efficiency improves with autonomy, as farmers can adjust resource use, sustain productivity, and make adaptive choices regarding crop selection and input management. Eliminating top-down land allocations, granting secure land use rights, expanding financial and market access, and decentralizing training programs can improve the capacity of farmers to become more productive and adaptable in the face of current and future challenges.

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Sett, Dominic, Florian Waldschmidt, Alvaro Rojas-Ferreira, et al. Climate and disaster risk analytics tool for adaptive social protection. United Nations University - Institute for Environment and Human Security, 2022. http://dx.doi.org/10.53324/wnsg2302.

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Adaptive Social Protection (ASP) as discussed in this report is an approach to enhance the well-being of communities at risk. As an integrated approach, ASP builds on the interface of Disaster Risk Management (DRM), Climate Change Adaptation (CCA) and Social Protection (SP) to address interconnected risks by building resilience, thereby overcoming the shortcomings of traditionally sectoral approaches. The design of meaningful ASP measures needs to be informed by specific information on risk, risk drivers and impacts on communities at risk. In contrast, a limited understanding of risk and its d

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Hicks, Jacqueline. Examples of 'Systems Thinking' Projects in International Development. Institute of Development Studies, 2022. http://dx.doi.org/10.19088/k4d.2022.067.

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A “systems thinking” (ST) approach generally recognises that international development processes are complex, inter-related, non-linear, and constantly changing. They involve many different types of actors, all with different levels of power. ST change methods try to mirror these qualities, and move away from more conventional project design and implementation that use simple linear input-output-impact project logic. Thus, this rapid literature review seeks to find out what are some examples of ‘systems thinking’ projects in international development. The aim of this rapid review is to provide

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