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Journal articles on the topic 'Resource allocating'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Edavalath, Sheena, and Manikandasaran S. Sundaram. "MARCR: Method of allocating resources based on cost of the resources in a heterogeneous cloud environment." Scientific Temper 14, no. 03 (2023): 576–81. http://dx.doi.org/10.58414/scientifictemper.2023.14.3.03.

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The cloud is an intelligent technology that provides requested services to users. It offers unlimited services for the users. Many small and medium-scale industries are startup their businesses to the next level using cloud computing. The services have been provided to the users by allocating the requested resources. Allocating resources without waste and with the finest allocation is a critical task in the cloud. This paper proposes a method for allocating resources using the cost of the resource. Resource allocation follows a priority system when allocating resources. The proposed method giv

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Edavalath, Sheena, and Manikandasaran S. Sundaram. "Cost-based resource allocation method for efficient allocation of resources in a heterogeneous cloud environment." Scientific Temper 14, no. 04 (2023): 1339–44. http://dx.doi.org/10.58414/scientifictemper.2023.14.4.41.

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Cloud computing is appealing due to features like adaptability, portability, utility service and on-demand service. Cloud resource providers are a source of computing, and each provider delivers different types of resources. In an active cloud environment, timely resource allocation is more important. In order to increase the effectiveness and user-friendliness of resource allocation in the heterogeneous cloud, the paper suggests an efficient cost-based resource allocation (ECRA) method and framework. In the heterogeneous cloud, there is no centralized resource allocation manager (CRAM) to get

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Dolgov, D. A., and E. H. Durfee. "Resource Allocation Among Agents with MDP-Induced Preferences." Journal of Artificial Intelligence Research 27 (December 26, 2006): 505–49. http://dx.doi.org/10.1613/jair.2102.

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Allocating scarce resources among agents to maximize global utility is, in general, computationally challenging. We focus on problems where resources enable agents to execute actions in stochastic environments, modeled as Markov decision processes (MDPs), such that the value of a resource bundle is defined as the expected value of the optimal MDP policy realizable given these resources. We present an algorithm that simultaneously solves the resource-allocation and the policy-optimization problems. This allows us to avoid explicitly representing utilities over exponentially many resource bundle

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Gaurav, Raj1 Ankit Nischal2. "Efficient Resource Allocation in Resource provisioning policies over Resource Cloud Communication Paradigm." International Journal on Cloud Computing: Services and Architecture(IJCCSA) 2, June (2018): 01–08. https://doi.org/10.5281/zenodo.1438579.

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Optimal resource utilization for executing tasks within the cloud is one of the biggest challenges. In executing the task over a cloud, the resource provisioner is responsible for providing the resources to create virtual machines. To utilize the resources optimally, the resource provisioner has to take care of the process of allocating resources to Virtual Machine Manager (VMM). In this paper, an efficient way to utilize the resources, within the cloud, to create virtual machines has been proposed considering optimum cost based on performance factor. This performance factor depends upon the o

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Zheng, Junjun. "Optimization of Resource Allocation of University Innovation and Entrepreneurship Education Based on Collaborative Filtering Algorithm." Journal of Electrical Systems 20, no. 3s (2024): 1853–62. http://dx.doi.org/10.52783/jes.1724.

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Entrepreneurship education resource allocation involves the strategic distribution of resources to support programs and initiatives aimed at fostering entrepreneurial skills and mindset among students. These resources can include funding, faculty support, curriculum development, mentorship opportunities, and access to networks and facilities. Effective resource allocation ensures that entrepreneurship education programs are adequately equipped to provide students with the knowledge, skills, and support needed to succeed as entrepreneurs. By prioritizing resource allocation to areas such as exp

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Wang, Yanyan, and Baiqing Sun. "A Multiobjective Allocation Model for Emergency Resources That Balance Efficiency and Fairness." Mathematical Problems in Engineering 2018 (October 14, 2018): 1–8. http://dx.doi.org/10.1155/2018/7943498.

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Efficiency and fairness are two important goals of disaster rescue. However, the existing models usually unilaterally consider the efficiency or fairness of resource allocation. Based on this, a multiobjective emergency resource allocation model that can balance efficiency and fairness is proposed. The object of the proposed model is to minimize the total allocating costs of resources and the total losses caused by insufficient resources. Then the particle swarm optimization is applied to solve the model. Finally, a computational example is conducted based on the emergency relief resource allo

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Ma, Ding, M. Onderwater, F. Wetzels, et al. "Cost-Efficient Allocation of Additional Resources for the Service Placement Problem in Next-Generation Internet." Mathematical Problems in Engineering 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/517409.

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One of the major challenges in next-generation Internet is to allocate services to nodes in the network. This problem, known as theservice placement problem, can be solved by layered graph approach. However, due to the existence of resource bottleneck, the requests are rejected from the beginning in the resource constrained network. In this paper we propose two iterative algorithms for efficient allocation of additional resources in order to improve the ratio of accepted service placement requests. To this end, we (1) introduce a new concept of sensitivity for each service node to locate the b

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M, Sumathi, Niranjana B, Akshaya C, Ajitha M, and Bhavadharanee M. "Round Robin Based Efficient Resource Allocation and Utilization in an Organization." International Research Journal of Multidisciplinary Technovation 2, no. 2 (2020): 16–22. http://dx.doi.org/10.34256/irjmt2023.

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In an organization, resource allocation to a request is a complex task. Traditionally, resource allocation is done through manually with high time consumption. Similarly, collision is occurring for allocating a single resource to multiple requests. Thus, leads to complex problems and slow-down the working process. The existing resource allocation technique, allocate resources continuously to a specific request and omit another request. This kind of allocation technique also leads to lots of critical issues. That is the non-allocated process never gets a resource. To overcome these issues, the

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Chen, Chao, Changjun Fan, and Xingxing Liang. "A Multiobjective Resource Allocation Algorithm for Robust Project Scheduling." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7701–4. http://dx.doi.org/10.1166/jctn.2016.4426.

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Resource allocation is an important procedure which involves allocating finite resources to the activities of a given baseline schedule. Based on the conception of Pareto Optimization, a multiobjective optimization approach for the resource allocation problem is proposed in this paper. The problem is first described. Then the detailed procedure of the proposed algorithm is given. Finally, an extensive computational results obtained on a set of benchmark problems are reported.

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Deng, Hongyu, Cheng Wu, and Yiming Wang. "A cognitive gateway-based spectrum sharing method in downlink round robin scheduling of LTE system." Modern Physics Letters B 31, no. 19-21 (2017): 1740070. http://dx.doi.org/10.1142/s021798491740070x.

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A key technique of LTE is how to allocate efficiently the resource of radio spectrum. Traditional Round Robin (RR) scheduling scheme may lead to too many resource residues when allocating resources. When the number of users in the current transmission time interval (TTI) is not the greatest common divisor of resource block groups (RBGs), and such a phenomenon lasts for a long time, the spectrum utilization would be greatly decreased. In this paper, a novel spectrum allocation scheme of cognitive gateway (CG) was proposed, in which the LTE spectrum utilization and CG’s throughput were greatly i

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Mondal, Sakib A. "Resource allocation problem under single resource assignment." RAIRO - Operations Research 52, no. 2 (2018): 371–82. http://dx.doi.org/10.1051/ro/2017035.

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We consider a NP-hard resource allocation problem of allocating a set of resources to meet demands over a time period at the minimum cost. Each resource has a start time, finish time, availability and cost. The objective of the problem is to assign resources to meet the demands so that the overall cost is minimum. It is necessary that only one resource contributes to the demand of a slot. This constraint will be referred to as single resource assignment (SRA) constraint. We would refer to the problem as the S_RA problem. So far, only 16-approximation to this problem is known. In this paper, we

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Davies, Mark. "Allocating resources in mental health: a clinician's guide to involvement." Advances in Psychiatric Treatment 12, no. 5 (2006): 384–91. http://dx.doi.org/10.1192/apt.12.5.384.

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With fundamental changes to the way services are commissioned and resourced within the UK's National Health Service (NHS), optimising the efficient and effective use of resources has become a key task for mental health clinicians and managers. A core step in this process is ensuring that resources are optimally allocated across the service. This article outlines steps in resource allocation, including understanding how resources are managed through budgets, the link between resource matching and care delivery, and methods of reallocating resources to improve service performance. Influencing ap

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Yu, Zhipeng, Fangqing Gu, Hailin Liu, and Yutao Lai. "5G Multi-Slices Bi-Level Resource Allocation by Reinforcement Learning." Mathematics 11, no. 3 (2023): 760. http://dx.doi.org/10.3390/math11030760.

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As the centralized unit (CU)—distributed unit (DU) separation in the fifth generation mobile network (5G), the multi-slice and multi-scenario, can be better applied in wireless communication. The development of the 5G network to vertical industries makes its resource allocation also have an obvious hierarchical structure. In this paper, we propose a bi-level resource allocation model. The up-level objective in this model refers to the profit of the 5G operator through the base station allocating resources to slices. The lower-level objective in this model refers to the slices allocating the re

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HamaAli, Kurdistan Wns, and Subhi R. M. Zeebaree. "Resources Allocation for Distributed Systems: A Review." International Journal of Science and Business 5, no. 2 (2021): 76–88. https://doi.org/10.5281/zenodo.4462088.

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Resource allocation in a distributed system is the process of allocating the workload across multiple resources to optimize the required performance criteria. Different techniques are used to manage resource allocation in such distributed systems. The resource allocation for distributed systems such as cloud computing, cellular network, Software-Defined Networking (SDN), Radar Imaging and 5G Networks are used. In this paper many resource allocation algorithms in different environment and area that mentioned before are reviewed, compared and summarized. for instance, Cloud-based computation alg

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Thapa, Ram Bahadur. "Financial Resource Mobilization in Pokhara Sub-Municipal Corporation." Journal of Nepalese Business Studies 1, no. 1 (2006): 81–84. http://dx.doi.org/10.3126/jnbs.v1i1.42.

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Local bodies can play a vital role in nation building process through efficient mobilization of local financial resource. Financial resource mobilization includes both raising the adequate revenue and optimal allocation of funds to meet the local people’s needs. Municipality finances its expenditures with internal and external revenues. It has to increase its efficiency in allocating financial resources to maximize the marginal productivity of resources.  Journal of Nepalese Business Studies Vol.1(1) 2004 pp.81-84

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Deco, Gustavo, and Jürgen Ebmeyer. "Coarse Coding Resource-Allocating Network." Neural Computation 5, no. 1 (1993): 105–14. http://dx.doi.org/10.1162/neco.1993.5.1.105.

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In recent years localized receptive fields have been the subject of intensive research, due to their learning speed and efficient reconstruction of hypersurfaces. A very efficient implementation for such a network was proposed recently by Platt (1991). This resource-allocating network (RAN) allocates a new neuron whenever an unknown pattern is presented at its input layer. In this paper we introduce a new network architecture and learning paradigm. The aim of our approach is to incorporate "coarse coding" to the resource-allocating network. The network presented here provides for each input co

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Campbell, Thomas C. "Water: Allocating a Scarce Resource." Journal - American Water Works Association 77, no. 9 (1985): 53–56. http://dx.doi.org/10.1002/j.1551-8833.1985.tb05606.x.

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Lei, Xiaoli. "Resource Sharing Algorithm of Ideological and Political Course Based on Random Forest." Mathematical Problems in Engineering 2022 (May 21, 2022): 1–8. http://dx.doi.org/10.1155/2022/8765166.

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Three aspects of the system’s online resource distribution and application are built around subject, object, and intermediary resources. The invention relates to a method for allocating resources based on the random forest algorithm. The resource allocation process entails the following steps: constructing a mathematical model of the resource allocation process, defining a mathematical model of the resource allocation process for the target object, and designing the cost function. The training data set for random forest is constructed using the classification concept. It is based on the mathem

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Sathish, Kuppani, and A. Rama Mohan Reddy. "Resource Allocation Mechanism with New Models for Grid Environment." International Journal of Grid and High Performance Computing 5, no. 2 (2013): 1–26. http://dx.doi.org/10.4018/jghpc.2013040101.

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Resource allocation is playing a vital role in grid environment because of the dynamic and heterogeneous nature of grid resources. Literature offers numerous studies and techniques to solve the grid resource allocation problem. Some of the drawbacks occur during grid resource allocation are low utilization, less economic reliability and increased waiting time of the jobs. These problems were occurred because of the inconsiderable level in the code of allocating right resources to right jobs, poor economic model and lack of provision to minimize the waiting time of jobs to get their resources.

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George Fernandez, I., and J. Arokia Renjith. "Resource allocation, scheduling and auto-scaling algorithms for enhancing the performance of cloud using Grey Wolf Optimization and Fuzzy rules." Journal of Intelligent & Fuzzy Systems 39, no. 5 (2020): 7449–67. http://dx.doi.org/10.3233/jifs-200787.

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Cloud computing technology is playing a major role in the industry and real-life, for providing fast services such as data sharing and allocating the cloud resources that are paid and truly required. In this scenario, the cloud users are scheduled according to the rule-based systems for attempting to automate the matching between computing requirements and resources. Even though, the majority auto-scaling algorithms only helped as indicators for simple resource utilization and also not considered both cloud user needs and budget concerns. For this purpose, we propose a new model which is the c

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Zhang, Bin, and Yi Liu. "Distributed Resource Allocation for Green HetNets with Renewable Energy Resources." International Journal of Pattern Recognition and Artificial Intelligence 35, no. 08 (2021): 2159029. http://dx.doi.org/10.1142/s0218001421590291.

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In fifth generation (5G) systems, green heterogeneous network (HetNet) is capable of achieving energy efficiency by densely deploying renewable-powered small cells. However, the small cells may suffer performance degradation due to the limited backhaul from macro base station (BS) and renewable intermittency. In this paper, we introduce a distributed HetNet architecture in which the renewable-powered small cell BSs collaboratively exchange information and allocate the spectrum and power resources by themselves. Considering the uncertainty of the available spectrum, renewable energy supply and

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Mrs., K.S.Saraswathi Devi. "Federated Learning-Based Resource Allocation for Cloud-Edge Computing." IJAPR Journal UGC Indexed & Care Listed 7, no. 1 (2022): 120–25. https://doi.org/10.5281/zenodo.8311909.

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<strong>Cloud-edge computing is a promising paradigm that can address the challenges of latency, bandwidth, and privacy in cloud computing. However, the edge nodes have limited resources, so it is important to allocate resources efficiently. This paper proposes a federated learning-based resource allocation framework for cloud-edge computing. The proposed framework consists of three main components: a federated learning algorithm, a resource allocation algorithm, and a secure communication protocol. The federated learning algorithm is responsible for training a machine learning model without s

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Karamthulla, Musarath Jahan, Jesu Narkarunai, Arasu Malaiyappan, and Ravish Tillu. "Optimizing Resource Allocation in Cloud Infrastructure through AI Automation: A Comparative Study." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2, no. 2 (2023): 315–26. http://dx.doi.org/10.60087/jklst.vol2.n2.p326.

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Optimizing resource allocation in cloud infrastructure is paramount for ensuring efficient utilization of computing resources and minimizing operational costs. With the proliferation of diverse workloads and dynamic user demands, manual resource management becomes increasingly challenging. In this context, artificial intelligence (AI) automation emerges as a promising approach to enhance resource allocation efficiency. This paper presents a comparative study of various AI techniques applied to optimize resource allocation in cloud environments. We explore the efficacy of machine learning, evol

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Arora, Manish, and M. Syamala Devi. "Design of Multi Agent System for Resource Allocation and Monitoring." International Journal of Agent Technologies and Systems 3, no. 1 (2011): 1–10. http://dx.doi.org/10.4018/jats.2011010101.

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The objective of Resource Allocation and Monitoring System is to make the procedures involved in allocating fund resources to competing clients transparent so that deserving candidates get funds. Proactive and goal directed behaviour of agents make the system transparent and intelligent. This paper presents design of Multi Agent Systems for Resource Allocation and Monitoring using Agent Unified Modelling Language (AUML) and implementation in agent based development tool. At a conceptual level, three agents are identified with their roles and responsibilities. The identified agents, functionali

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Karahda, Aarti, and Shobhit Kumar Prasad. "The Mental Health Care Act 2017 and Mental Health Resource Allocation in India." Annals of Indian Psychiatry 8, no. 1 (2024): 83–88. http://dx.doi.org/10.4103/aip.aip_80_22.

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Abstract Mental health policymakers are now tasked with maximizing the efficient and effective use of mental health resources as a result of fundamental changes to mental health laws. A crucial step in this process is ensuring optimal resource allocation across the service. Multiple biases prevent policymakers from allocating resources to mental health, resulting in a violation of the right to health, an increase in suffering, and a heavy economic burden associated with mental illness. This article provides a summary of Indian mental health policy, examines Indian public perceptions of mental

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Chen, Zheng, Zhaoquan Gu, and Yuexuan Wang. "Incentives against Max-Min Fairness in a Centralized Resource System." Wireless Communications and Mobile Computing 2021 (October 18, 2021): 1–13. http://dx.doi.org/10.1155/2021/5570104.

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Resource allocating mechanisms draw much attention from various areas, and exploring the truthfulness of these mechanisms is a very hot topic. In this paper, we focus on the max-min fair allocation in a centralized resource system and explore whether the allocation is truthful when a node behaves strategically. The max-min fair allocation enables nodes receive appropriate resources, and we introduce an efficient algorithm to find out the allocation. To explore whether the allocation is truthful, we analyze how the allocation varies when a new node is added to the system, and we discuss whether

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Artiushenko, Bohdan. "A Nucleolus-Based Approach for Cloud Resource Allocation." NaUKMA Research Papers. Computer Science 7 (May 12, 2025): 25–30. https://doi.org/10.18523/2617-3808.2024.7.25-30.

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Cloud computing has transformed organizational operations by enabling flexible resource allocation and reducing upfront hardware investments. However, the growing complexity of resource management, particularly for computing instances, has led to challenges in cost control and resource allocation. Fair allocation policies, such as max-min fairness and Dominant Resource Fairness, aim to distribute resources fairly among users. In recent years, the FinOps framework has emerged to address cloud cost management, empowering teams to manage their own resource usage and budgets. The allocation of res

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Mao, Li, De Yu Qi, Wei Wei Lin, Bo Liu, and Ye Da Li. "An Energy-Efficient Resource Scheduling Algorithm for Cloud Computing based on Resource Equivalence Optimization." International Journal of Grid and High Performance Computing 8, no. 2 (2016): 43–57. http://dx.doi.org/10.4018/ijghpc.2016040103.

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With the rapid growth of energy consumption in global data centers and IT systems, energy optimization has become an important issue to be solved in cloud data center. By introducing heterogeneous energy constraints of heterogeneous physical servers in cloud computing, an energy-efficient resource scheduling model for heterogeneous physical servers based on constraint satisfaction problems is presented. The method of model solving based on resource equivalence optimization is proposed, in which the resources in the same class are pruning treatment when allocating resource so as to reduce the s

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Meadows, Graham. "Resource Allocation and Moral Theory: Easy and Hard Problems." Australasian Psychiatry 5, no. 5 (1997): 228–30. http://dx.doi.org/10.3109/10398569709082277.

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This paper is intended as a constructive response to“Managing Scarcity: a worked example using Burden and Efficacy”, from Professor Gavin Andrews. Professor Andrews” paper is helpful in proposing an approach to allocating resources which has some claims to being rational. However the presentation begs many questions. In this commentary, I set out to critique Professor Andrews” model of resource allocation from a moral theoretical perspective.

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Kazemi, Ali, and Daniel Eek. "EFFECTS OF GROUP GOAL AND RESOURCE VALENCE ON ALLOCATION PREFERENCES IN PUBLIC GOOD DILEMMAS." Social Behavior and Personality: an international journal 35, no. 6 (2007): 803–18. http://dx.doi.org/10.2224/sbp.2007.35.6.803.

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Previous research has not been conclusive as to whether people prefer different or identical allocation principles in distributions of positive and negative outcomes. Thus, in this study, the question of whether or not group goal accounts for preferred allocation of positive and negative outcomes was posed. As hypothesized for division of surpluses, the results showed that relationship-oriented goals predicted preferences for equality, whereas performance-oriented goals predicted preferences for equity. Moreover, the results were the same for allocation of deficits. This suggests that people i

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Tsachrelias, Konstantinos, Chrysostomos-Athanasios Katsigiannis, Vasileios Kokkinos, Apostolos Gkamas, Christos Bouras, and Philippos Pouyioutas. "Game Theory Algorithms for Resource Allocation in 5G MIMO." International Journal of Interactive Mobile Technologies (iJIM) 19, no. 13 (2025): 183–203. https://doi.org/10.3991/ijim.v19i13.56051.

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Efficient resource allocation is essential in 5G MIMO networks due to increasing demands for high-quality communications. This paper compares four game theory algorithms: Stackelberg, Nash Bargaining, Mean Field Game, and Potential Game, evaluating their effectiveness in allocating resources dynamically. A simulation environment is developed to represent realistic user mobility by continuously updating user equipment (UE) positions. Each algorithm is assessed based on UE distribution, fairness, bandwidth consumption, and energy efficiency. The simulation results show clear differences among th

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Patrão Neves, Maria do Céu. "Ethical health resources allocation: Why the distinction between ‘rationing’ and ‘rationalization’ matters." Revista de Bioética y Derecho, no. 50 (July 29, 2020): 63–79. http://dx.doi.org/10.1344/rbd2020.50.32044.

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Allocation of health resources has an irreducible ethical dimension, thus cannot be decided only technically, but must be ethically weighed, what paradigmatic experiences of macro (Oregon Basic Health Services Act, 1989) and micro allocation (God’s Committee, 1962) have shown. Justice is required in the enunciation of prioritization criteria, and transparency in its application. In situations of aggravated resource scarcity, it is common to take ‘allocate’ and ‘rationing’ as synonyms or claim that ‘allocate’ is always ‘rationing’. Rejecting these positions, there is a distinction between 'allo

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Md.Mahbub-Or-Rashid, Julkar Nayeen Mahi Md., Afrin Jeba Jenia, and Tuj Johura Fatema. "Achieving an Efficient Approach through using Resource Allocation, Management and Load Balancing for Cloud Data Centers." Recent Trends in Cloud Computing and Web Engineering 3, no. 1 (2021): 1–10. https://doi.org/10.5281/zenodo.4683400.

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Appropriate resource allocation and management in cloud datacenters has become a crucial consideration for the progress of cloud datacenters. Since allocating resources in a planned and convenient way has a prevailing impact in the issue of "Cloud computing" along these lines the cloud server farms must manage the complexities in making sense of and settling the strategies to control, dispense, utilize, work and move the resources in an enormously effective way. Maintaining Quality of Service (QoS) in cloud datacenters may also become tougher if resources (like- CPU, Hard disk, Memor

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Sandu, Roman, and Alexandr Shcherbakov. "A Resource Allocation Algorithm for a History-Aware Frame Graph." Journal of WSCG 31, no. 1-2 (2023): 63–70. http://dx.doi.org/10.24132/jwscg.2023.7.

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We consider the problem of memory consumption by a real-time GPU-accelerated graphical application. A history of a resource is defined for a particular frame to be the final contents of such a resource at the end of the previous frame. When organizing a graphical application using a frame rendering graph approach, it makes sense to implement automatic serving of resource history read requests of nodes. In absence of history resource requests, allocating resources for a fixed frame graph is the classic problem of dynamic storage allocation (DSA). In this paper, we formulate a generalization of

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Alodhaibi, Sultan, Robert L. Burdett, and Prasad K. D. V. Yarlagadda. "A Framework for Sharing Staff between Outbound and Inbound Airport Processes." Mathematics 8, no. 6 (2020): 895. http://dx.doi.org/10.3390/math8060895.

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This paper proposes an advanced simulation-optimization approach to evaluate and optimize the passenger flows within international airports. This approach allocates resources intelligently during the simulation process and balances demand and service quality. The resource allocation performed by our Advanced Resource Management (ARM) algorithm was used to develop an integrated system for arranging resources, identifying the proper resources, and allocating them throughout the model. It was used to investigate the influences of different staff allocation techniques on the inbound and outbound p

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Feng, Lei, Wenjing Li, Peng Yu, and Xuesong Qiu. "An Enhanced OFDM Resource Allocation Algorithm in C-RAN Based 5G Public Safety Network." Mobile Information Systems 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9586287.

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Public Safety Network (PSN) is the network for critical communication when disaster occurs. As a key technology in 5G, Cloud-Radio Access Network (C-RAN) can play an important role in PSN instead of LTE-based RAN. This paper firstly introduces C-RAN based PSN architecture and models the OFDM resource allocation problem in C-RAN based PSN as an integer quadratic programming, which allows the trade-off between expected bitrates and allocating fairness of PSN Service User (PSU). However, C-RAN based PSN needs to improve the efficiency of allocating algorithm because of a mass of PSU-RRH associati

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Aliu, Daniel, and Muyideen Omuya Momoh. "Optimal Resource Scheduling Algorithm for OFDMA-based Multicast Traffic Delivery over WIMAX Networks using Particle Swarm Optimization." International Journal of Software Engineering and Computer Systems 7, no. 2 (2021): 50–63. http://dx.doi.org/10.15282/ijsecs.7.2.2021.6.0089.

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Researchers are yet to entirely mapped out the difficulty in allocating optimal resources to mobile Worldwide Interoperability for Microwave Access (WiMAX) subscribers. This research presents an optimal scheduling algorithm for WiMAX resource allocation based on an Particle Swarm Optimization (PSO). In this work, sub-group creation is used to offer a PSO-based technique for allocating subcarriers and Orthogonal Frequency Division Multiplexing (OFDM) symbols to mobile WiMAX customers. The WiMAX network environment is organized into seven layers, with seven different modulation and coding algori

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Sangaiah, Arun Kumar, Ali Asghar Rahmani Hosseinabadi, Morteza Babazadeh Shareh, Seyed Yaser Bozorgi Rad, Atekeh Zolfagharian, and Naveen Chilamkurti. "IoT Resource Allocation and Optimization Based on Heuristic Algorithm." Sensors 20, no. 2 (2020): 539. http://dx.doi.org/10.3390/s20020539.

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The Internet of Things (IoT) is a distributed system that connects everything via internet. IoT infrastructure contains multiple resources and gateways. In such a system, the problem of optimizing IoT resource allocation and scheduling (IRAS) is vital, because resource allocation (RA) and scheduling deals with the mapping between recourses and gateways and is also responsible for optimally allocating resources to available gateways. In the IoT environment, a gateway may face hundreds of resources to connect. Therefore, manual resource allocation and scheduling is not possible. In this paper, t

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Hamrick, Florence A., John H. Schuh, and Mack C. Shelley. "Predicting higher education graduation rates from institutional characteristics and resource allocation." education policy analysis archives 12 (May 4, 2004): 19. http://dx.doi.org/10.14507/epaa.v12n19.2004.

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This study incorporated institutional characteristics (e.g., Carnegie type, selectivity) and resource allocations (e.g., instructional expenditures, student affairs expenditures) into a statistical model to predict undergraduate graduation rates. Instructional expenditures, library expenditures, and a number of institutional classification variables were significant predictors of graduation rates. Based on these results, recommendations as well as warranted cautions are included about allocating academic financial resources to optimize graduation rates

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Qiao, Liang, Miao Dai, and Meng Na Li. "Integrated Water Resource Management in Yinchuan Plain." Applied Mechanics and Materials 448-453 (October 2013): 1057–61. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.1057.

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Based on the analysis of the current state of water resources and utilization characters, the optimizing and allocating model of water resources in Yinchuan plain is established by multi-objective planning methodology. Systematic viewpoint runs throughout the whole modeling process. Furthermore, by employing the established model, the proper allocation of the industrial and agricultural water, the ecological environment water and integrated development of surface water and groundwater are discussed. The more reasonable water utilization structure is suggested. The water resource for agricultur

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Manzoor, Muhammad Faraz, Adnan Abid, Muhammad Shoaib Farooq, Naeem A. Azam, and Uzma Farooq. "Resource Allocation Techniques in Cloud Computing: A Review and Future Directions." Elektronika ir Elektrotechnika 26, no. 6 (2020): 40–51. http://dx.doi.org/10.5755/j01.eie.26.6.25865.

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Cloud computing has become a very important computing model to process data and execute computationally concentrated applications in pay-per-use method. Resource allocation is a process in which the resources are allocated to consumers by cloud providers based on their flexible requirements. As the data is expanding every day, allocating resources efficiently according to the consumer demand has also become very important, keeping Service Level Agreement (SLA) between service providers and consumers in prospect. This task of resource allocation becomes more challenging due to finite available

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Shakil, Kashish Ara, Mansaf Alam, and Samiya Khan. "A latency-aware max-min algorithm for resource allocation in cloud." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 671. http://dx.doi.org/10.11591/ijece.v11i1.pp671-685.

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Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. This pap

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Kashish, Ara Shakil, Alam Mansaf, and Khan Samiya. "A latency-aware max-min algorithm for resource allocation in cloud." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 671–85. https://doi.org/10.11591/ijece.v11i1.pp671-685.

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Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. Th

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Choi, Hyunseok, Yoonhyeong Lee, Gayeong Kim, Euisin Lee, and Youngju Nam. "Resource Cluster-Based Resource Search and Allocation Scheme for Vehicular Clouds in Vehicular Ad Hoc Networks." Sensors 24, no. 7 (2024): 2175. http://dx.doi.org/10.3390/s24072175.

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Vehicular clouds represent an appealing approach, leveraging vehicles’ resources to generate value-added services. Thus, efficiently searching for and allocating resources is a challenge for the successful construction of vehicular clouds. Many recent schemes have relied on hierarchical network architectures using clusters to address this challenge. These clusters are typically constructed based on vehicle proximity, such as being on the same road or within the same region. However, this approach struggles to rapidly search for and consistently allocate resources, especially considering the di

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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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Григорьева, М. П., О. В. Кружкова та Е. С. Кузнецова. "Модель и алгоритмы распределения внутренних ресурсов в организационной системе". Сибирский пожарно-спасательный вестник, № 3(34) (11 жовтня 2024): 41–55. http://dx.doi.org/10.34987/vestnik.sibpsa.2024.92.92.003.

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Рассмотрены механизмы распределения государственных ресурсов на содержание федеральных органов исполнительной власти в сложных условиях несбалансированности бюджетов и оптимизации финансирования для исполнения бюджетных полномочий в полном объеме, не снижая качества предоставления государственных услуг. Предложены модель и алгоритмы распределения ресурсов территориального органа федерального органа исполнительной власти (ФОИВ) на примере МЧС России. Авторами рассмотрены ключевые особенности планирования и распределения ресурсов при осуществлении основных видов деятельности. В рамках исследован

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Cummings, Leslie E., and Jerome J. Vallen. "Considerations for Microcomputing Resource Decisions In Hri Programs." Hospitality Education and Research Journal 12, no. 2 (1988): 37–46. http://dx.doi.org/10.1177/109634808801200205.

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HRI decision-makers charged with putting in place appropriate microcomputer resources face the challenges of assessing needs, identifying educational objectives, and appropriating and allocating resources. In this paper are outlined major considerations for each area, supported by interviews, a literature review, and the experience of the authors. Vallen has been dean of a major hospitality administration program for 21 years. Cummings is a former computer analyst for a large computer firm and, for the past four years, has served as computing coordinator within the above program. Key terms: co

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Dhanalakshmi, B. K., K. C. Srikantaiah, and K. R. Venugopal. "Dynamic Computation of Threshold Value for Classifying Jobs in Cloud Computing for Efficient Resource Utilization." Journal of Computational and Theoretical Nanoscience 17, no. 9 (2020): 4458–61. http://dx.doi.org/10.1166/jctn.2020.9097.

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Cloud computing is an instant use of resources and it is a trending technology in the field of computer science. Here, many jobs will be arriving continuously with different job size, at that point of time, allocating of resources for suitable virtual machines without allowing virtual machine to starving is a hindrance job. So, to avoid this hindrance, an algorithm Dynamic Computation of Threshold Value is proposed (DCTV) and based on the threshold value the jobs are classified in the initial stage, so this classification leads to allocation of resources precisely and efficient resource utiliz

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Amuji, Harrison O., Donatus E. Onwuegbuchunam, Geoffrey U. Ugwuanyim, et al. "A STOCHASTIC DYNAMIC PROGRAMMING MODEL OF POLICE RESOURCE ALLOCATION FOR CRIME CONTROL." Advances and Applications in Discrete Mathematics 42, no. 4 (2025): 401–14. https://doi.org/10.17654/0974165825026.

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In this paper, we developed a non-homogeneous Poisson process-based stochastic dynamic programming model for efficient allocation of police resources with precision and effective crime control. Another important model developed alongside the stochastic dynamic programming model was the optimal decision model for allocating police resources to regions with probabilities of intercepting crimes. The two developed models were applied to crime and logistics data from Area Command, Enugu for optimal resource allocation. From this work, we conclude that for effective crime prevention and control, Are

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Sharma, Neha, Lakshay Kumar, Namrata Dwivedi, Ashpinder Kaur, and Gagandeep Kaur. "Resource Allocation and Security Threat in Cloud Computing: A Survey." CGC International Journal of Contemporary Technology and Research 6, no. 2 (2024): 381–87. http://dx.doi.org/10.46860/cgcijctr.2024.06.10.381.

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Cloud computing is a cutting-edge technology with enormous commercial and enterprise potential. Apps and related data can be accessed from any location thanks to clouds. Companies can drastically lower the cost of their infrastructure by renting resources from the cloud for storage and other processing needs. They can also use pay-as-you-go application access available to the entire firm. Therefore, obtaining licenses for specific products is not necessary. However, allocating resources as efficiently as possible is one of the main challenges in cloud computing. Because the model is unique, re

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