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Journal articles on the topic 'Deployment cost'

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1

Yamashina, H., and T. Kubo. "Manufacturing cost deployment." International Journal of Production Research 40, no. 16 (2002): 4077–91. http://dx.doi.org/10.1080/00207540210157178.

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YAMASHINA, Hajime, Takashi KUBO, and Keiichi OKAZAKI. "Manufacturing Cost Deployment." Journal of the Japan Society for Precision Engineering 65, no. 2 (1999): 260–66. http://dx.doi.org/10.2493/jjspe.65.260.

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3

Venturini, Stefano, Guido Giovando, and Chiara Crovini. "Evolutions in manufacturing cost deployment." Global Business and Economics Review 22, no. 1/2 (2020): 41. http://dx.doi.org/10.1504/gber.2020.10026684.

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Giovando, Guido, Chiara Crovini, and Stefano Venturini. "Evolutions in manufacturing cost deployment." Global Business and Economics Review 22, no. 1/2 (2020): 41. http://dx.doi.org/10.1504/gber.2020.105029.

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Reddy, Vonteru Srikanth, and Kumar Debasis. "Statistical Review of Health Monitoring Models for Real-Time Hospital Scenarios." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7s (2023): 465–81. http://dx.doi.org/10.17762/ijritcc.v11i7s.7025.

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Health Monitoring System Models (HMSMs) need speed, efficiency, and security to work. Cascading components ensure data collection, storage, communication, retrieval, and privacy in these models. Researchers propose many methods to design such models, varying in scalability, multidomain efficiency, flexibility, usage and deployment, computational complexity, cost of deployment, security level, feature usability, and other performance metrics. Thus, HMSM designers struggle to find the best models for their application-specific deployments. They must test and validate different models, which incr
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Kennedy, Tom. "Cost Saving Approach to GIS Deployment." Proceedings of the Water Environment Federation 2003, no. 7 (2003): 224–31. http://dx.doi.org/10.2175/193864703784641126.

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7

Ameli, Nadia, and Daniel M. Kammen. "Clean energy deployment: addressing financing cost." Environmental Research Letters 7, no. 3 (2012): 034008. http://dx.doi.org/10.1088/1748-9326/7/3/034008.

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8

Bode, Jürgen, and Richard Y. K. Fung. "Cost engineering with quality function deployment." Computers & Industrial Engineering 35, no. 3-4 (1998): 587–90. http://dx.doi.org/10.1016/s0360-8352(98)00165-x.

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9

Jeyaratnam, Canestus, Louis Doukas, and Graham Pollock. "Integrative Systems Approach to Cost Deployment." INCOSE International Symposium 9, no. 1 (1999): 1324–29. http://dx.doi.org/10.1002/j.2334-5837.1999.tb00311.x.

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10

Kumarasamy, Somasundaram. "Cost-Efficient Deployment Strategies: A Comparative Analysis of Feature Flagging Services and Blue/Green Deployments." Asian Journal of Research in Computer Science 17, no. 6 (2024): 96–101. http://dx.doi.org/10.9734/ajrcos/2024/v17i6459.

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Aims: This study provides a detailed comparison of two leading feature flagging services, LaunchDarkly and ConfigCat, and also examines the cost-efficiency and operational implications of using Blue/Green deployment strategies. It seeks to aid stakeholders in understanding the trade-offs and benefits of each approach to make informed decisions based on project-specific needs, budget constraints, and developmental objectives. Study Design: The study employs a comparative analysis framework, focusing on features, usability, scalability, architectural design, and the financial impacts of adopting
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Liagkou, Vasiliki, George Fragiadakis, Evangelia Filiopoulou, Vagia Kyriakidou, Christos Michalakelis, and Mara Nikolaidou. "Comparing the Cost of IaaS and CaaS Services." International Journal of Technology Diffusion 13, no. 1 (2022): 1–11. http://dx.doi.org/10.4018/ijtd.315632.

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Cloud computing environments allow businesses to deploy applications in a fast and scalable way. Infrastructure-as-a-service (IaaS) and container-as-a-service (CaaS) models can be adopted for the deployment of cloud-based applications. The current paper presents a specific near-real-world scenario of a cloud-based application, deployed by the two aforementioned cloud models. The deployment cost differs between the cloud models and relies on the number of utilized resources, which is driven by the user demand. Since the cost is a major importance factor that finally determines the adoption of c
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Bartolucci, Andrea, Darren Walter, and Tony Redmond. "Comparative Review on the Cost-Effectiveness Analysis of Relief Teams’ Deployment to Sudden-Onset Disasters." Prehospital and Disaster Medicine 34, no. 04 (2019): 415–21. http://dx.doi.org/10.1017/s1049023x19004540.

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AbstractWhen a disaster exceeds the capacity of the affected country to cope with its own resources, the provision of external rescue and health services is required, and the deployment of relief units requested. Recently, the cost of international relief and the belief that such deployment is cost-effective has been questioned by the international community; unfortunately, there is still little informed debate and few detailed data are available. This paper presents the results of a comparative review on the cost-effectiveness analysis (CEA) of search and rescue (SAR) and Emergency Medical Te
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Khatiwoda, Naba Raj, and Babu R. Dawadi. "A study on FTTH implementation and migration in Nepal." Journal of Engineering Issues and Solutions 1, no. 1 (2021): 174–96. http://dx.doi.org/10.3126/joeis.v1i1.36836.

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The increasing demand of high speed data results into extensive enhancement on different telecommunication technologies through wireline and wireless technologies. Optical Fiber technology is being popular for fixed broadband technologies and for backhaul network data for network convergence and media device interaction. Fiber to the home (FTTH) is gaining momentum of deployments in many countries all around the world. Passive optical network (PON) utilizes point to multipoint (P2MP) topology and is becoming suitable, cost effective, and promising solutions as compared to existing copper based
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14

Malandrino, Francesco, Carla Fabiana Chiasserini, Gil Einziger, and Gabriel Scalosub. "Reducing Service Deployment Cost Through VNF Sharing." IEEE/ACM Transactions on Networking 27, no. 6 (2019): 2363–76. http://dx.doi.org/10.1109/tnet.2019.2945127.

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15

Akindeji, Akinlabi, and Meera Joseph. "Optimal deployment of femtocells using cost function." International Journal of Communication Systems 31, no. 5 (2017): e3496. http://dx.doi.org/10.1002/dac.3496.

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Ramya Boorugula. "Serverless computing for ML workloads: The convergence of on-demand resources and model deployment." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 918–24. https://doi.org/10.30574/wjaets.2025.15.2.0637.

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Serverless computing represents a transformative approach for machine learning deployments, offering event-driven execution, automatic scaling, and pay-per-use billing models that address longstanding operational challenges. This article explores the convergence of serverless architectures with machine learning workloads, examining how this integration reshapes deployment practices and operational economics. The global serverless architecture market continues rapid expansion, with ML deployments representing an increasingly significant segment. The evolution from traditional server-based deplo
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Odarchenko, R. S., A. D. Pinchuk, and O. O. Polihenko. "LTE network deployment based on open-source solutions." Herald of the Kazakh-British technical university 20, no. 4 (2023): 40–47. http://dx.doi.org/10.55452/1998-6688-2023-20-4-40-47.

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In recent years, the landscape of LTE network deployment has experienced a significant shift from reliance on proprietary solutions provided by established vendors to the exploration of open-source alternatives. Open-source solutions have gained traction due to their cost-effectiveness and flexibility, allowing network operators to customize their deployments according to specific requirements and preferences. This article examines the deployment of a 4G LTE network based on open-source solutions. In the context of open-source, the options of using software and hardware for network deployment
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18

Hadi, Mohammed A., Diane Quigley, Prasoon Sinha, and Liang Hsia. "Benefit and Cost Parameters of Intelligent Transportation Systems." Transportation Research Record: Journal of the Transportation Research Board 1910, no. 1 (2005): 57–63. http://dx.doi.org/10.1177/0361198105191000107.

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The Intelligent Transportation Systems (ITS) Deployment Analysis System (IDAS) is a sketch planning analysis tool that can be used to estimate the impacts and costs resulting from the deployment of ITS components. The program includes default values for the parameters required to calculate ITS deployment costs and benefits. IDAS allows users to override the default values of ITS device cost and benefit parameters, including unit cost estimates, cost assumptions, benefit module parameters, ITS impacts, and impact dollar values. On one hand, the use of cost and benefit parameter values that bett
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Theisen, Adam, Max Ungar, Bryan Sheridan, and Bradley G. Illston. "More science with less: evaluation of a 3D-printed weather station." Atmospheric Measurement Techniques 13, no. 9 (2020): 4699–713. http://dx.doi.org/10.5194/amt-13-4699-2020.

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Abstract. A weather station built using 3D-printed parts and low-cost sensors, based on plans and guidance provided by the University Corporation for Atmospheric Research 3D-Printed Automatic Weather Station Initiative, was deployed alongside an Oklahoma Mesonet station to compare its performance against standard commercial sensors and determine the longevity and durability of the system. Temperature, relative humidity, atmospheric pressure, wind speed and direction, solar radiation, and precipitation measurements were collected over an 8-month field deployment in Norman, Oklahoma. Measurement
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20

Lin, Guanjing, Hannah Kramer, Valerie Nibler, Eliot Crowe, and Jessica Granderson. "Building Analytics Tool Deployment at Scale: Benefits, Costs, and Deployment Practices." Energies 15, no. 13 (2022): 4858. http://dx.doi.org/10.3390/en15134858.

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Buildings are becoming more data-rich. Building analytics tools, including energy information systems (EIS) and fault detection and diagnostic (FDD) tools, have emerged to enable building operators to translate large amounts of time-series data into actionable findings to achieve energy and non-energy benefits. To expedite data analytics adoption and facilitate technology innovation, building owners, technology developers, and researchers need reliable cost–benefit data and evidence-based guidance on deployment practices. This paper fulfills these needs with the energy use and survey data from
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21

Marco, Anisetti, A. Ardagna Claudio, Damiani Ernesto, Gaudenzi Filippo, and Jeon Gwanggil. "Cost-effective deployment of certified cloud composite services." Journal of Parallel and Distributed Computing 135, January 2020 (2018): 203–18. https://doi.org/10.1016/j.jpdc.2019.09.003.

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The advent of cloud computing has radically changed the concept of distributed environments, where services can now be composed and reused at high rates. Today, service composition in the cloud is driven by the need of providing stable QoS, where non-functional properties of composite services are proven over time and composite services continuously adapt to both functional and non-functional changes of the component services. This scenario introduces substantial costs on the cloud providers that go beyond the cost of deploying component services, and require to consid
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22

Basorun, Oluseyi, and Mnse Mnieee Mieee. "Implementing Enterprise VoIP Deployment." Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552) 3, no. 4 (2016): 06–16. http://dx.doi.org/10.53555/nncse.v3i4.424.

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Voice over Internet Protocol (VoIP) is perceived as the best example of collaboration technology in today’s telecommunication space. There have being a paradigm shift from regular legacy telephone systems to VoIP over the last decade by most telecommunication and multinational companies globally. One of the huge benefit of VoIP is noticeable reduction in international call rates. In addition to the potential cost savings, VoIP offers the prospect of integrating voice with data and video applications, this goes a long way in increasing workers’ productivity within organizations. Many organizati
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23

Wang, Zhigang, Liqin Tian, Lianhai Lin, and Yinghua Tong. "Lattice-Based 3-Dimensional Wireless Sensor Deployment." Journal of Sensors 2021 (August 17, 2021): 1–14. http://dx.doi.org/10.1155/2021/2441122.

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With the wide application of wireless sensor networks (WSNs) in real space, there are numerous studies on 3D sensor deployments. In this paper, the k -connectivity theoretical model of fixed and random nodes in regular lattice-based deployment was proposed to study the coverage and connectivity of sensor networks with regular lattice in 3D space. The full connectivity range and cost of the deployment with sensor nodes fixed in the centers of four regular lattices were quantitatively analyzed. The optimal single lattice coverage model and the ratio of the communication range to the sensing rang
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24

Ukani, Neema Amish, and Saurabh S. Chakole. "Empirical analysis of machine learning-based moisture sensing platforms for agricultural applications: A statistical perspective." Journal of Physics: Conference Series 2327, no. 1 (2022): 012026. http://dx.doi.org/10.1088/1742-6596/2327/1/012026.

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Abstract Modelling of accurate detection & estimation soil moisture sensors requires integration of various signal processing, filtering, segmentation, and pattern analysis methods. Sensing of moisture is generally performed via use of resistive, or capacitive materials, which change their parametric characteristics w.r.t. changes in moisture levels. These sensors are further classified depending upon capabilities of measurements, which include, volumetric sensors, soil water tensor sensors, electromagnetic sensors, time domain reflectometry (TDR) sensors, Neutron probe sensors, tensiomete
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25

Sangeetha J, Keerthiraj Nagaraj, Ram Prakash Rustagi, and Balasubramanya Murthy K N. "Placement of Relay Stations in WiMAX Network Using Glowworm Swarm Optimization." International Journal of Applied Metaheuristic Computing 10, no. 3 (2019): 39–67. http://dx.doi.org/10.4018/ijamc.2019070103.

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The Relay Station (RS) deployment problem for WiMAX networks is studied. Unlike Base Station (BS), RS does not need a wire-line backhaul and has much lower hardware complexity. Hence, usage of RSs can significantly minimize the deployment cost and maximize the network coverage of the system. To solve the RS deployment problem, the authors have used a nature inspired technique known as Glowworm Swarm Optimization (GSO). Different cases have been considered for a single fixed BS, to find the feasible number of RSs and its optimal placement in WiMAX networks. Computational experiments are conduct
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26

Sørensen, Lars, Lars Jacobsen, and John Hansen. "Low Cost and Flexible UAV Deployment of Sensors." Sensors 17, no. 12 (2017): 154. http://dx.doi.org/10.3390/s17010154.

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27

Jia, Lu, and Yasheng Zhang. "Cost Estimation Model for Mega-Constellation Deployment Missions." IEEE Access 9 (2021): 156778–88. http://dx.doi.org/10.1109/access.2021.3130295.

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28

Zhang, Shan, Ning Zhang, Peng Yang, and Xuemin Shen. "Cost-Effective Cache Deployment in Mobile Heterogeneous Networks." IEEE Transactions on Vehicular Technology 66, no. 12 (2017): 11264–76. http://dx.doi.org/10.1109/tvt.2017.2724547.

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29

Anisetti, Marco, Claudio A. Ardagna, Ernesto Damiani, Filippo Gaudenzi, and Gwanggil Jeon. "Cost-effective deployment of certified cloud composite services." Journal of Parallel and Distributed Computing 135 (January 2020): 203–18. http://dx.doi.org/10.1016/j.jpdc.2019.09.003.

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30

Pandiri, Subash Babu. "Cloud deployment model and cost analysis in Multicloud." IOSR Journal of Electronics and Communication Engineering 4, no. 3 (2012): 25–31. http://dx.doi.org/10.9790/2834-0432531.

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31

Wang, Hao, Jianzhong Li, and Hong Gao. "Minimized Cost Gateway Deployment in Cyber-Physical Systems." International Journal of Distributed Sensor Networks 11, no. 9 (2015): 813656. http://dx.doi.org/10.1155/2015/813656.

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32

Al-Shareefi, Nael A., and Ammar AbdRaba Sakran. "A novel optimal small cells deployment for next-generation cellular networks." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (2021): 5259. http://dx.doi.org/10.11591/ijece.v11i6.pp5259-5265.

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Small-cell-deployments have pulled cellular operators to boost coverage and capacity in high-demand areas (for example, downtown hot spots). The location of these small cells (SCs) should be determined in order to achieve successful deployments. In this paper, we propose a new approach that optimizes small cells deployment in cellular networks to achieve three objectives: reduce the total cost of network installation, balancing the allocation of resources, i.e. placement of each SC and their transmitted power, and providing optimal coverage area with a lower amount of interference between adja
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Nael, A. Al-Shareefi, and AbdRaba Sakran Ammar. "A novel optimal small cells deployment for next-generation cellular networks." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (2021): 5259–65. https://doi.org/10.11591/ijece.v11i6.pp5259-5265.

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Small-cell-deployments have pulled cellular operators to boost coverage and capacity in high-demand areas (for example, downtown hot spots). The location of these small cells (SCs) should be determined in order to achieve successful deployments. In this paper, we propose a new approach that optimizes small cells deployment in cellular networks to achieve three objectives: reduce the total cost of network installation, balancing the allocation of resources, i.e. placement of each SC and their transmitted power, and providing optimal coverage area with a lower amount of interference between adja
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34

Ardelia, Naila, Lindawati Lindawati, and Nurhajar Anugraha. "Comparison of Automation Deployment Implementation on Google Cloud Virtual Machine Using Deployment Manager and Terraform." Jurnal Teknologi Informasi dan Pendidikan 17, no. 2 (2025): 529–42. https://doi.org/10.24036/jtip.v17i2.869.

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Software development has significantly transformed in recent years, with organizations increasingly turning to cloud computing infrastructure to speed up and ease the development and implementation processes. Up until now, there are few studies testing the efficiency and performance of deployment automation using Google Cloud Deployment Manager, which is essentially a built-in infrastructure deployment service provided by Google Cloud Platform. Most studies tend to prefer using open-source software such as Terraform, Ansible, and Kubernetes. This research aims to compare the implementation of
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35

Mauleón, Ignacio. "Assessment of Renewable Energy Deployment Roadmaps." Energies 12, no. 15 (2019): 2875. http://dx.doi.org/10.3390/en12152875.

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This research implements a methodology to the joint assessment of the photovoltaic and onshore wind investment roadmaps put forward by the main institutions in the field, International Renewable Energy Association (Irena) and the International Energy Agency, to achieve a low carbon emissions economy with near zero net greenhouse gases emissions. The two energies taken together account for over 80% of the renewable energy deployments envisaged by both roadmaps. The assessment is conducted according to economic criteria (the levelized cost of energy, capital requirements and financial risks), an
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Darbari, Dr Manuj. "Enhancing Organizational Infrastructure Using Kubernetes." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48763.

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Abstract - This paper presents a zero-cost, fully automated cloud-native deployment framework using Kubernetes, targeting small teams, academic settings, and early-stage startups. The framework leverages freely available DevOps tools and platforms (GitHub Actions, Docker, Render, MongoDB Atlas) to orchestrate microservice-based web applications with full CI/CD capabilities. The goal is to reduce deployment complexity while improving scalability, reliability, and performance without requiring paid infrastructure. This solution offers a sustainable and robust deployment pipeline with minimal man
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37

Yunas, Syed Fahad, Waqas H. Ansari, and Mikko Valkama. "Technoeconomical Analysis of Macrocell and Femtocell Based HetNet under Different Deployment Constraints." Mobile Information Systems 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/6927678.

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Ultradense deployment of small cells is being considered as one of the key flavors of the emerging 5G cellular networks to address the future data capacity challenges. A large share of these deployments will be indoor, as this is the arena where the majority of the data traffic is believed to originate from in the future. Indoor small cell solutions (e.g., femtocell or WiFi) are well positioned for delivering superior indoor coverage and capacity. However, due to relatively smaller coverage footprint compared to traditional macrocells, a very dense deployment of small cells will be needed in o
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38

Ifechukwude Ashiedu, Benedict, Ejielo Ogbuefi, Uloma Stella Nwabekee, Jeffrey Chidera Ogeawuchi, and Abraham Ayodeji Abayomi. "Predictive Analytics in Site Operations Management: Optimizing Rural Deployment in Telecom Networks." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 2326–36. https://doi.org/10.62225/2583049x.2024.4.6.4327.

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Predictive analytics is revolutionizing site operations management, particularly in the context of rural telecom network deployment. As network providers face mounting pressure to expand coverage to underserved regions, the ability to make data-driven decisions becomes essential for cost efficiency, speed, and service quality. This presents a predictive analytics framework tailored to optimize rural deployment strategies by refining the analysis of contractor payments and site-level operational data. Leveraging historical payment records, project timelines, and performance metrics from existin
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39

Ye, Hengzhou, Fengyi Huang, and Wei Hao. "On Cost-Aware Heterogeneous Cloudlet Deployment for Mobile Edge Computing." International Journal of Information Technology and Web Engineering 17, no. 1 (2022): 1–23. http://dx.doi.org/10.4018/ijitwe.297968.

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Edge computing undertakes downlink cloud services and uplink terminal computing tasks, data interaction latency and network transmission cost are thus significantly reduced. Although a lot of research has been conducted in mobile edge computing (MEC), which assumed that all homogeneous cloudlets are placed in WMAN and user mobility is also ignored, little attention is paid to how to place heterogeneous cloudlets in wireless metropolitan area network (WMAN) to minimize the deployment cost of cloudlets. Meanwhile, the method of selecting an optimal access point (AP) for deployment, modeling and
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Walker, Jonathan B., and Kevin Heaslip. "A Low-Cost Real-World Planning Strategy for Deploying a Dedicated Short-Range Communications Roadside Unit on a Highway Off-Ramp." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 19 (2018): 124–34. http://dx.doi.org/10.1177/0361198118776813.

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The deployment of dedicated short-range communications (DSRC) roadside units (RSUs) allows a connected or automated vehicle to acquire information from the surrounding environment, such as a traffic light’s signal phase and timing, using vehicle-to-infrastructure communication. Several scholarly papers exist on planning strategies for DSRC RSU deployments using simulation without accounting for wireless communication constraints and environmental changes. This paper proposes an empirical-based planning strategy for a highway off-ramp in a real-world environment. The research goal focuses on de
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Xu, Meng, Qing Zhong Li, and Li Zhen Cui. "Performance and Cost Aware Application Placement in Cloud." Applied Mechanics and Materials 631-632 (September 2014): 204–9. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.204.

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With the development of Internet technology, cloud computing has been widely applied to various industries as a new service delivery model in recent years. The cloud service providers must provide services for many customs at the same time. So a large number of different applications must be deployed and the application deployment problem becomes more and more important. How to deploy the application according to their different performance requirements has an important effect on improving the quality of service, enhancing user experience and reducing the service cost. However, for service pro
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Abel, Chai Yu Hao, Hung Lai Chean, Tiong Su Hieng, et al. "Cost estimation methods for internet infrastructure deployment in Rural Sarawak: a review." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 3 (2020): 1375–83. https://doi.org/10.11591/ijeecs.v19.i3.pp1375-1383.

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In rural Sarawak, the internet accessibility is low due to unreliable power grids to support telecommunication network and large geographical area. The risk for network infrastructure implementation is high for Internet Service Provider (ISP), thus more practical and accurate cost estimation methods should be used. This paper reviews different types of cost estimation methods and the accuracy and feasibility of each methods are discussed and compared for network infrastructure implementation in rural Sarawak. The unique characteristics of rural Sarawak are considered in this work, including th
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Shao, Yanling, Zhen Shen, Siliang Gong, and Hanyao Huang. "Cost-Aware Placement Optimization of Edge Servers for IoT Services in Wireless Metropolitan Area Networks." Wireless Communications and Mobile Computing 2022 (July 27, 2022): 1–17. http://dx.doi.org/10.1155/2022/8936576.

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Edge computing migrates cloud computing capacity to the edge of the network to reduce latency caused by congestion and long propagation distance of the core network. And the Internet of things (IoT) service requests with large data traffic submitted by users need to be processed quickly by corresponding edge servers. The closer the edge computing resources are to the user network access point, the better the user experience can be improved. On the other hand, the closer the edge server is to users, the fewer users will access simultaneously, and the utilization efficiency of nodes will be redu
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44

Корнеева, Т. А., and А. М. Кривоногов. "The method of "Cost deployment". The basic of tools, integration into a lean management system." Экономика и предпринимательство, no. 8(145) (January 19, 2023): 1234–37. http://dx.doi.org/10.34925/eip.2022.145.8.256.

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Авторами данной статьи рассматриваются ключевые особенности метода, этапы внедрения на производстве, основные преимущества для бизнеса. The authors of this article consider the key features of the method "Cost deployment". It describes the main steps of cost deployment and is showed benefits for lean factories.
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Fan, Tie Gang, Gui Fa Teng, and Li Min Huo. "Minimum Cost Programming Models of Nodes Deployment for WSNs." Applied Mechanics and Materials 719-720 (January 2015): 696–701. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.696.

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WSNs can cover a wide range of application. Node deployment is a fundamental factor in determining the connectivity, coverage, lifetime and cost of WSNs. This paper focuses on the cost of network that satisfies some constraints (coverage, connectivity and lifetime). In order to satisfy the connectivity and coverage, we use the regular hexagonal cell architecture. We present a new metric, the Cost Per Unit Area and Lifetime, to be objective function. Three programming models are proposed under different scenarios. For reasons of space, we present briefly the method to solve above models and som
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Wei, Siew Hong, Tan Saw Chin, and Lee Ching Kwang. "Cost-location aware heuristic algorithm for hybrid SDN deployment." Annals of Mathematics and Artificial Intelligence 89, no. 8-9 (2021): 875–97. http://dx.doi.org/10.1007/s10472-021-09750-6.

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Chai, Rong, Xizheng Yang, Chunling Du, and Qianbin Chen. "Network cost optimization-based capacitated controller deployment for SDN." Computer Networks 197 (October 2021): 108326. http://dx.doi.org/10.1016/j.comnet.2021.108326.

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Mehdi, Rouan-Serik, and Kaddour Mejdi. "On optimizing the deployment cost of visual sensor networks." Journal of High Speed Networks 24, no. 1 (2018): 17–30. http://dx.doi.org/10.3233/jhs-170578.

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Ran, Bin, Kwun Yee Kenny Lee, and Haikun Dong. "Cost-Benefit Analysis on Deployment of Automated Highway Systems." Transportation Research Record: Journal of the Transportation Research Board 1588, no. 1 (1997): 137–44. http://dx.doi.org/10.3141/1588-17.

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Abstract:
The optimal ranges of traffic flow and capacity will be determined for selected scenarios, in which different proportions of automated and conventional traffic will operate simultaneously in an automated highway system (AHS). It is found that there will be a substantial increase in the net benefit and the traffic flow and capacity ranges when there is a higher proportion of AHS traffic. The optimal range of capacity refers to the maximum range of traffic volumes, for which there will be some net benefit, which is the difference between the total cost and the total benefit for each flow. The to
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Tashtarian, Farzad, Mohamed Faten Zhani, Bita Fatemipour, and Delaram Yazdani. "CoDeC: A Cost-Effective and Delay-Aware SFC Deployment." IEEE Transactions on Network and Service Management 17, no. 2 (2020): 793–806. http://dx.doi.org/10.1109/tnsm.2019.2949753.

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