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Journal articles on the topic 'CloudAnalyst'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Shanmugapriya, S., and N. Priya. "Examination of Cloud Simulation Platforms and Implementation of Load Balancing in CloudAnalyst." Indian Journal Of Science And Technology 17, no. 33 (2024): 3424–36. http://dx.doi.org/10.17485/ijst/v17i33.1751.

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Objectives: In light of the growing number of open-source simulation tools for load balancing in cloud computing, the objective of this research is to assess some of the most significant tools before selecting the best one depending on the requirements and goals of the research and also implementing the load balancing approach in the CloudAnalyst tool for dynamic workload (HTTP request) allocation and virtual machine selection in the Infrastructure as a Service (IaaS) heterogeneous cloud environment, with the aim of minimizing the searching time, improving the response time and datacenter proc

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S, Shanmugapriya, and Priya N. "Examination of Cloud Simulation Platforms and Implementation of Load Balancing in CloudAnalyst." Indian Journal of Science and Technology 17, no. 33 (2024): 3424–36. https://doi.org/10.17485/IJST/v17i33.1751.

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Abstract <strong>Objectives:</strong> In light of the growing number of open-source simulation tools for load balancing in cloud computing, the objective of this research is to assess some of the most significant tools before selecting the best one depending on the requirements and goals of the research and also implementing the load balancing approach in the CloudAnalyst tool for dynamic workload (HTTP request) allocation and virtual machine selection in the Infrastructure as a Service (IaaS) heterogeneous cloud environment, with the aim of minimizing the searching time, improving the re

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Patel, Sandip, Ritesh Patel, Hetal Patel, and Seema Vahora. "CloudAnalyst : A Survey of Load Balancing Policies." International Journal of Computer Applications 117, no. 21 (2015): 21–24. http://dx.doi.org/10.5120/20679-3525.

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*Akrati, Sharma Sanjiv Sharma. "A COMPREHENSIVE STUDY OF CLOUDANALYST TOOL AND ITS VARIOUS ALGORITHMS." International Journal OF Engineering Sciences & Management Research 3, no. 6 (2016): 1–7. https://doi.org/10.5281/zenodo.55186.

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In today’s era the main concern of technocrats is to find out the efficient storage space for users. So that they can store any kind or any size of data their without spending lots of money on storage devices. The birth of ‘cloud’ technology is just like boon for users. Anywhere and anytime usage of cloud services are quite beneficial for their users. Various cloud services like SAAS, PAAS, IAAS, DBAAS are taken on rent by the users for their own usage. CloudAnalyst tool based on cloudsim is used for storing data on different data centers. It also worked as a load balancer fo

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., T. Menakadevi. "AN OPTIMUM SERVICE BROKER POLICY FOR SELECTING DATA CENTER IN CLOUDANALYST." International Journal of Research in Engineering and Technology 05, no. 09 (2016): 76–84. http://dx.doi.org/10.15623/ijret.2016.0509011.

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Hassan, Jameela Abdulla, and Fahad Al-Dosari. "Cloudlet Networks Performance Analysis and Improvement." International Research Journal of Electronics and Computer Engineering 3, no. 2 (2017): 22. http://dx.doi.org/10.24178/irjece.2017.3.2.22.

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Abstract— Cloud computing is a Participation in the process and storage operations across distant servers that are shared by many organizations and users and thus be transferred from an application to a service. The organization can share data over the Internet and user can pay only for the resources that will be used only. While cloud computing has disadvantages, there are some advantages for cloudlets have over cloud computing which include: lower network latency and users having full ownership of the data shared. When the need of data to be stored in the servers grows quickly, the workload

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Shahid, Muhammad Asim, Muhammad Mansoor Alam, and Mazliham Mohd Su’ud. "A Systematic Parameter Analysis of Cloud Simulation Tools in Cloud Computing Environments." Applied Sciences 13, no. 15 (2023): 8785. http://dx.doi.org/10.3390/app13158785.

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To provide various applications in various domains, a large-scale cloud data center is required. Cloud computing enables access to nearly infinite computing resources on demand. As cloud computing grows in popularity, researchers in this field must conduct real-world experiments. Configuring and running these tests in an actual cloud environment is costly. Modeling and simulation methods, on the other hand, are acceptable solutions for emulating environments in cloud computing. This research paper reviewed several simulation tools specifically for cloud computing in the literature and presente

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Shanmugapriya, S., and N. Priya. "The Proposed IT-TALB in Infrastructure as a Service Cloud." Indian Journal Of Science And Technology 17, no. 16 (2024): 1654–62. http://dx.doi.org/10.17485/ijst/v17i16.3274.

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Objectives: The purpose of the proposed IT-TALB load balancing algorithm is to dynamically allocate the user's workload to the appropriate virtual machine in an Infrastructure as a Service (IaaS) cloud environment. Methods: This research work includes several key procedures. The user's workloads are distributed to the data center controller (DCC), which in turn uses the ECO-SBP service broker policy to select the efficient data center (DC) for processing the loads. The DCC forwards the load to the selected DC, and the IT-TALB load balancer picks the best Virtual Machine (VM) using CloudAnalyst

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S, Shanmugapriya, and Priya N. "The Proposed IT-TALB in Infrastructure as a Service Cloud." Indian Journal of Science and Technology 17, no. 16 (2024): 1654–62. https://doi.org/10.17485/IJST/v17i16.3274.

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Abstract <strong>Objectives:</strong> The purpose of the proposed IT-TALB load balancing algorithm is to dynamically allocate the user's workload to the appropriate virtual machine in an Infrastructure as a Service (IaaS) cloud environment. <strong>Methods:</strong> This research work includes several key procedures. The user's workloads are distributed to the data center controller (DCC), which in turn uses the ECO-SBP service broker policy to select the efficient data center (DC) for processing the loads. The DCC forwards the load to the selected DC, and the IT-TALB load balan

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Daisy Sharmah. "Integrating Honey Bee Load Balancing Algorithm with Role-Based Access Control in Blockchain Technology to Minimise Response Time in Cloud Computing." Journal of Information Systems Engineering and Management 10, no. 33s (2025): 702–13. https://doi.org/10.52783/jisem.v10i33s.5629.

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The RBAC is considered one of the best security mechanisms used in cloud computing to assign roles and grant specific permissions. The implementation of a RBAC mechanism for load balancing can enhance the overall performance of the server. In this paper, we are focusing on the significance of using the RBAC mechanism in the Honey Bee Load Balancing Algorithm to improve the security of the blockchain consortium system. We have proposed an algorithm using the concept of RBAC with Honey Bee Load Balancing Algorithm in Blockchain to minimize the response time in the Cloud computing. The proposed a

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Elrotub, Mousa, and Abdelouahed Gherbi. "Multi-Cloud Service Brokers for Selecting the Optimal Data Center in Cloud Environment." International Journal of Cloud Applications and Computing 12, no. 1 (2022): 1–19. http://dx.doi.org/10.4018/ijcac.309935.

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Cloud computing provides different services through data centers that are often located in different geographical locations. The users are faced with a wide variety of services to choose from. Also, with the increasing number of serviced applications, overloading might occur on service brokers for balancing and serving the requests. Consequently, maximizing the number of entry points and considering the maximum number of factors that affect the performance for balancing the workload is very important for the quality of service. This paper proposes a model named multi-cloud service brokers (MCS

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Karadimce, Aleksandar. "Adjusting the massively open online courses in cloud computing environment." International scientific journal HORIZONS 1, no. 2014 (2014): 73–82. https://doi.org/10.5281/zenodo.23004.

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Abstract: Massively Open Online Courses (MOOC) is new trending model for delivering learning content online to any person with no limit on attendance for everyone that wishes to attend to a course. Following the MOOC trend there is an expectation that till 2015 there will be more than 6 million unique students worldwide. In order to provide appropriate quality learning user experience for the students we propose how to optimize the cloud computing resources, such as Virtual Machine (VM) distribution per contents to support the MOOC. For this purpose we have used a simulation tool, called Cloud

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Nor, Syazwani Mohd Pakhrudin, Kassim Murizah, and Idris Azlina. "Cloud service analysis using round-robin algorithm for qualityof-service aware task placement for internet of things services." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 3 (2023): 3464–73. https://doi.org/10.11591/ijece.v13i3.pp3464-3473.

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Round-robin (RR) is a process approach to sharing resources that requires each user to get a turn using them in an agreed order in cloud computing. It is suited for time-sharing systems since it automatically reduces the problem of priority inversion, which are low-priority tasks delayed. The time quantum is limited, and only a one-time quantum process is allowed in round-robin scheduling. The objective of this research is to improve the functionality of the current RR method for scheduling actions in the cloud by lowering the average waiting, turnaround, and response time. CloudAnalyst tool w

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Hamdani, Mostefa, and Youcef Aklouf. "Enhanced active VM load balancing algorithm using fuzzy logic and K-means clustering." Multiagent and Grid Systems 17, no. 1 (2021): 59–82. http://dx.doi.org/10.3233/mgs-210343.

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With the rapid development of data and IT technology, cloud computing is gaining more and more attention, and many users are attracted to this paradigm because of the reduction in cost and the dynamic allocation of resources. Load balancing is one of the main challenges in cloud computing system. It redistributes workloads across computing nodes within cloud to minimize computation time, and to improve the use of resources. This paper proposes an enhanced ‘Active VM load balancing algorithm’ based on fuzzy logic and k-means clustering to reduce the data center transfer cost, the total virtual

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Parida, Sasmita, Bibudhendu Pati, Suvendu Nayak, Chhabi Panigrahi, and Tien-Hsiung Weng. "PE-DCA: Penalty elimination based data center allocation technique using guided local search for IaaS cloud." Computer Science and Information Systems, no. 00 (2021): 59. http://dx.doi.org/10.2298/csis210512059p.

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In Cloud computing the user requests are passaged to data centers (DCs) to accommodate resources. It is essential to select the suitable DCs as per the user requests so that other requests should not be penalized in terms of time and cost. The searching strategies consider the execution time rather than the related penalties while searching DCs. In this work, we discuss Penalty Elimination-based DC Allocation (PE-DCA) using Guided Local Search (GLS) mechanism to locate suitable DCs with reduced cost, response time, and processing time. The PE-DCA addresses, computes, and eliminates the penalti

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Mohd Pakhrudin, Nor Syazwani, Murizah Kassim, and Azlina Idris. "Cloud service analysis using round-robin algorithm for quality-of-service aware task placement for internet of things services." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 3 (2023): 3464. http://dx.doi.org/10.11591/ijece.v13i3.pp3464-3473.

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Round-robin (RR) is a process approach to sharing resources that requires each user to get a turn using them in an agreed order in cloud computing. It is suited for time-sharing systems since it automatically reduces the problem of priority inversion, which are low-priority tasks delayed. The time quantum is limited, and only a one-time quantum process is allowed in round-robin scheduling. The objective of this research is to improve the functionality of the current RR method for scheduling actions in the cloud by lowering the average waiting, turnaround, and response time. CloudAnalyst tool w

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17

Elnagar, Noha G., Ghada F. Elkabbany, Amr A. Al-Awamry, and Mohamed B. Abdelhalim. "Simulation and performance assessment of a modified throttled load balancing algorithm in cloud computing environment." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 2087. http://dx.doi.org/10.11591/ijece.v12i2.pp2087-2096.

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<span lang="EN-US">Load balancing is crucial to ensure scalability, reliability, minimize response time, and processing time and maximize resource utilization in cloud computing. However, the load fluctuation accompanied with the distribution of a huge number of requests among a set of virtual machines (VMs) is challenging and needs effective and practical load balancers. In this work, a two listed throttled load balancer (TLT-LB) algorithm is proposed and further simulated using the CloudAnalyst simulator. The TLT-LB algorithm is based on the modification of the conventional TLB algorit

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18

Subramanian, Shanmugapriya, and Priya Natarajan. "Efficient criticality oriented service brokering policy in cloud datacenters." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 2024. http://dx.doi.org/10.11591/ijece.v14i2.pp2024-2034.

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Cloud service provider (CSP) offers a huge number of datacenters and virtual servers to the users for processing their workloads in an infrastructure as a service (IaaS) cloud computing environment. Due to the heterogeneous volume of these resources and the immense number of user workloads arriving simultaneously in the cloud, it is necessary to use an effective load distribution technique for scheduling the resources to achieve high performance and high user satisfaction. Service brokering policy and load balancing techniques are the two crucial areas to be focused on while selecting the data

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Noha, G. Elnagar, F. Elkabbany Ghada, A. Al-Awamry Amr, and B. Abdelhalim Mohamed. "Simulation and performance assessment of a modified throttled load balancing algorithm in cloud computing environment." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 2087–96. https://doi.org/10.11591/ijece.v12i2.pp2087-2096.

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Load balancing is crucial to ensure scalability, reliability, minimize response time, and processing time and maximize resource utilization in cloud computing. However, the load fluctuation accompanied with the distribution of a huge number of requests among a set of virtual machines (VMs) is challenging and needs effective and practical load balancers. In this work, a two listed throttled load balancer (TLT-LB) algorithm is proposed and further simulated using the CloudAnalyst simulator. The TLT-LB algorithm is based on the modification of the conventional throttled load balancer (TLB) algori

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Subramanian, Shanmugapriya, and Priya Natarajan. "Efficient criticality oriented service brokering policy in cloud datacenters." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 2024–34. https://doi.org/10.11591/ijece.v14i2.pp2024-2034.

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Cloud service provider (CSP) offers a huge number of datacenters and virtual servers to the users for processing their workloads in an infrastructure as a service (IaaS) cloud computing environment. Due to the heterogeneous volume of these resources and the immense number of user workloads arriving simultaneously in the cloud, it is necessary to use an effective load distribution technique for scheduling the resources to achieve high performance and high user satisfaction. Service brokering policy and load balancing techniques are the two crucial areas to be focused on while selecting the data

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Ahmad, Abdulnasir Younis, and Asmaa Y. Hammo. "A Comparative Study of the Performance of Load Balancing Algorithms Using Cloud Analyst." Webology 19, no. 1 (2022): 4898–911. http://dx.doi.org/10.14704/web/v19i1/web19328.

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Cloud computing technology has grown and expanded widely in recent years. Cloud computing is a distributed system that may be on physical or virtual machines. Because of the ease of working in the cloud, its ease of use, it's being an interactive model and a highly profitable business model, many users have used it. This led to an increase in the load on it, and thus the overload has become a problem that must be solved. Many algorithms have been proposed to balance the load on cloud. The essential are three: Round robin, Equally Spread Current Execution (ESCE), and Throttled. This research in

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Singhal, Saurabh, Senthil Athithan, Madani Abdu Alomar, et al. "Energy Aware Load Balancing Framework for Smart Grid Using Cloud and Fog Computing." Sensors 23, no. 7 (2023): 3488. http://dx.doi.org/10.3390/s23073488.

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Data centers are producing a lot of data as cloud-based smart grids replace traditional grids. The number of automated systems has increased rapidly, which in turn necessitates the rise of cloud computing. Cloud computing helps enterprises offer services cheaply and efficiently. Despite the challenges of managing resources, longer response plus processing time, and higher energy consumption, more people are using cloud computing. Fog computing extends cloud computing. It adds cloud services that minimize traffic, increase security, and speed up processes. Cloud and fog computing help smart gri

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BOKIYE, Lencho M., and Ilker Ali OZKAN. "HYBRID LOAD BALANCING POLICY TO OPTIMIZE RESOURCE DISTRIBUTION AND RESPONSE TIME IN CLOUD ENVIRONMENT." International Journal of Applied Mathematics Electronics and Computers 10, no. 4 (2022): 101–9. http://dx.doi.org/10.18100/ijamec.1158866.

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Load balancing and task scheduling are the main challenges in Cloud Computing. Existing load balancing algorithms have a drawback in considering the capacity of virtual machines while distributing loads among them. The proposed algorithm works toward solving existing issues, such as fair load distribution, avoiding underloading and overloading, and improving response time. It implements best practices of Throttled load balancing algorithm and Equally Shared Current Execution algorithm. Virtual machines are selected based on the ratio of their bandwidth and load allocation count. Requests are s

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Mon, Nan Kham. "Optimizing Cloud Computing Performance by Integrating the Novel PSBR Service Broker Policy and Load Balancing Algorithms." Journal of Computing Theories and Applications 2, no. 2 (2024): 212–21. http://dx.doi.org/10.62411/jcta.11221.

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As cloud computing advances, organizations' IT infrastructure and application deployment processes are moving to the cloud because cloud computing provides everything as a service over the Internet. The performance of a cloud-based application is based on proper datacenter selection and workload distribution within the selected datacenter. Service broker policies are used for suitable datacenter selection, and load balancing algorithms(LBA) are applied to distribute workloads. This paper is to evaluate the effect of a proposed service broker policy (PSBR) on the performance of cloud-based appl

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Udenwagu, N. E., A. A. Oni, and A. A. Ezenwoke. "Improving Load Balancing in Cloud Computing for Maximum Infrastructure Utilisation Using Multi-Objective Particle Swarm Optimization Algorithm." IOP Conference Series: Earth and Environmental Science 1492, no. 1 (2025): 012005. https://doi.org/10.1088/1755-1315/1492/1/012005.

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Abstract Particle Swarm Optimization (PSO) is a population-based optimization algorithm inspired by the social behaviour of birds or fish schooling. PSO is widely adopted to solve continuous optimization problems due to its fast convergence qualities. It has been deployed efficiently in different domains where optimization is required such as load balancing in data centres for the reduction of carbon footprint, energy consumption, response time, system throughput and energy management towards building a more resilient cloud infrastructure. However, it has a downside which makes it fall into lo

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Harjit, Singh*1 &. Harpreet Kaur2. "OPTIMIZED ENVIRONMENT ALLOCATION FOR STATIC AND DYNAMIC TASKS BASED ON THROTTLE ALGORITHM IN CLOUD." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 7 (2018): 1–11. https://doi.org/10.5281/zenodo.1305803.

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<strong>ABSTRACT</strong> Cloud computing is a developing computing technology that has tend to every entity in the digital organization, it can be personal or government sector. Taking into account the significance of cloud computing, finding new ideas in advancements of cloud computing services is an area of research field. With the initiation of the Cloud, deployment and hosting became easier and cheaper with the use of pay-per-use model offered by Cloud providers. Usually clouds have powerful data centers and data controller to handle large number of users. Cloud is a platform providing dy

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Bukhsh, Rasool, Muhammad Umar Javed, Aisha Fatima, Nadeem Javaid, Muhammad Shafiq, and Jin-Ghoo Choi. "Cost Efficient Real Time Electricity Management Services for Green Community Using Fog." Energies 13, no. 12 (2020): 3164. http://dx.doi.org/10.3390/en13123164.

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The computing devices in data centers of cloud and fog remain in continues running cycle to provide services. The long execution state of large number of computing devices consumes a significant amount of power, which emits an equivalent amount of heat in the environment. The performance of the devices is compromised in heating environment. The high powered cooling systems are installed to cool the data centers. Accordingly, data centers demand high electricity for computing devices and cooling systems. Moreover, in Smart Grid (SG) managing energy consumption to reduce the electricity cost for

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Nguyen, Xuan Phi, Trung Tin Cao, Nguyen Ky Thu Luu, and Cong Hung Tran. "Proposed Load Balancing Algorithm to Reduce Response Time and Processing Time on Cloud Computing." International Journal of Computer Networks & Communications (IJCNC) 10, no. 3 (2018): 87–98. https://doi.org/10.5281/zenodo.1311649.

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ABSTRACT Cloud computing is a new technology that brings new challenges to all organizations around the world. Improving response time for user requests on cloud computing is a critical issue to combat bottlenecks. As for cloud computing, bandwidth to from cloud service providers is a bottleneck. With the rapid development of the scale and number of applications, this access is often threatened by overload. Therefore, this paper our proposed Throttled Modified Algorithm(TMA) for improving the response time of VMs on cloud computing to improve performance for end-user. We have simulated the pro

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Shahid, Muhammad Asim, Rizwan Bin Faiz, Muhammad Mansoor Alam, and M. S. Mazliham. "A Systematic Survey of Simulation Tools for Cloud and Mobile Cloud Computing Paradigm." Journal of Independent Studies and Research Computing 20, no. 1 (2022). http://dx.doi.org/10.31645/jisrc.22.20.1.10.

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Cloud computing (CC) provides fast and on-demand access to virtually unlimited computing resources. Mobile cloud computing (MCC) is a new technology that brings CC and mobile devices together. MCC allows mobile devices access to cloud services. Describe the basic architectures for various MCC applications, as well as a brief comparison of cloud and MCC. As CC becomes more common, researchers in this field may need to conduct real-world experiments in their studies. Configuring and running these experiments in real-world cloud environments is costly. As a consequence, modeling and simulation ap

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"An Analysis on ECSE Load Balancing Algorithm with CDC as a Service Broker Policy in Cloud with Heterogeneous Communication and Device Characteristics." International Journal of Innovative Technology and Exploring Engineering 8, no. 9 (2019): 1631–35. http://dx.doi.org/10.35940/ijitee.i8274.078919.

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Load balancing algorithms and service broker policies plays a crucial role in determining the performance of cloud systems. User response time and data center request servicing time are largely affected by the load balancing algorithms and service broker policies. Several load balancing algorithms and service broker polices exist in the literature to perform the data center allocation and virtual machine allocation for the given set of user requests. In this paper, we investigate the performance of equally spread current execution (ESCE) based load balancing algorithm with closest data center(

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"Performance Analysis of Multi Scale Applications on Cloud Systems." International Journal of Recent Technology and Engineering 8, no. 4 (2019): 11915–21. http://dx.doi.org/10.35940/ijrte.d9765.118419.

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Cloud Computing is the most adoptable technology in use recently where bigger and complex applications are deployed and used on cloud server. Multi scaled applications are such applications which have multiple attributes (data size, number of requests, number of concurrent users etc.) that can cause to poor performance of its application service. For better performance, it needs to be measured, analyzed and optimized using tools, strategies or algorithms. The multi scale application’s performance is measured at end user level, network level and data center level. In this paper, the focus is me

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"Efficient Resource Allocation for Time-Sensitive IoT Applications in Cloud and Fog Environments." International Journal of Recent Technology and Engineering 8, no. 3 (2019): 2356–63. http://dx.doi.org/10.35940/ijrte.b1568.098319.

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Nowadays, with the quick development of internet and cloud technologies, a big number of physical objects are linked to the Internet and every day, more objects are connected to the Internet. It provides great benefits that lead to a significant improvement in the quality of our daily life. Examples include: Smart City, Smart Homes, Autonomous Driving Cars or Airplanes and Health Monitoring Systems. On the other hand, Cloud Computing provides to the IoT systems a series of services such as data computing, processing or storage, analysis and securing. It is estimated that by the year 2025, appr

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