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Djamba, Kalema Josue. "Cloud-Based Centralizing system for academic history, plagiarism prevention management in Higher Education Institution IN DRC: Benefit, Challenges". British Journal of Multidisciplinary and Advanced Studies 3, n.º 2 (16 de diciembre de 2022): 142–52. http://dx.doi.org/10.37745/bjmas.2022.0062.
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Cloud computing is becoming increasingly popular in the twenty-first century, with demand coming from all sectors of industry, including higher education institutions. In this paper, we address the benefits and limitations of cloud computing in the context of higher education institutions in DRC. Adopting modern cloud computing technology is projected to minimize the cost of IT-based solutions and services, as well as ICT infrastructure. The purpose of this work is to establish a system on cloud based that will enable the centralization and exchange of data on students' academic careers, to prevent plagiarism, to avoid fraud and falsification of transcripts, Share the researches and academic works between the universities to avoid plagiarism. Many challenges must be resolved before cloud computing can be successfully deployed in higher education.
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Karthiga, T. "Cloud Based Video on Demand (VoD) Using DCRP Algorithm". Asian Journal of Computer Science and Technology 1, n.º 1 (5 de mayo de 2012): 107–10. http://dx.doi.org/10.51983/ajcst-2012.1.1.1662.
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The attempt to display media files through internet was started from mid-20th century. Several research works have been reported to provide Video on Demand model in distributed like RMI, SOA and Grid Computing. Internet-based cloud computing is a new computing paradigm aiming to provide agile and scalable resource access in a utility-like fashion. The fundamental question is how to configure the cloud utility to meet the highly dynamic demands of such applications at a modest cost. In this paper, a queueing network based model is used to characterize the viewing behaviors of users in a multichannel VoD application, and derive the server capacities needed to support smooth playback in the channels for two popular streaming models, client-server and P2P.Disk Scheduling is used to allocate separate disks to users. A dynamic cloud resource provisioning algorithm is used in which the derived capacities and instantaneous network statistics as inputs, can effectively support VoD streaming with low cloud utilization cost. Analysis and algorithm design are verified and extensively evaluated by applying large-scale experiments under dynamic realistic settings on a cloud platform.
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Xiangyang, Zhu, Dai Hua, Yi Xun, Yang Geng y Li Xiao. "MUSE: An Efficient and Accurate Verifiable Privacy-Preserving Multikeyword Text Search over Encrypted Cloud Data". Security and Communication Networks 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/1923476.
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With the development of cloud computing, services outsourcing in clouds has become a popular business model. However, due to the fact that data storage and computing are completely outsourced to the cloud service provider, sensitive data of data owners is exposed, which could bring serious privacy disclosure. In addition, some unexpected events, such as software bugs and hardware failure, could cause incomplete or incorrect results returned from clouds. In this paper, we propose an efficient and accurate verifiable privacy-preserving multikeyword text search over encrypted cloud data based on hierarchical agglomerative clustering, which is named MUSE. In order to improve the efficiency of text searching, we proposed a novel index structure, HAC-tree, which is based on a hierarchical agglomerative clustering method and tends to gather the high-relevance documents in clusters. Based on the HAC-tree, a noncandidate pruning depth-first search algorithm is proposed, which can filter the unqualified subtrees and thus accelerate the search process. The secure inner product algorithm is used to encrypted the HAC-tree index and the query vector. Meanwhile, a completeness verification algorithm is given to verify search results. Experiment results demonstrate that the proposed method outperforms the existing works, DMRS and MRSE-HCI, in efficiency and accuracy, respectively.
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Sang, Yongxuan, Junqiang Cheng, Bo Wang y Ming Chen. "A three-stage heuristic task scheduling for optimizing the service level agreement satisfaction in device-edge-cloud cooperative computing". PeerJ Computer Science 8 (18 de enero de 2022): e851. http://dx.doi.org/10.7717/peerj-cs.851.
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Device-edge-cloud cooperative computing is increasingly popular as it can effectively address the problem of the resource scarcity of user devices. It is one of the most challenging issues to improve the resource efficiency by task scheduling in such computing environments. Existing works used limited resources of devices and edge servers in preference, which can lead to not full use of the abundance of cloud resources. This article studies the task scheduling problem to optimize the service level agreement satisfaction in terms of the number of tasks whose hard-deadlines are met for device-edge-cloud cooperative computing. This article first formulates the problem into a binary nonlinear programming, and then proposes a heuristic scheduling method with three stages to solve the problem in polynomial time. The first stage is trying to fully exploit the abundant cloud resources, by pre-scheduling user tasks in the resource priority order of clouds, edge servers, and local devices. In the second stage, the proposed heuristic method reschedules some tasks from edges to devices, to provide more available shared edge resources for other tasks cannot be completed locally, and schedules these tasks to edge servers. At the last stage, our method reschedules as many tasks as possible from clouds to edges or devices, to improve the resource cost. Experiment results show that our method has up to 59% better performance in service level agreement satisfaction without decreasing the resource efficiency, compared with eight of classical methods and state-of-the-art methods.
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Yogi, Manas Kumar, K. Ganga y Devi Bhavani. "Green IOT: Principles, Current Trends, Future Directions". International Journal of Advance Research and Innovation 6, n.º 3 (2018): 27–32. http://dx.doi.org/10.51976/ijari.631805.
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The two trending and popular technologies are Cloud Computing (CC) and the Internet of Things (IoT) are current hot discussions in the field of agriculture and healthcare applications. Motivated by achieving a sustainable world, this paper discusses various technologies and issues regarding green cloud computing and green Internet of Things, further improves the discussion with the reduction in energy consumption of the two techniques (CC and IoT) combination in agriculture and healthcare systems. The history and concept of the hot green information and communications technologies (ICT’s) which are enabling green IoT will be discussed. Green computing introduction first and later focuses on the recent works done regarding the emerging technologies. Finally, lists out the advantages, challenges, and future research directions related to green application design. Our research aims to make green area broad and contribution to sustainable application world.
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Luo, Yingyu. "Semantic Characteristics of the Emerging Popular Construction "Cloud X" in Modern Chinese Language". Transactions on Social Science, Education and Humanities Research 7 (6 de mayo de 2024): 134–43. http://dx.doi.org/10.62051/8njcxg38.
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Accompanied by the development of the Internet and big data, "cloud X" has become a popular construction that is more frequently used in the Internet in recent years. Studying and analyzing the generation mechanism and evolution process of "Cloud X" is of great reference significance for understanding the development of popular words in the new period and the word formation process of popular words. Therefore, this paper analyzes the popular word "cloud X" from the semantic perspective, taking the semantic evolution of "Yun (cloud)" as the entry point. In the process of exploring "Yun (cloud)", this paper will focus on the transformation of the semantic features of "Yun (cloud)", observing the original meaning of "Yun (cloud)",Yun (cloud)" in "cloud computing", and the semantic features of "Yun (cloud)" after "cloud X" has become a construction. By examining the similarities and differences of the semantic features, we can explore the process of "Yun (cloud)" gradually changing from a real word to a class of affixes and the reasons for the change.
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Narawade, Dr Navnath. "Campus Automation Using Cloud Computing". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, n.º 04 (20 de abril de 2024): 1–5. http://dx.doi.org/10.55041/ijsrem31117.
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The project, we propose is “Campus automation”, which is considered a website for a college, the main aim of this project is to change college website content dynamically online and provide a user interface application. The above aim can be established by creating a layout Structural module and each module may have a sub-module. This will provide information about the college campus in which staff, students, and HOD can access this information and will be familiar with the college campus. When campus automation technology is integrated with popular web services it can be utilized securely by an even larger audience. By leveraging the power of cloud computing, the system offers scalability, reliability, and accessibility. It allows users to access the platform from anywhere, at any time, using a web browser, thereby facilitating seamless collaboration and communication among stakeholders. Overall, the proposed Campus Automation System aims to modernize campus management processes, streamline administrative tasks, improve communication, and enhance the overall efficiency of educational institutions. By harnessing the capabilities of cloud computing and the MERN stack, the system promises to deliver a robust, scalable, and user-friendly solution tailored to the needs of modern educational institutions. Key Words: Campus automation, cloud computing, MERN stack, web services
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Wasim Akram, Sk, Dr P. Rajesh y SK Shama. "A review report on challenges and opportunities of edge, fog and cloud computing by employing IoT technology". International Journal of Engineering & Technology 7, n.º 3.29 (24 de agosto de 2018): 263. http://dx.doi.org/10.14419/ijet.v7i3.29.18808.
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In the future, various information and things will be connected to the network. People can now live more convenient and comfortable life where the things and information coordinated together. A world where things are connected to network is referred as IOT (Internet of Things). A huge amount of incomplete data is generated by IOT need to process and responded to very short time. This pose challenge of dealing with big data from many geometrically distributed data sources which are to be managed and processed. To achieve this objective, cloud computing is a treated as one of the popular choice due to its scalability, storage, computational and other capabilities. However current cloud models are not intended to handle the essentials of IOT– volume, variety, and velocity of data. Moreover, as the physical distance between cloud and user increases, transmission latency increases with it, increasing response time and stressing of the user. In addition to that, the processing speed in this environment is largely dependent on the performance of user device. The viable solution to these problems is identified as Edge Computing. The Edge Computing platform works by allowing some application processing to be performed by a small edge server position between the cloud and user, and crucially in a location physically closed to the user. This paper comprehensively presents various research trends that are available in Edge, Fog computing along with a comparison is made among Cloud. Particularly the architecture, characteristics, key technologies, potential applications, security issues and challenges of Edge, Fog and Cloud Computing are discussed and summarized.
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Antonova, Аlfiia y Svitlana Bartkova. "An overview of the advantages of cloud computing and online IDE". Automation of technological and business processes 12, n.º 3 (5 de noviembre de 2020): 47–50. http://dx.doi.org/10.15673/atbp.v12i3.1927.
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The article discusses cloud computing and their impact on the field of software development, and analyzes several issues of developers that can be solved using the online IDE. Usage of cloud computing in the enterprise is not new, and it is not difficult in terms of implementation. That is why it is gaining popularity. First, due to the large number of technologies that allow you to optimize internal processes. Secondly, due to the large number of giant companies and small businesses that use these technologies. Cloud computing is very interesting in financial terms. After all, they allow not spending money on building and supporting the infrastructure. One can also not worry about risks, such as, for example, equipment that affects the system, weather conditions, and so on. It takes on all these moments. Evolving of architectural solutions also increases the impact on cloud technology. A service-oriented approach to software development is becoming increasingly popular. It is less and less possible to see the usual thin client and a single server-monolith. Clients are becoming more complex, attracting part of the business logic, servers are divided into parts, each of which is responsible for a particular part of the subject area, and in some cases may not know about the existence of others. The IDE, which requires developers for programming, also has analogs on the web platform. The online IDE has its advantages for solving some tasks and has become increasingly popular lately. Users of the online IDE can create, run, and customize software that works with a simple browser. The main goal of this study is to determine the main advantages of cloud technologies in the application development process, analyze the segment of online IDE. Based on these data to identify the main situations that determine their use, predict further development, and identify principles and technologies used in this area.
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Carvalho, Juliana, Dario Vieira, Christiano Rodrigues y Fernando Trinta. "LM2K Model for Hosting an Application Based on Microservices in Multi-Cloud". Sensors 23, n.º 9 (2 de mayo de 2023): 4450. http://dx.doi.org/10.3390/s23094450.
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Cloud computing has become a popular delivery model service, offering several advantages. However, there are still challenges that need to be addressed when applying the cloud model to specific scenarios. Two of such challenges involve deploying and executing applications across multiple providers, each comprising several services with similar functionalities and different capabilities. Therefore, dealing with application distributions across various providers can be a complex task for a software architect due to the differing characteristics of the application components. Some works have proposed solutions to address the challenges discussed here, but most of them focus on service providers. To facilitate the decision-making process of software architects, we previously presented PacificClouds, an architecture for managing the deployment and execution of applications based on microservices and distributed in a multi-cloud environment. Therefore, in this work, we focus on the challenges of selecting multiple clouds for PacificClouds and choosing providers that best meet the microservices and software architect requirements. We propose a selection model and three approaches to address various scenarios. We evaluate the performance of the approaches and conduct a comparative analysis of them. The results demonstrate their feasibility regarding performance.
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Sharma, Anjali y K. K. Sharma. "A Novel approach for Load Balancing distribution and storage by using Cloud Computing". E3S Web of Conferences 399 (2023): 04009. http://dx.doi.org/10.1051/e3sconf/202339904009.
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Today’s Cloud computing is the popular technology to complete the work in an efficient way, this provides an important platform to storing data in terms of pay as per use and accessible for everyone by the help of the internet. As we know the use of this technology invites many issues, some are security, failure rate and most critical load balancing. These research papers focus on load balancing and also provide an algorithm to overcome this issue. This paper proposed an idea to minimize the extra burden on the nodes through load shift or load transfer according to the availability or requirement while nodes are overloaded. Here we are discussing many algorithms and their features and find out the proposed joint algorithm which works accordingly as demanded and also offer an idea to overcome the problem of over burdens on nodes by load balancing.
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Yassein, Muneer O. Bani, Yaser M. Khamayseh y Ali M. Hatamleh. "Intelligent Randomize Round Robin for Cloud Computing". International Journal of Cloud Applications and Computing 3, n.º 1 (enero de 2013): 27–33. http://dx.doi.org/10.4018/ijcac.2013010103.
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Cloud computing is a recent scientific revolution in information technology, it is considered as the basic infrastructure of ubiquitous computing. It supports various features including, Internet based computing, and resources sharing. Delivery of services is provided to computers and other devices upon request. In other words, it is a technology based on the internet and central remote servers to maintain data and applications. This technology allows consumers and enterprises to use applications without the need of installing them or allowing access to their personal files at any computer with internet access. Among different users that may access the cloud data center, cloud computing must include job scheduling to organize and monitor these jobs, and to achieve fairness among all users. One of the most popular job scheduling algorithms is Round Robin (RR). This paper proposes an enhancement to the traditional RR, namely Randomized Round Robin (RRR). The enhanced version of RR algorithms is based on random selection for processes that come from different users to achieve near optimal selection of jobs to be served. A simulation has been carried out using CloudSim simulator V 3.0 to test the performance of the proposed scheme in terms of different evaluation metrics such as average throughput and average turnaround time.
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Ahamed, Zaakki, Maher Khemakhem, Fathy Eassa, Fawaz Alsolami y Abdullah S. Al-Malaise Al-Ghamdi. "Technical Study of Deep Learning in Cloud Computing for Accurate Workload Prediction". Electronics 12, n.º 3 (28 de enero de 2023): 650. http://dx.doi.org/10.3390/electronics12030650.
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Proactive resource management in Cloud Services not only maximizes cost effectiveness but also enables issues such as Service Level Agreement (SLA) violations and the provisioning of resources to be overcome. Workload prediction using Deep Learning (DL) is a popular method of inferring complicated multidimensional data of cloud environments to meet this requirement. The overall quality of the model depends on the quality of the data as much as the architecture. Therefore, the data sourced to train the model must be of good quality. However, existing works in this domain have either used a singular data source or have not taken into account the importance of uniformity for unbiased and accurate analysis. This results in the efficacy of DL models suffering. In this paper, we provide a technical analysis of using DL models such as Recurrent Neural Networks (RNN), Multilayer Perception (MLP), Long Short-Term Memory (LSTM), and, Convolutional Neural Networks (CNN) to exploit the time series characteristics of real-world workloads from the Parallel Workloads Archive of the Standard Workload Format (SWF) with the aim of conducting an unbiased analysis. The robustness of these models is evaluated using the Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) error metrics. The findings of these highlight that the LSTM model exhibits the best performance compared to the other models. Additionally, to the best of our knowledge, insights of DL in workload prediction of cloud computing environments is insufficient in the literature. To address these challenges, we provide a comprehensive background on resource management and load prediction using DL. Then, we break down the models, error metrics, and data sources across different bodies of work.
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V Ram Naresh Yadav, B. y P. Anjaiah. "Dynamic Selection of Optimal Cloud Service Provider for Big Data Applications". International Journal of Engineering & Technology 7, n.º 2.24 (25 de abril de 2018): 92. http://dx.doi.org/10.14419/ijet.v7i2.24.12007.
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Big data analytics and Cloud computing are the two most imperative innovations in the current IT industry. In a surprise, these technologies come up together to convey the effective outcomes to various business organizations. However, big data analytics require a huge amount of resources for storage and computation. The storage cost is massively increased on the input amounts of data and requires innovative algorithms to reduce the cost to store the data in a specific data centers in a cloud. In Today’s IT Industry, Cloud Computing has emerged as a popular paradigm to host customer, enterprise data and many other distributed applications. Cloud Service Providers (CSPs) store huge amounts of data and numerous distributed applications with different cost. For example Amazon provides storage services at a fraction of TB/month and each CSP having different Service Level Agreements with different storage offers. Customers are interested in reliable SLAs and it increases the cost since the number of replicas are more. The CSPs are attracting the users for initial storage/put operations and get operations from the cloud becomes hurdle and subsequently increases the cost. CSPs provides these services by maintaining multiple datacenters at multiple locations throughout the world. These datacenters provide distinctive get/put latencies and unit costs for resource reservation and utilization. The way of choosing distinctive CSPs data centers, becomes tricky for cloud users those who are using the distributed application globally i.e. online social networks. In has mainly two challenges. Firstly, allocating the data to different datacenters to satisfy the SLO including the latency. Secondly, how one can reserve the remote resource i.e. memory with less cost. In this paper we have derived a new model to minimize the cost by satisfying the SLOs with integer programming. Additionally, we proposed an algorithm to store the data in a data center by minimizing the cost among different data centers and the computation of cost for put/get latencies. Our simulation works shows that the cost is minimized for resource reservation and utilization among different datacenters.
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Wu, Bin, Xianyi Chen, Zongda Wu, Zhiqiang Zhao, Zhuolin Mei y Caicai Zhang. "Privacy-Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario". Wireless Communications and Mobile Computing 2021 (16 de marzo de 2021): 1–12. http://dx.doi.org/10.1155/2021/6617959.
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The arrival of cloud computing age makes data outsourcing an important and convenient application. More and more individuals and organizations outsource large amounts of graph data to the cloud computing platform (CCP) for the sake of saving cost. As the server on CCP is not completely honest and trustworthy, the outsourcing graph data are usually encrypted before they are sent to CCP. The optimal route finding on graph data is a popular operation which is frequently used in many fields. The optimal route finding with support for semantic search has stronger query capabilities, and a consumer can use similar words of graph vertices as query terms to implement optimal route finding. Due to encrypting the outsourcing graph data before they are sent to CCP, it is not easy for data customers to manipulate and further use the encrypted graph data. In this paper, we present a solution to execute privacy-guarding optimal route finding with support for semantic search on the encrypted graph in the cloud computing scenario (PORF). We designed a scheme by building secure query index to implement optimal route finding with support for semantic search based on searchable encryption idea and stemmer mechanism. We give formal security analysis for our scheme. We also analyze the efficiency of our scheme through the experimental evaluation.
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A. SULTAN, Nagham y Dhuha B. ABDULLAH. "A COMPREHENSIVE STUDY ON BIG DATA FRAMEWORKS". MINAR International Journal of Applied Sciences and Technology 05, n.º 01 (1 de marzo de 2023): 34–48. http://dx.doi.org/10.47832/2717-8234.14.4.
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With the advent of cloud computing technology, the generation of data from various sources has increased during the last few years. The current data processing technology must handle the enormous volumes of newly created data. Therefore, the studies in the literature have concentrated on big data, which has enormous volumes of almost unstructured data. Dealing with such data needs well-designed frameworks that fulfil developers’ needs and fit colourful purposes. Moreover, these frameworks can use for storing, processing, structuring, and analyzing data. The main problem facing cloud computing developers is selecting the most suitable framework for their applications. The literature includes many works on these frameworks. However, there is still a severe gap in providing comprehensive studies on this crucial area of research. Hence, this article presents a novel comprehensive comparison among the most popular frameworks for big data, such as Apache Hadoop, Apache Spark, Apache Flink, Apache Storm, and MongoDB. In addition, the main characteristics of each framework in terms of advantages and drawbacks are also deeply investigated in this article. Our research provides a comprehensive analysis of various metrics related to data processing, including data flow, computational model, overall performance, fault tolerance, scalability, interval processing, language support, latency, and processing speed. To our knowledge, no previous research has conducted a detailed study of all these characteristics simultaneously. Therefore, our study contributes significantly to the understanding of the factors that impact data processing and provides valuable insights for practitioners and researchers in the field
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Tsipis, Athanasios, Asterios Papamichail, George Koufoudakis, Georgios Tsoumanis, Spyros E. Polykalas y Konstantinos Oikonomou. "Latency-Adjustable Cloud/Fog Computing Architecture for Time-Sensitive Environmental Monitoring in Olive Groves". AgriEngineering 2, n.º 1 (6 de marzo de 2020): 175–205. http://dx.doi.org/10.3390/agriengineering2010011.
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The emerging and vast adoption of the Internet of Things (IoT) has sprung a plethora of research works regarding the potential benefits in smart agriculture. A popular implementation involves the deployment of Wireless Sensor Networks (WSNs), which embed low energy consumption sensory nodes to capture the critical environmental parameters prevailing on the farms. However, to manage the ever-increasing volumes of raw data successfully, new approaches must be explored. Under this scope, current work reports on the design and development of an IoT system, having in mind the case of olive groves, which are considered the dominant sector for agricultural activity in the Mediterranean Basin. The system incorporates the cloud/fog computing paradigm to equip the olive growers with a low-cost solution for accurate, reliable, and almost real-time monitoring of their crops. Its core is based on a three-layered network architecture, capable of dynamically balancing the generated load, by pushing cloud-elastic resources to the underlying fog network. As such, the premise of the approach lies in the conforming character of the system that allows for targeted alterations to its operational functionality to meet stringent latency and traffic load environmental monitoring constraints. To evaluate the performance of the proposed architecture, a demo prototype is developed and deployed in the facilities of the Ionian University. Experimental results illustrate the efficiency, flexibility, and scalability of the approach in terms of latency, achieving response time reduction across all platforms, a subject of the utmost importance when it comes to precision agriculture of the future. Moreover, it is shown that the system is capable of dynamic functionality adaptation, to meet network traffic load constraints, achieving high throughput (on average 95%) and addressing potential environmental dangers to olive oil production.
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Fang, Kuo-Chi, Husnu S. Narman, Ibrahim Hussein Mwinyi y Wook-Sung Yoo. "PPHA-Popularity Prediction Based High Data Availability for Multimedia Data Center". International Journal of Interdisciplinary Telecommunications and Networking 11, n.º 1 (enero de 2019): 17–29. http://dx.doi.org/10.4018/ijitn.2019010102.
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Due to the growth of internet-connected devices and extensive data analysis applications in recent years, cloud computing systems are largely utilized. Because of high utilization of cloud storage systems, the demand for data center management has been increased. There are several crucial requirements of data center management, such as increase data availability, enhance durability, and decrease latency. In previous works, a replication technique is mostly used to answer those needs according to consistency requirements. However, most of the works consider full data, popular data, and geo-distance-based replications by considering storage and replication cost. Moreover, the previous data popularity based-techniques rely on the historical and current data access frequencies for replication. In this article, the authors approach this problem from a distinct aspect while developing replication techniques for a multimedia data center management system which can dynamically adapt servers of a data center by considering popularity prediction in each data access location. Therefore, they first label data objects from one to ten to track access frequencies of data objects. Then, they use those data access frequencies from each location to predict the future access frequencies of data objects to determine the replication levels and locations to replicate the data objects, and store the related data objects to close storage servers. To show the efficiency of the proposed methods, the authors conduct an extensive simulation by using real data. The results show that the proposed method has an advantage over the previous works in terms of data availability and increases the data availability up to 50%. The proposed method and related analysis can assist multimedia service providers to enhance their service qualities.
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Akavia, Adi, Max Leibovich, Yehezkel S. Resheff, Roey Ron, Moni Shahar y Margarita Vald. "Privacy-Preserving Decision Trees Training and Prediction". ACM Transactions on Privacy and Security 25, n.º 3 (31 de agosto de 2022): 1–30. http://dx.doi.org/10.1145/3517197.
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In the era of cloud computing and machine learning, data has become a highly valuable resource. Recent history has shown that the benefits brought forth by this data driven culture come at a cost of potential data leakage. Such breaches have a devastating impact on individuals and industry, and lead the community to seek privacy preserving solutions. A promising approach is to utilize Fully Homomorphic Encryption ( \( \mathsf {FHE } \) ) to enable machine learning over encrypted data, thus providing resiliency against information leakage. However, computing over encrypted data incurs a high computational overhead, thus requiring the redesign of algorithms, in an “ \( \mathsf {FHE } \) -friendly” manner, to maintain their practicality. In this work we focus on the ever-popular tree based methods, and propose a new privacy-preserving solution to training and prediction for trees over data encrypted with homomorphic encryption. Our solution employs a low-degree approximation for the step-function together with a lightweight interactive protocol, to replace components of the vanilla algorithm that are costly over encrypted data. Our protocols for decision trees achieve practical usability demonstrated on standard UCI datasets encrypted with fully homomorphic encryption. In addition, the communication complexity of our protocols is independent of the tree size and dataset size in prediction and training, respectively, which significantly improves on prior works. 1
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Malik, Aruna y Sonal Gandhi. "Efficient Pixel-Value Differencing Based Hybrid Steganographic Method Using Modulus Function". International Journal of Information Retrieval Research 10, n.º 4 (octubre de 2020): 51–62. http://dx.doi.org/10.4018/ijirr.2020100104.
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In the era of cloud computing and Big Data, steganographic methods are playing a pivotal role to provide security to sensitive contents. In the steganographic domain, pixel-value differencing (PVD) proposed by Wu and Tsai has been one of the most researched and popular methods as the PVD technique provides good quality stego-image along with high embedding capacity. This article extends the Wu and Tsai's work by proposing a new hybrid steganography scheme which works in two phases to increase the embedding capacity along with stego-image quality. In the first phase, the cover image is preprocessed using a segmentation table to make the image more robust for PVD method. In the second phase, the resultant image is partitioned into 2×1 pixels size blocks in a non-overlapping fashion and then modulus function based scheme is applied in reversible manner. Thus, a significant amount of secret data is embedded into the image. The experimental results prove that the proposed scheme has significantly improved in embedding capacity and quality as compared to the other related PVD-based methods.
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Bu, Hualong, Jing Xia, Qilin Wu y Liping Chen. "Relationship Discovery and Hierarchical Embedding for Web Service Quality Prediction". Computational Intelligence and Neuroscience 2022 (5 de octubre de 2022): 1–16. http://dx.doi.org/10.1155/2022/9240843.
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Web Services Quality Prediction has become a popular research theme in Cloud Computing and the Internet of Things. Graph Convolutional Network (GCN)-based methods are more efficient by aggregating feature information from the local graph neighborhood. Despite the fact that these prior works have demonstrated better prediction performance, they are still challenged as follows: (1) first, the user-service bipartite graph is essentially a heterogeneous graph that contains four kinds of relationships. Previous GCN-based models have only focused on using some of these relationships. Therefore, how to fully mine and use the above relationships is critical to improving the prediction accuracy. (2) After the embedding is obtained from the GCNs, the commonly used similarity calculation methods for downstream prediction need to traverse the data one by one, which is time-consuming. To address these challenges, this work proposes a novel relationship discovery and hierarchical embedding method based on GCNs (named as RDHE), which designs a dual mechanism to represent services and users, respectively, designs a new community discovery method and a fast similarity calculation process, which can fully mine and utilize the relationships in the graph. The results of the experiment on the real data set show that this method greatly improved the accuracy of the web service quality prediction.
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Nguyen, Hoang-Sy, Huynh-Cong Danh, Quoc-Phu Ma, Jakub Mesicek, Jiri Hajnys, Marek Pagac y Jana Petru. "A Bibliometrics Analysis of Medical Internet of Things for Modern Healthcare". Electronics 12, n.º 22 (10 de noviembre de 2023): 4586. http://dx.doi.org/10.3390/electronics12224586.
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The integration of the Internet of Things (IoT) in healthcare has been a popular topic in recent years. This article provides a comprehensive review of the medical IoT for healthcare, emphasizing the state of the art, the enabling technologies to adopt virtuality and reality interaction, and human-centered communication for healthcare (the Metaverse, Extended Reality (XR), blockchain, Artificial Intelligence (AI), robotics). In particular, we assess the number of scientific articles and patents within the period 2015–2022. We then use the two-stage process following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and screening techniques. From that, the relations among the published papers can be visualized. This study examines the insights by evaluating the weights and connections of the nodes in the bibliometric networks. The reviewed papers showcase the rapid growth of IoT-related studies and intellectual property developments, reflecting the burgeoning interest and investment in this domain. As this paper delves into the network of interconnections between these works, it fosters a deeper understanding of the current state of IoT applications in healthcare and uncovers potential research gaps and areas for future exploration. This paper also provides a brief view of the role of IoT in healthcare research and application in combination with emerging technologies such as AI, blockchain, the IoT-enabled Metaverse, robotics, and cloud computing. The article can serve as a guideline and inspiration for both researchers and practitioners in the smart health service sector.
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Makrani, Hosein Mohamamdi, Hossein Sayadi, Najmeh Nazari, Sai Mnoj Pudukotai Dinakarrao, Avesta Sasan, Tinoosh Mohsenin, Setareh Rafatirad y Houman Homayoun. "Adaptive Performance Modeling of Data-intensive Workloads for Resource Provisioning in Virtualized Environment". ACM Transactions on Modeling and Performance Evaluation of Computing Systems 5, n.º 4 (marzo de 2021): 1–24. http://dx.doi.org/10.1145/3442696.
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The processing of data-intensive workloads is a challenging and time-consuming task that often requires massive infrastructure to ensure fast data analysis. The cloud platform is the most popular and powerful scale-out infrastructure to perform big data analytics and eliminate the need to maintain expensive and high-end computing resources at the user side. The performance and the cost of such infrastructure depend on the overall server configuration, such as processor, memory, network, and storage configurations. In addition to the cost of owning or maintaining the hardware, the heterogeneity in the server configuration further expands the selection space, leading to non-convergence. The challenge is further exacerbated by the dependency of the application’s performance on the underlying hardware. Despite an increasing interest in resource provisioning, few works have been done to develop accurate and practical models to proactively predict the performance of data-intensive applications corresponding to the server configuration and provision a cost-optimal configuration online. In this work, through a comprehensive real-system empirical analysis of performance, we address these challenges by introducing ProMLB: a proactive machine-learning-based methodology for resource provisioning. We first characterize diverse types of data-intensive workloads across different types of server architectures. The characterization aids in accurately capture applications’ behavior and train a model for prediction of their performance. Then, ProMLB builds a set of cross-platform performance models for each application. Based on the developed predictive model, ProMLB uses an optimization technique to distinguish close-to-optimal configuration to minimize the product of execution time and cost. Compared to the oracle scheduler, ProMLB achieves 91% accuracy in terms of application-resource matching. On average, ProMLB improves the performance and resource utilization by 42.6% and 41.1%, respectively, compared to baseline scheduler. Moreover, ProMLB improves the performance per cost by 2.5× on average.
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Shendge, Prathamesh, Chaitanya Tale, Sanket Kumawat, Atharva Shitole y Prof S. A. Mhaske. "IOT Based Smart Irrigation System Using GSM". International Journal for Research in Applied Science and Engineering Technology 12, n.º 4 (30 de abril de 2024): 5542–46. http://dx.doi.org/10.22214/ijraset.2024.61251.
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Abstract: Horticulture is the essential division and a huge parcel of Indian populace (almost 58%) is locked in in this segment and associated businesses. Water system is an basic portion of horticulture. Out of the as it were 3% new water accessible to the world, less than 0.5% is accessible in frame of underground water or barometrical dampness, the water that able to utilize. In this circumstance it gets to be basic that an water system strategy which is viable, proficient however doable is utilized. Water system is fundamentally giving water to the crops misleadingly to fulfill their water necessities. It can moreover be utilized to supply supplements to the soil. In a nation like India where most of the ranchers are dependent on the questionable rainstorm, it is fundamental that we make utilize of the foremost proficient strategies that we have. IOT based savvy water system framework is one such procedure where water system can be done without much bother and proficiently, sparing water as well. With everything on smartphones, water system can be done effectively and accessibly from a person ’s versatile, that as well by setting enlightening once and the framework at that point works on its claim. This remote checking of field water system moreover creates a expansive sum of information be that as it may, that can be handled by cloud computing. The focal points of this savvy irrigation system are much more than little issues. With time, there will be more improvements and inquire about within the same, the framework will ended up indeed better
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Changchit, Chuleeporn. "Cloud Computing". International Journal of Information and Communication Technology Education 11, n.º 2 (abril de 2015): 105–17. http://dx.doi.org/10.4018/ijicte.2015040109.
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Cloud computing has become increasingly popular among users and businesses around the world, and education is no exception. Cloud computing can bring an increased number of benefits to an educational setting, not only for its cost effectiveness, but also for the thirst for technology that college students have today, which allows learning and adopting to these new technologies easier for them. This study aims at investigating how cloud computing is perceived by college students and which factors have a tendency to encourage or discourage them to accept the cloud computing as part of their course curriculum. The results in this study reveal that all five factors, perceived usefulness, perceived ease of use, perceived security, perceive speed of access, and perceived cost of usage are factors that play an important role in encouraging students to accept cloud computing as part of their core curriculum.
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Azmi, Nor Nashrah y Azham Hussain. "A Bibliometric Analysis of Dropbox on Scopus Publication". Webology 18, SI02 (13 de enero de 2021): 54–78. http://dx.doi.org/10.14704/web/v18si02/web18012.
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Having a considered that online storage and sharing has becoming an essential to organised, stay focused and get in sync contents for all team members to enlighten way to work. Dropbox is the world‟s first smart work space which bring content of all team members together whilst letting users use the tool they want. Dropbox was initiated in 2008. Based on the usefulness and benefits of Dropbox, there are many kinds of research has been conducted on this topic. Therefore, this paper aims to analyse the scientific literature and report various types of published documents related to the Dropbox based on the data obtained from the Scopus Database by using Perish software to combine the obtained data, VOS Viewer Software to visualize the obtained data and Microsoft Excel to analysis the obtained data analysis. As of 27thApril 2020, there are 506 documents were retrieved and analysed based on the „key words‟ search result thru database. By using standard bibliometric indicators, this paper reports the documents types, source types, publication years, language of publications, subject area, most active source title, keywords, distribution of publications by countries, authorship, text analysis, most active institutions and citation analysis. As the result show that 1) 81% of the articles were published in conferences proceedings and journals articles. 2) 91% of the articles were published in English. 3) There is an increased growth rate of literature on Dropbox since 1985. However, the growth rate is slightly lower from 2016 until 2018. 4) Computer Science is the most popular subject category with respect to the frequency of citations, Halevi, Harnik, Pinkas and Shulman-Peleg (2011)‟s article appears as the most cited paper with an average of 30.44 citations per year. 5) Keywords of the Digital Storage, Cloud Storages and Cloud Computing were the top three keywords used in the database which represented the main areas of about Dropbox. 6) An analysis by country, The United States (US) is first country published most articles about Dropbox with 138 (27.27%).Meanwhile, 6) a total of 446 (88.14%) articles were published as multi-authored with a mean index of 3.55 authors per paper. Therefore, this research reviews of Dropbox published articles and delivers details of growth of Drop box for these35 years. This may help in potential directions or reference for future research.
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Pandey, Jyoti. "Virtualization in Cloud Computing". International Journal for Research in Applied Science and Engineering Technology 11, n.º 11 (30 de noviembre de 2023): 1825–29. http://dx.doi.org/10.22214/ijraset.2023.56955.
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Abstract: Virtualization and cloud computing have been two popular avenues of research over the past few years. They enable users to use applications on internet and intranet. In this research paper, we will discuss about virtualization in cloud computing in detail: its evolution, its need and benefits, challenges its facing nowadays and how to overcome them. We also discuss about cloud management and the future trends in virtualization technology and cloud computing
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Somula, Rama Subbareddy y Sasikala R. "A Survey on Mobile Cloud Computing: Mobile Computing + Cloud Computing (MCC = MC + CC)". Scalable Computing: Practice and Experience 19, n.º 4 (29 de diciembre de 2018): 309–37. http://dx.doi.org/10.12694/scpe.v19i4.1411.
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In recent years, the mobile devices become popular for communication and running advanced real time applications such as face reorganization and online games. Although, mobile devices advanced for providing significant benefits for mobile users. But still, these devices suffers with limited recourses such as computation power, battery and storage space due to the portable size. However, The Cloud Technology overcome the limitations of mobile computing with better performance and recourses. The cloud technology provides enough computing recourses to run mobile applications as storage computing power on cloud platform. Therefore, the novel technology called mobile cloud computing (MCC) is introduced by integrating two technologies (Mobile Computing, Cloud Computing) in order to overcome the limitations(such as Battery life, Storage capacity, Processing capacity) of Mobile Devices by offloading application to recourse rich Remote server. This paper presents an overview of MCC, the advantages of MCC, the related concepts and the technology beyond various offloading frameworks, the architecture of the MCC, Cloudlet technology, security and privacy issues and limitations of mobile cloud computing. Finally, we conclude with feature research directions in MCC.
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Bansal, Alka, Money Sethi, Pooja Rani y Deepika Sharma. "Introduction to Cloud Computing". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, n.º 8 (23 de agosto de 2014): 4747–52. http://dx.doi.org/10.24297/ijct.v13i8.7073.
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The Cloud computing is a fastest growing area in IT industry, computing and research industry. Cloud is a pool of virtualized computer resources .A cloud can support self-redundant, self-recovering and scalable programming models that allow data to recover from any hardware/software failures. With the advent of this new technology, you can access the data online if you have an access to the internet. The intent of this paper is to have a review on cloud computing, how it works, services of cloud computing and its deployment models, benefits and challenges.
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Sajid, Rafat Ul Aman, Sirajul Islam, Abul Bashar Khan Rakib y Amandeep Kaur. "Interpretation on the Google Cloud Platform and Its Wide Cloud Services". International Journal of Security and Privacy in Pervasive Computing 14, n.º 1 (1 de enero de 2022): 1–7. http://dx.doi.org/10.4018/ijsppc.313586.
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Cloud computing is growing wide and first-rate promising technology. There are three forms of cloud computing: infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). There are many cloud service providers. Among these, AWS (Amazon Web Service), Azure (Microsoft Cloud), IBM Cloud, Oracle Cloud, and VMware are immensely popular. In this paper, the authors study the Google Cloud Platform (GCP) and a few principally used popular services. Google Cloud Platform could be a cloud provider; they supply servers and services that are used on-demand and at scale. Google Cloud Platform is the fastest growing cloud service supplier now.
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Narayana Samy, Ganthan, Nurazean Maarop, Mohd Shahidan Abdullah, Sundresan Perum, Sameer Hasan Albakri, Bharanidharan Shanmugam y Premylla Jeremiah. "Digital Forensic Investigation Challenges based on Cloud Computing Characteristics". International Journal of Engineering & Technology 7, n.º 4.15 (7 de octubre de 2018): 7. http://dx.doi.org/10.14419/ijet.v7i4.15.21361.
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One of the most popular computing technologies is cloud computing. There are many benefits in adopting cloud computing such as high-performance, flexibility and availability on-demand, more focused on the business objective and low-cost. However, the characteristics of the cloud computing environment have created many difficulties and challenges for digital forensic investigation processes. Therefore, this paper focuses on the digital forensic investigation challenges based on cloud computing characteristics.
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Yuvaraj, Mayank. "Perception of cloud computing in developing countries". Library Review 65, n.º 1/2 (1 de febrero de 2016): 33–51. http://dx.doi.org/10.1108/lr-02-2015-0015.
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Purpose – The purpose of this paper is to explore the perceptions of librarians engaged in Indian academic libraries towards cloud computing. Design/methodology/approach – A structured questionnaire was used to collect responses from the library professionals engaged in Indian academic libraries. Overall, 339 respondents participated in the survey. Descriptive survey method was used in the study. Findings – The findings of the study reveal that library professionals are using cloud-computing tools in their daily works. They want to adopt cloud computing in the libraries to improve library services and avoid redundancy of works. Ubiquitous availability, economy and the various service layers are the core drivers of its adoption in the libraries. The respondents showed their concern over security and data privacy in cloud. Practical implications – The study establishes the fact that the benefits of cloud computing are inadequate to convince the libraries to migrate from the traditional computing paradigm to the cloud. Technological advancement may not transform the cloud into a mainstream technology. To motivate the expansion of cloud computing adoption, emphasis has to be laid upon collaboration between the cloud service providers supplemented by solid cloud legislations which need to be worked out. Originality/value – The paper provides the perceptions of library professionals in response to the adoption of cloud computing.
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Saini, Dinesh Kumar, Krishan Kumar y Punit Gupta. "Security Issues in IoT and Cloud Computing Service Models with Suggested Solutions". Security and Communication Networks 2022 (12 de abril de 2022): 1–9. http://dx.doi.org/10.1155/2022/4943225.
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Cloud computing is a new model for providing computing services, where computing is delivered as a service over the Internet. Cloud computing is a very popular choice among SMEs because computing services are provided at much lower prices compared to their own IT infrastructure. In the cloud computing model, computing services and data storage are outsourced to cloud service providers. Customers do not have full control over applications and their data. Therefore, an added overhead of security risks comes along, and the security of data becomes the primary concern for cloud customers when considering cloud services. This paper explores various deployment models of cloud computing services and IoT (Internet of Things), figures out associated data security issues with them, and suggests a metric-based solution to assess security provided by cloud services.
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Alzakholi, Omar, Lailan Haji, Hanan Shukur, Rizgar Zebari, Shakir Abas y Mohammad Sadeeq. "Comparison Among Cloud Technologies and Cloud Performance". Journal of Applied Science and Technology Trends 1, n.º 2 (23 de abril de 2020): 40–47. http://dx.doi.org/10.38094/jastt1219.
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The cloud is the best method used for the utilization and organization of data. The cloud provides many resources for us via the internet. There are many technologies used in cloud computing systems; each one uses a different kind of protocols and methods. Many tasks can execute on different servers per second, which cannot execute on their computer. The most popular technologies used in the cloud system are Hadoop, Dryad, and another map reducing framework. Also, there are many tools used to optimize the performance of the cloud system, such as Cap3, HEP, and Cloudburst. This paper reviews in detail the cloud computing system, its used technologies, and the best technologies used with it according to multiple factors and criteria such as the procedure cost, speed cons and pros. Moreover, A comprehensive comparison of the tools used for the utilization of cloud computing systems is presented.
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Yang, Dehua. "A Quantitative Method for Selection of Enterprise Cloud Computing Models". Journal of Systems Science and Information 4, n.º 4 (25 de agosto de 2016): 365–78. http://dx.doi.org/10.21078/jssi-2016-365-14.
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AbstractTargeting at methodological limitations in the decision-making of enterprise cloud computing adoption, this paper analyzes the main influence factors affecting enterprise cloud computing, builds up their hierarchical structures, and works out 8 key influence factors affecting cloud computing models, based on the structural model theory in system engineering. A quantitative method is provided for the selection of optimal or recommended enterprise cloud computing models, in terms of the relationship valuations among key influence factors, cloud computing models, and the factor weights for a specific enterprise.
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Thobejane, Motlokwe, Hope Mogale y Michael B. Esiefarienrhe. "A review on the criteria for adoption of cloud computing in South African Institutions and Business enterprises". International Conference on Intelligent and Innovative Computing Applications 2022 (31 de diciembre de 2022): 153–58. http://dx.doi.org/10.59200/iconic.2022.017.
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Cloud computing has taken over the IT industry. Big enterprises such as Oracle, Microsoft and Amazon have developed world class state of the art products and services for Cloud Computing. These products serve and the needs and power many corporations, business institutions and enterprises across the world. Cloud computing is continuing to growing and attracting more businesses and birthing and transforming industries such as music streaming and online gaming. As we progress and move towards a 5G and become a 4th industrial society more cloud computing products and services will be developed and used. However, there are many issues that arise such as stability, reliability, security and fraud. Addressing these problems introduces complexity towards adopting cloud comput ing for small business enterprises leaving only big enterprises to be able to afford reliable cloud computing products. There are many outstanding works that have been previously published by scholars on cloud computing. This research paper provides a systematic review and a summary of some the outstanding works of scholars recently published and the different criterias used for clouding computing adoption by South African Institutions and Business enterprises.
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Liu, K. y J. Boehm. "CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (20 de agosto de 2015): 553–57. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-553-2015.
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Point cloud data plays an significant role in various geospatial applications as it conveys plentiful information which can be used for different types of analysis. Semantic analysis, which is an important one of them, aims to label points as different categories. In machine learning, the problem is called classification. In addition, processing point data is becoming more and more challenging due to the growing data volume. In this paper, we address point data classification in a big data context. The popular cluster computing framework Apache Spark is used through the experiments and the promising results suggests a great potential of Apache Spark for large-scale point data processing.
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S.Apirajitha, P. "A Study on Data Security In Fog Computing". International Journal of Engineering & Technology 7, n.º 2.19 (17 de abril de 2018): 50. http://dx.doi.org/10.14419/ijet.v7i2.19.15045.
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During the years, Cloud Computing is a popular paradigm which provide access to configurable resources on devices at any time,with on demand. Cloud Computing provides many benefits to enterprises by reducing the cost and allowing them to concentrate on their core business. Apart from this , the Development of Internet of Things came into existence, where the cloud divulge a long distance between users and its environment. Cloud Computing is also referred as heavy computing and dense form of computing power. In Spite of this a new computing has been proposed called Fog Computing also known as Fogging, which overcomes the problem of cloud. Fog computing which majority supports the concepts of Internet of Things(IoT), where many IoT devices are used by users on daily basis which are connected to each other. Fog Computing is also an extended version of cloud computing.
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Almarabeh, Tamara y Yousef Kh Majdalawi. "Cloud Computing of E-learning". Modern Applied Science 12, n.º 8 (8 de julio de 2018): 11. http://dx.doi.org/10.5539/mas.v12n8p11.
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With considerable improvement in Information and Communication Technology (ICT) field, many areas of our lives have been affected, including the learning environmentE-learning is one such inventions and is linked to the use of electronic methods to support the E-learning process, which has become increasingly popular and has become a strong trend due to the enormous benefits it offers to learning environments. However, E-learning systems and its management require huge investments in information technology, and many educational institutions don't have enough budget to afford the cost, therefore cloud computing is the finest solution. It provides an effective mechanism which can allow of building a new mode of E-learning system. This paper, discusses the features of the E-learning system, describes the strategy of Cloud computing, and analyzes the impact of using Cloud Computing in E-learning.
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Gele, Aori. "Study on the Security of the Databases in Cloud Computing Environment". Applied Mechanics and Materials 443 (octubre de 2013): 473–76. http://dx.doi.org/10.4028/www.scientific.net/amm.443.473.
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In the modern information technologies, cloud computing is the most popular. However, the security problems in the application of the cloud databases should be never ignored. In this paper, the characteristics of cloud computing database are first introduced, and then the potential security problems as well as solutions in the application of cloud database are analyzed.
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single, Neeraj. "Efficient Task Allocation Based on Green Computing in Private Cloud". CGC International Journal of Contemporary Technology and Research 2, n.º 1 (30 de diciembre de 2019): 68–76. http://dx.doi.org/10.46860/cgcijctr.2019.12.20.68.
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Cloud computing is a rapidly emerging new paradigm for delivering computing as a service. There are many research issues in cloud computing. Resource allocation is one of the challenging tasks in cloud environment. The main aim of resource allocation to reduce the infrastructure cost associated with companies. The resources offered in the cloud are probably heterogeneous and extremely dynamic. Due to this dynamic access, load balancing of jobs required. Cloud computing resource allocation should be elastic and intelligent, based on application demand and user requirements [1].Green cloud computing is a trend which has become popular with the emergence of internet driven services in every field of life. It refers to the prospective environmental advantages that computer based internet services can guarantee to the environment, by processing huge amount of data and information from collective resources pool.load balancing in an efficient way so that the resource utilization can be maximized and the energy consumption of the data centre could be minimized that can further result in reducing global warming. We have concluded the parameters that should be analysed and improved that will result in reduction of global warming and will increase the profits of cloud provider and the client. Cloud computing resource allocation should be elastic and intelligent, based on application demand and user requirements. Green cloud computing is a trend which has become popular with the emergence of internet driven services in every field of life
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Fernanda, Adwita, Miftahul Huda y Abid Renata Fadri Geovanni. "Application of Learning Cloud Computing Technology (Cloud Computing) to Students in Higher Education". International Journal of Cyber and IT Service Management 3, n.º 1 (29 de marzo de 2023): 32–39. http://dx.doi.org/10.34306/ijcitsm.v3i1.121.
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The development of internet-based computing technology is currently more directed at application systems that are easy to use and do not require a lot of energy. With the existence of cloud computing in the current digital era, it has been felt amid society in everyday life, such as by using email and social media. In general, the purpose of this research is to understand the application of cloud computing for students to calculate data from learning materials under the teacher's material so that later it can help build an effective and efficient learning system. The results of this study can later help students understand the application and function of cloud computing technology, especially in learning. This type of research is a case study from a qualitative descriptive approach by specifying interview instruments and also from questionnaires. The results of the research described above prove that most users use cloud computing applications based on all the conveniences that this application proposes compared to conventional learning systems in the classroom. The facilities provided by this cloud computing application have become popular and attractive to students
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Yang, Shu Guo. "Cloud Computing Security Issues and Mechanisms". Advanced Materials Research 225-226 (abril de 2011): 706–9. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.706.
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Cloud computing is regarded as one of the most enticing technologies and potential silver bullet in the IT industry. Because of open condition and general-purpose nature of cloud, security issue is becoming a bottle neck of rapid development and broad application of cloud computing. Firstly, this paper addresses cloud customers’ significant concerns about and requirements of cloud security. Secondly, cloud security risks and threats posed by the pervasive and ad hoc nature of the cloud are comprehensively analyzed. Finally, some effective and dependable security mechanisms are proposed to lower cloud security risks and meet security requirements of cloud customers. Especially, a novel scheme for integrity and copyright protection of customers’ works in the cloud is presented based on digital watermarking and digital signature.
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Ye, Ming, Jun Zhou, Da Fei Xia y Wei Yao Jia. "Integrated Solving Strategy for Cloud Computing". Applied Mechanics and Materials 44-47 (diciembre de 2010): 3299–303. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3299.
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Cloud computing, which refers to an emerging computing model where machines in large data centers can be used to deliver services in a scalable manner, has become popular for corporations in need of inexpensive, large scale computing. Recently, However, the study of integrated solving strategy is rare. In this paper, we propose a novel integrated solving strategy for cloud computing. For this purpose, we present cloud computing architectures , platforms, and applications to deliver services and meet the needs of their constituents and information and services supported by this integrated solving strategy. At the same time ,this paper also argues that we focused on cloud computing integrated solving stratrgy is an essential part of the government IT environment.
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Safar, Faya y Raddad Al King. "Data Security in Cloud Computing". International Journal of Wireless and Ad Hoc Communication 7, n.º 1 (2023): 50–61. http://dx.doi.org/10.54216/ijwac.070105.
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In recent years, cloud computing was and still is one of the most pragmatic and popular topics of research because of its advantages. Cloud storage allows organizations to store information of service providers at remote sites. However, cloud computing has encountered challenges, notably security issues and scheduling problems, primarily stemming from concerns related to data confidentiality and efficient resource allocation among users. These challenges are inherent to cloud computing, where data and computational resources are shared among multiple users and often hosted on remote servers operated by third-party providers. Hence, our objective is to identify and analyze the challenges associated with cloud computing, with a particular focus on data security. in addition to conduct scientific review and compare multiple recent research studies. The focus will be on identify challenges and advantages of cloud computing and data security when going through various data security measures that are currently employed in cloud computing. eventually we will come up with valid recommendations based on the findings.
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Islam, Shareeful, Stefan Fenz, Edgar Weippl y Christos Kalloniatis. "Migration Goals and Risk Management in Cloud Computing". International Journal of Secure Software Engineering 7, n.º 3 (julio de 2016): 44–73. http://dx.doi.org/10.4018/ijsse.2016070103.
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Organizations are now seriously considering adopting cloud into the existing business context, but migrating data, application and services into cloud doesn't come without substantial risks. These risks are the significant barriers for the wider cloud adoption. There are works that consolidate the existing work on cloud migration and technology. However, there is no secondary study that consolidates the state of the art research and existing practice on risk management in cloud computing. It makes difficult to understand the risks management trend, maturity, and research gaps. This paper investigates the state of the art research and practices relating to risk management in cloud computing and discusses survey results on migration goals and risks. The survey participants are practitioners from both public and private organizations of two different locations, i.e., UK and Malaysia. The authors identify and classify the relevant literature and systematically compare the existing works and survey results. The results show that most of the existing works do not consider the existing organization and business context for the risk assessment. The authors' study results also reveal that risk management in cloud computing research and practice is still not in a mature stage but gradually advancing. Finally, they propose a risk assessment approach and determine the relative importance of the migration goals from two real migration use cases.
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Satish R. Devane, Ratnadeep R. Deshmukh, Ganesh V. Gujar,. "Performance Comparison of Different Load Balancing Algorithms in Cloud Computing". International Journal on Recent and Innovation Trends in Computing and Communication 11, n.º 8s (18 de agosto de 2023): 747–54. http://dx.doi.org/10.17762/ijritcc.v11i8s.9286.
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Cloud computing offers economical, scalable, and instantaneous computing resources to enterprises, allowing them to manage substantial traffic volumes and cater to a multitude of users. But the need for effective load balancing techniques has grown significantly as cloud computing becomes more and more popular. To guarantee the best possible performance, availability, and dependability of apps and services, load balancing is a crucial component of cloud computing. This paper offers a comparative study of different cloud computing technologies and load balancing strategies. We present a performance comparison of software-based load balancing; our analysis compares various service broker policies, such as closest distance, optimized, and reconfigurable, with algorithms such as round robin, throttled, and equally spread. Overall, this paper helps readers understand load balancing mechanisms in cloud computing.
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Namasudra, Suyel. "Data Access Control in the Cloud Computing Environment for Bioinformatics". International Journal of Applied Research in Bioinformatics 11, n.º 1 (enero de 2021): 40–50. http://dx.doi.org/10.4018/ijarb.2021010105.
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Bioinformatics is a branch of science that applies computational science in the biological world. In bioinformatics, large sizes of biological data (genome) are processed in the cloud computing platform. Due to the advantages of cloud computing, such as reduced cost scalability, high performance, unlimited storage and many more, the applications of cloud computing in bioinformatics are increasing exponentially. However, cloud computing has some disadvantages like security, privacy, transferability, etc. Among all these problems, access control is a critical issue in the cloud computing environment. The main objective of this paper is to present many access control models along with their advantages and disadvantages. Moreover, some of the popular cloud-based bioinformatics applications are also introduced for the benefit of researchers.
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Ptak, Aleksandra. "Cloud Computing Systems in Information Society - The European Enterprises towards Technological Advancement - Comparative Rough Set Analysis". Applied Mechanics and Materials 795 (octubre de 2015): 171–78. http://dx.doi.org/10.4028/www.scientific.net/amm.795.171.
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Cloud computing systems usage in enterprises has become very popular in recent years. On the world market there is an increasing number of cloud computing services providers with more or less complex solutions in their offer. Thanks to cloud computing services SMEs have the chance to compete with big corporations. The article presents the usage of cloud computing in the European enterprises in comparison with enterprises from the United States, the use of cloud computing solutions in enterprises of the EU countries in 2014 and prognosis on the use of cloud technologies in Eastern European countries between 2014 and 2017. The aim of the article is to present the current state of cloud systems adoption in European enterprises and to conduct the comparative analysis of the data structure based on the rough sets theory.
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Reema, Syeda. "Cloud Computing as a Solution for Security and Privacy Concerns". International Journal for Research in Applied Science and Engineering Technology 11, n.º 3 (31 de marzo de 2023): 183–87. http://dx.doi.org/10.22214/ijraset.2023.49375.
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Abstract: In recent years, cloud computing has emerged as a popular and cost-effective solution for businesses and individuals to store and manage their data. However, the widespread adoption of cloud computing has raised serious concerns about the security and privacy of sensitive information stored in the cloud. This paper aims to explore the various security and privacy issues associated with cloud computing and examines how the technology can be leveraged to address these concerns. Through a comprehensive review of existing literature and case studies, This paper proposes that cloud computing can be an effective solution for security and privacy concerns in the digital age, provided certain best practices are followed by cloud service providers and users.