作者：
Ramasamy, G.Kamalakkannan, S.Vels Institute of Science
Technology & Advanced Studies Department of Computer Science School of Computing Sciences Pallavaram Chennai India Vels Institute of Science
Technology & Advanced Studies Department of Information Technology School of Computing Sciences Pallavaram Chennai India
Container-based virtualisation has become a cornerstone of cloudcomputing (CC) due to its lightweight and scalable properties when compared to traditional virtual machines. However, it is still difficult to optimisin...
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cloudcomputing, which moves assets from desktop setting to cloud infra-structure—where apps are kept in a "cloud" with massive processing power and nearly infinite database storage—has fundamentally alter...
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In the current competitive environment, businesses are looking at how to lower their IT expenses while simultaneously improving their productivity and flexibility to respond quickly to changes in their operational pro...
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Task scheduling in cloud-fog computing is challenging, particularly for large-scale Bag-of-Jobs (BoJ) applications. To address this complexity, we propose a new task-scheduling model that balances execution speed and ...
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High Frequency Trading (HFT) is one of the most latency sensitive domains in the finance industry. HFT firms rely on ultra-low latency to find opportunities of profit in the market and execute trades at a very high sp...
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As healthcare technology develops, fog computing has been viewed as a paradigm-shifting technology that extends cloud-based services to network edges. The Paper presents a software-based framework intended to maximize...
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The swift expansion of the information technology (IT) industry has led to a surge in compute-intensive and latency-sensitive applications. While cloudcomputing can satiate the demands of such applications, its centr...
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ISBN:
(纸本)9783031751691;9783031751707
The swift expansion of the information technology (IT) industry has led to a surge in compute-intensive and latency-sensitive applications. While cloudcomputing can satiate the demands of such applications, its centralized architecture may cause delays in the execution of tasks. To address such issues, edge computing brings computation closer to data sources. However, limited resources on Internet of things (IoT) devices make local execution quite challenging. Therefore, a pliable approach is to consider task offloading for moving heavy tasks to resource-extensive systems like edge/cloud. Osmotic computing, leveraging edge and cloud resources, aims to enhance IoT services. However, the dynamic nature of IoT, edge, and cloud introduces challenges for task offloading. This paper proposes an offloading algorithm using fuzzy logic to manage uncertainty. Furthermore, we introduce an osmotic decision manager (ODM) that employs fuzzy logic for optimized offloading decisions, considering IoT/edge for latency-sensitive tasks and cloud for latency-tolerant tasks. This algorithm aims to improve overall system performance by efficiently offloading tasks based on their specific requirements and constraints. The proposed algorithm undergoes simulation and assessment with diverse synthetic test cases to demonstrate its efficacy.
cloudcomputing is a game-changer in modern agriculture, providing new forms to access enormous data analysis. In this paper, we investigate how cloudcomputing solutions are being integrated with agricultural practic...
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A computing system that is based on the internet and offers users all resources as on-demand services. Servers, storage, databases, software, and networking are among these on-demand services. Usually, the user must p...
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This paper reviews the latest machine learning and artificial intelligence technology, showcasing its potential to revolutionize the oil and gas industry. Despite the current limitations, the industry is on the brink ...
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