دانلود مقاله گسترش سکوی رایانش ابری مبتنی بر شبکه عصبی
چکیده
مقدمه
توسعه پلت فرم رایانش ابری مبتنی بر شبکه عصبی
تجزیه و تحلیل تجربی
نتیجه گیری
منابع
Abstract
Introduction
Development of Cloud Computing Platform Based on Neural Network
Experimental Analysi
Conclusion
Data Availability
Conflicts of Interest
References
چکیده
این مقاله با هدف مشکلات ذخیره‌سازی داده‌های کوچک، توان عملیاتی پلتفرم کوچک و مصرف انرژی بالا در توسعه پلت‌فرم‌های رایانش ابری موجود، یک پلت فرم رایانش ابری مبتنی بر شبکه‌های عصبی را توسعه می‌دهد. در طراحی پلتفرم ابتدا کارکردهای بستر محاسبات ابری مشخص می شود. بر اساس طراحی عملکرد، سخت افزار و نرم افزار بستر محاسبات ابری طراحی شده است. در طراحی سخت افزار، توپولوژی پلتفرم رایانش ابری، ماژول اکتساب داده، میکروکامپیوتر تک تراشه، استقرار گره و انواع دیگر سخت افزار کاربردی طراحی شده است. در طراحی نرم افزار، شبکه عصبی عمدتاً برای حذف افزونگی داده های ذخیره شده در یک پلتفرم رایانش ابری، طراحی جریان پردازش داده پلتفرم رایانش ابری و تکمیل توسعه پلتفرم رایانش ابری مبتنی بر شبکه عصبی استفاده می شود. نتایج تجربی نشان می‌دهد که پلتفرم محاسبات ابری مبتنی بر شبکه عصبی طراحی‌شده در این مقاله سریع‌تر اجرا می‌شود، توان عملیاتی داده‌های پلتفرم به طور قابل‌توجهی بهبود یافته است و مصرف انرژی عملیاتی پلتفرم پایین است.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
Aiming at the problems of small data storage, small platform throughput, and high energy consumption in the development of existing cloud computing platforms, this paper develops a cloud computing platform based on neural networks. In the design of the platform, firstly, the functions of the cloud computing platform are determined. Based on the function design, the hardware and software of the cloud computing platform are designed. In the hardware design, the topology of cloud computing platform, data acquisition module, single-chip microcomputer, node deployment, and other types of functional hardware are designed. In the software design, the neural network is mainly used to remove the redundancy of data stored in a cloud computing platform, design the data processing flow of cloud computing platform, and complete the development of cloud computing platform based on neural network. The experimental results show that the cloud computing platform based on the neural network designed in this paper runs faster, the throughput of platform data has been significantly improved, and the operating energy consumption of the platform is low.
Introduction
With the development of information technology, the Internet has become an indispensable part of people’s life. People cannot get information, publish information, and exchange information without the Internet. In this context, the computing that consumes the most CPU is gradually transferred to the processing of information [1]. The computing power that a single processor can provide is close to the limit. This makes major manufacturers face great challenges; they need to mine useful information from TB and even Pb level data and process this information quickly and efficiently [2].
Cloud computing technology is a business model rising in recent years [3]. It combines the characteristics of distributed computing, parallel computing, and grid computing and uses the computing cluster built by a large number of ordinary servers and the storage cluster built by a large number of low-cost devices to provide users with scalable computing resources and storage space. Cloud computing technology creates a new application mode, which makes the computing power circulate through the network and provide computing power services comparable to supercomputers through combination, and gradually develops into a network application trend. The deployment and application of supercomputer applications face a very high threshold due to the very expensive hardware investment, while cloud computing combines ordinary personal computers and standard servers into computer clusters through the Internet, becoming a low-cost solution for supercomputing services [4]. In the cloud computing environment, both the number of users and the number of resources are very large. Without a rigorous regulatory mechanism, it is easy to be chaotic and out of order. In addition, China’s laws and regulations on intellectual property are not perfect, piracy is very serious, and the intellectual property rights of resource builders are vulnerable to infringement. In order to ensure the smooth progress of resource sharing in the cloud environment, it is necessary to establish a rigorous regulatory mechanism to supervise the sharing behavior of users. Establishing a professional organization with organizational ability and supervision is a better solution [5].
Results and analyses
This study develops a cloud computing platform based on neural networks to overcome the challenges of tiny data storage, low platform throughput, and high energy consumption in the development of existing cloud computing platforms. The functions of the cloud computing platform are first identified during platform design. The hardware and software of the cloud computing platform are created based on the function design. The structure of the cloud computing platform, data acquisition module, single-chip microcomputer, node deployment, and other types of functional hardware are designed in the hardware design phase. The neural network is mostly used in software design to reduce redundancy from data stored in a cloud computing platform, design the cloud computing platform’s data processing flow, and finish the construction of a cloud computing platform based on a neural network.