Research on Resource Allocation based on RBF Neural Network Under Cloud Computing

In cloud computing environment, the resources of network is unknown and the topology is not fixed, so the structure and distribution of resources in whole cloud environment and the actual situation is unpredictable. In this case, the position of computing resources and quality amount is unknown to the data section point. It is unknown to find out the computing resources in the network topology by using RBF neural network algorithm, and select the most appropriate one or a few assigned to the user operation until meet the needs of users. This paper studied resource allocation based on RBF neural network under cloud computing. The results show the RBF neural network under cloud computing is a valid method for resource allocation. Introduction Due to the rapid development of information technology, when network data gradually complicated, the traditional parallel technology has not required for full foot growing human development and scientific research office [1]. As some network model arose at the historic moment, cloud computing as a new parallel computing technology also appeared on the network[2]. As a new Internet, cloud computing is the further development of distributed computing, parallel computing and grid computing based computing model, is also the concept of computer science commercial implementation[3]. Distributed computing tasks will constitute a large number of computer resource pool, so that all applications can root access to computing power, storage space and software services[4]. Cloud computing resources are dynamically scalable and virtualization, through the Internet providing cloud computing is a super computing model based on Internet, and the architecture of a distributed, resource structure of global access, the data center operation in a similar calculation under the environment of Internet are stored in the personal computer, mobile phone and other equipment on the large amount of information and processor resources and work together. Cloud computing services include three levels of service, IaaS, PaaS and SaaS[5]. In recent years, virtualization is the cornerstone of cloud computing, which has also been a hot research field. Virtual tides across all areas of server, storage, network, PC machine etc. The most prominent advantage of virtualization is to save money, the integrated service server, maximize the utilization of resources. Resource Allocation Process By reference to Map/Reduce computing system, each unit in cloud environment can be divided into two roles: Master and Slave. The former configures NameNode and JobTracker node, the latter configures DataNode and TaskTracker node. When resources are allocated by the main scheduling node of the unit (Master JobTracker) and the units under the jurisdiction of each node in the cluster from the task distribution node (slave TaskTracker) jointly completed. Therefore all nodes in the This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Copyright © 2017, the Authors. Published by Atlantis Press. 702 Advances in Computer Science Research (ACSR), volume 76 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)