首页> 外文期刊>Journal of ambient intelligence and humanized computing >Modified adaptive neuro fuzzy inference system based load balancing for virtual machine with security in cloud computing environment
【24h】

Modified adaptive neuro fuzzy inference system based load balancing for virtual machine with security in cloud computing environment

机译:基于修改的自适应神经模糊推理系统的虚拟机具有云计算环境安全性的虚拟机负载平衡

获取原文
获取原文并翻译 | 示例
           

摘要

In a heterogeneous environment, computation over internet is provided by a popular paradigm called cloud computing. In a cloud heterogeneous environment, service providing has various difficulties. Based on service type, difficulties differ. On cloud server, high load is produced by huge amount of request from various users for accessing various applications. Security and balancing of load are major concerns. In cloud environment, NP-hard optimization problem corresponds to load balancing. Dynamic load balancing is handled by various methods. They are designed for enhancing workload distribution process between nodes. Overload avoidance, minimization of average response time, data processing time and optimum utilization of resources are the major aim of those methods. An optimal load balancing technique should improve the turnaround time and maximum CPU utilization. Because of its opaqueness nature of cloud, security is a biggest challenge. According to Forbes, with introduction of General Data Protection Regulation security in cloud continue to be an issue with cloud computing. In the existing system, a fuzzy based hybrid load balancing algorithm is utilized and the results provided are not satisfactory. There are opportunities for improving CPU utilization and turnaround time and in terms of security. In this proposed research work, dynamic load balancing in a heterogeneous environment is handled by Modified Adaptive Neuro Fuzzy Inference System (MANFIS). Parameters of MANFIS are optimized by introducing Fire-fly Algorithm. Security is imposed on user authentication by using the Enhanced Elliptic Curve Cryptography. This is a password-less mechanism to authenticate users. The proposed work attains satisfactory results by proper resource utilization. An experimental result shows that proposed work exhibits better performance by improving the turnaround time and maximizing the CPU utilization and providing secured access to data.
机译:在异构环境中,通过互联网的计算是由一种叫做云计算的流行范式提供。在云异构环境中,服务提供了各种各样的困难。根据服务类型,不同的困难。云服务器,高负载由从各个用户用于访问各种应用的请求大量生产。安全性和负载平衡是主要问题。在云环境中,NP难的优化问题对应于负载均衡。动态负载平衡是通过各种方法来处理。它们是专为提高节点之间的工作负载分配过程。过负荷避免,的平均响应时间最小化,数据处理时间和资源的最佳利用是这些方法的主要目的。最佳的负载均衡技术应该提高周转时间和最大的CPU利用率。由于云计算的其不透明性,安全性是一个最大的挑战。据福布斯介绍与云通用数据保护条例保障仍然是云计算的一个问题。在现有的系统中,基于模糊混合的负载平衡算法,利用与所提供的结果是不能令人满意的。有用于提高CPU利用率和周转时间,并在安全性方面的机会。在此提出的研究工作,动态负载在异构环境中平衡被改进的自适应神经模糊推理系统(MANFIS)处理。 MANFIS的参数通过引入火飞算法进行了优化。安全性是通过使用增强的椭圆曲线密码体制强加给用户的认证。这是一个无密码的机制来认证用户。所提出的工作达到通过适当的资源利用率令人满意的结果。实验结果表明,提出的工作展品通过提高周转时间,并最大限度地提高CPU的利用率,并提供对数据的安全访问,性能更好。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号