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An Efficient Resource Allocation Mechanism for Time-Sensitive Data in Dew Computing

机译:露水计算中时间敏感数据的高效资源分配机制

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In this fast-growing world, the faster access of data is getting substantial day by day. Nowadays, the users wish autonomy from handling data locally and poverties that the data must become accessible anytime and everywhere. Dew computing composed of cloud and fog makes a cloud-dew architecture which can resolve the disputes. In dew computing, the provision of resources plays a crucial role in determining the resource utilization, performance, and quality of service of the users. The proper allocation of virtual machines (VMs) for a particular time-sensitive task in dew computing is also one of the significant research challenges. We have proposed an efficient resource allocation mechanism for allocating time-sensitive tasks using the proper allocation of VMs in dew computing and also shown the overall task allocation hierarchy between dew-fog-cloud computing in this paper. Our simulation outcomes illustrate that the newly proposed resource allocation mechanisms for time-sensitive data outperform the conventional cloud-fog mechanisms in the iFogSim simulator in terms of network usages, average latency control loop and execution time.
机译:在这个快速增长的世界中,越来越快地访问数据。如今,用户希望能够在本地处理数据方面拥有自主权,并希望能够随时随地访问这些数据的贫困状况。由云和雾组成的露水计算构成了可以解决纠纷的云露架构。在露水计算中,资源的提供在确定用户的资源利用率,性能和服务质量方面起着至关重要的作用。在露水计算中为特定时间敏感任务正确分配虚拟机(VM)也是重大的研究挑战之一。我们提出了一种有效的资源分配机制,用于在露水计算中使用VM的适当分配来分配对时间敏感的任务,并且在本文中还展示了露水-雾云计算之间的总体任务分配层次结构。我们的仿真结果表明,就网络使用率,平均等待时间控制环和执行时间而言,针对时间敏感数据的新提议资源分配机制优于iFogSim模拟器中的传统云雾机制。

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