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International Journal of Big Data Intelligent Technology, 2020, 1(1); doi: 10.38007/IJBDIT.2020.010102.

Data Center Resource Allocation Strategy Based on Edge Computing

Author(s)

Qiang Long

Corresponding Author:
Qiang Long
Affiliation(s)

Heilongjiang University, Harbin, China

Abstract

In recent years, Mobile Edge Computing (MEC) technology can support resource-intensive applications in edge networks. With the expansion of cloud computing service models in edge networks, it provides users with real-time services, which solves traditional cloud computing the high latency barrier when the center provides services is a new technology with very broad application prospects. This article aims to study the data center resource allocation strategy of edge computing. This paper designs an edge server experiment to make full use of the edge computing model to mine the computing power of the edge terminal in the network, perform some or all calculations at the edge terminal, process private data, and reduce the computing, transmission bandwidth load and energy consumption of the cloud computing center. The concept of edge computing was proposed only after the development of cloud computing technology for a period of time. At present, edge computing and cloud computing technology are complementary to each other. As the technical basis for building an interconnected environment of all things, this paper studies in detail the use of mobile edge computing technology to provide users with real-time application services The architecture of this service model analyzes the challenges faced by the service model and proposes an effective solution, which improves the efficiency of resource allocation by nearly 45.73%.

Keywords

Edge Computing, Minimum Access Delay, Network Reliability, Resource Allocation

Cite This Paper

Qiang Long. Data Center Resource Allocation Strategy Based on Edge Computing. International Journal of Big Data Intelligent Technology (2020), Vol. 1, Issue 1: 18-34. https://doi.org/10.38007/IJBDIT.2020.010102.

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