Flow data processing paradigm and its application in smart city using a cluster analysis approach

被引：3

作者：

Zou, Xiang ^{[1
,2
]}

Cao, Jinghua ^{[2
,3
]}

Sun, Wei ^{[2
]}

Guo, Quan ^{[2
]}

Wen, Tao ^{[1
,2
]}

机构：

[1] Northeastern Univ, Software Ctr, Shenyang, Liaoning, Peoples R China

[2] Dalian Neusoft Inst Informat, Dalian, Peoples R China

[3] Dalian Maritime Univ, Traff Informat Engn & Control, Dalian, Liaoning, Peoples R China

来源：

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / 02期

关键词：

Big data; Cluster computing; Distributed processing; Spark; Information mining; BIG DATA; CLOUD;

D O I：

10.1007/s10586-018-2839-y

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the digital revolution era the work style of the people changed into real and live communicative systems. Smart cities are evolved from the smart ecosystem with various domains like healthcare, information exchange, transportation, buildings etc., the presence of multiple information system makes these smart cities into a heterogeneous which includes multiple data transfer based on the large no of interconnected sub systems. Since the systems provide data from various terminals to the host the amount of information generates is same as the chances of increasing the challenges and issues in the smart city. These flow data from various sources are handled using cluster computing and this proposed research provides the data flow in the smart city using cluster computing. Apache spark is the tool used to handle the issues in the smart city which is much better than the Hadoop. The results discuss the comparison between the applications in same environment on both the tools.

引用

页码：435 / 444

页数：10

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