Paper The following article is Open access

Fusion Application of Big Data and Cloud Computing In the Internet of Things

and

Published under licence by IOP Publishing Ltd
, , Citation Yongjun Qi and Haiyan Wu 2021 J. Phys.: Conf. Ser. 1881 032013 DOI 10.1088/1742-6596/1881/3/032013

1742-6596/1881/3/032013

Abstract

The Internet of Things can be simply understood as the mode of connecting things in the Internet environment. It is mainly the organic combination of computer, Internet technology and other information technology means. At the same time, the organic combination of the Internet of Things, big data, cloud computing and other advanced information thinking and computing methods is the direction of the future smart city construction. In the experiment, due to the characteristics of real-time and massive data of the Internet of Things, the fusion processing of big data cannot be carried out well. Based on the Internet of Things technology, cloud computing technology and fusion algorithm are selected for research. Experimental data show that the number of four types of nodes is set as 30, and the system has 100 nodes in total, and the length of one rotation of the system is 50s. The ordinary Leacha algorithm is used first, and then the improved Leach algorithm is used in the same environment. The experimental results show that there are four different types of nodes in the monitoring environment obtained by the test, and the initial data transmission rates of each node are 60, 90, 110 and 80 respectively. Therefore, the adjusted and improved LEACH algorithm can allocate the required data transmission time according to the different failure levels of the data. If the aging level is higher, the data transmission time of node data will be relatively longer. The improved strategy is in line with the characteristics of the Internet of Things and has the feasibility to complete the experiment.

Export citation and abstract BibTeX RIS

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Please wait… references are loading.
10.1088/1742-6596/1881/3/032013