A convergent model for distributed processing of Big Sensor Data in urban engineering networks

International Conference on Information Technologies in Business and Industry 2016

计算机科学;经济学;工业技术

Parygin, D.S.^1 ; Finogeev, A.G.^2 ; Kamaev, V.A.^1 ; Finogeev, A.A.^2 ; Gnedkova, E.P.^1 ; Tyukov, A.P.^1

Volgograd State Technical University, 28, Lenina Ave., Volgograd

400131, Russia^1

Penza State University, 40, Krasnaya Str., Penza

440026, Russia^2

关键词: Compute unified device architectures;    Distributed data processing;    Distributed objects;    Distributed processing;    Industrial controllers;    Integral indicators;    Sensor data processing;    Three-tier architecture;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/803/1/012112/pdf
DOI  :  10.1088/1742-6596/803/1/012112

来源: IOP

【 摘 要 】

The problems of development and research of a convergent model of the grid, cloud, fog and mobile computing for analytical Big Sensor Data processing are reviewed. The model is meant to create monitoring systems of spatially distributed objects of urban engineering networks and processes. The proposed approach is the convergence model of the distributed data processing organization. The fog computing model is used for the processing and aggregation of sensor data at the network nodes and/or industrial controllers. The program agents are loaded to perform computing tasks for the primary processing and data aggregation. The grid and the cloud computing models are used for integral indicators mining and accumulating. A computing cluster has a three-tier architecture, which includes the main server at the first level, a cluster of SCADA system servers at the second level, a lot of GPU video cards with the support for the Compute Unified Device Architecture at the third level. The mobile computing model is applied to visualize the results of intellectual analysis with the elements of augmented reality and geo-information technologies. The integrated indicators are transferred to the data center for accumulation in a multidimensional storage for the purpose of data mining and knowledge gaining.