Adaptive accessibility management in geographic information systems using fog computing

Vyacheslav Burlov, Vitaliy Gryzunov, Dmitriy Sipovich

Abstract


Geographic information systems are integrated with information systems of enterprises and the state, are systems of critical application and work with a large amount of heterogeneous and unstructured data. The volume of data, the number of users and cyberattacks is increasing every year. Ensuring information security, in turn, requires the availability of the system resource. The applied methods of centralized storage and processing of data do not cope with the assigned tasks, cannot ensure the availability of the requested resource accurately and on time, which further leads to a violation of other aspects of information security: integrity and confidentiality. One possible solution to the accessibility problem is the use of foggy computing.

The article proposes: a hierarchical model of a geographic information system using fog computing(FIST – Full Infrastructure of Sources Toolkit). The model includes the levels of software, logical structure, physical structure. Interaction between the levels of the model is formalized. An example of a basic law allowing you to combine individual elements into a pool (fog node) is given. The principle of gradual spreading of tasks in the geographic information system is formulated, the task of adaptive control of the geographic information system performance is posed as a modified task of container packing, the method of pooling the necessary resources into pools is disclosed: computers, communication channels, input / output devices, storage devices. The method (D-FIST – Dynamic Full Infrastructure of Sources Toolkit)includes 3 steps: selection of candidate elements, pools combination, formation of management for change. The convergence and termination of the proposed method is proved. The features of the data with which geographic information systems work, and modern technologies, on the basis of which the proposed method can be implemented, are analyzed.

Full Text:

PDF (Russian)

References


R. J. Winchell, J. Broecker, A. J. Kerwin, B. Eastridge, and M. Crandall, “Comparing geographic information system–based estimates with trauma center registry data to assess the effects of additional trauma centers on system access”, Journal of Trauma and Acute Care Surgery, vol. 89, issue 6, pp. 1131–1135, 2020.

V. A. Kudelkin and V. F. Denisov, “Experience of integration of distributed information systems”, IT standard, no. 1, pp. 24–30, 2017.

O. V. Stoletov, I. A. Chikharev, O. A. Moskalenko, and D. V. Makovskaya, “Geoinformation support of the mediterranean branch of the silk road”, Intercarto. Intergis, part 25, no. 1, pp. 102–113, 2019.

K. Schwab, “Globalization 4.0. New architecture for the fourth industrial revolution”, Eurasian integration: economics, law, politics, № 1 (27), pp. 79–84, 2019.

M. O. Kolbanev, I. I. Palkin, and T. M. Tatarnikova, “The challenges of the digital economy”, Hydrometeorology and ecology, no. 5, pp. 156–167, 2020.

Geographical information systems. Terms and definitions, GOST R 52438-2005, 2018.

V. V. Gryzunov and A. O. Nesterova, “Survivable structure of network of meteorological complexes of transport and logistics systems “industry 4.0”, Gidrometeorologija i jekologija, no. 59, pp. 111–123, 2020.

J. Zhang, L. Xu, Y. Zhang, G. Liu, L. Zhao, and Y. Wang, “An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS”, ISPRS International Journal of Geo-Information, vol. 8, no. 9, pp. 392, 2019.

C. Quinde, D. Guillermo, L. Siguenza-Guzman, D. Orellana, and P. A. Pesántez-Cabrera, “Software Architecture Proposal for a Data Platform on Active Mobility and Urban Environment”, in 2020 Conference on Information and Communication Technologies of Ecuador (TICEC 2020), pp. 501–515.

S. Sumith Satheendran and S. Smitha Chandran, “Development of a Cloud Based Spatial Information System for Karunagappally Municipality, Kerala, The God’s Own Country”, Journal of Emerging Technologies and Innovative Research (JETIR), vol. 7, issue 7, pp. 2304–2310, 2020.

H. Broesamle et al., “Assessment of solar electricity potentials in North Africa based on satellite data and a geographic information system”, Solar Energy, vol. 70, no 1, pp. 1–12, 2001.

Official web site of Data Center Companies. Available: https://www.datacenters.com/directory/companies.

Ieee 1934-2018-ieee standard for adoption of open fog reference architecture for fog computing, IEEE Standard Association et al., 2018.

E. Panidi, “Fog computing perspectives in connection with the current geospatial standards”, International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, vol. 42, pp. 171–174, 2017.

J. Das, A. Mukherjee, S. K. Ghosh, and R. Buyya, “Spatio-Fog: A green and timeliness-oriented fog computing model for geospatial query resolution”, Simulation Modelling Practice and Theory, vol. 100, pp. 102043, 2020.

A. Kapsalis, P. Kasnesis, I. S. Venieris, D. I. Kaklamani, and C. Z. Patrikakis, “A cooperative fog approach for effective workload balancing”, IEEE Cloud Computing, 4 (2), pp. 36–45, 2017. doi:10.1109/MCC.2017.25.

A. Yousefpour, G. Ishigaki, and J. P. Jue, “Fog Computing: Towards Minimizing Delay in the Internet of Things”, in Proceedings - 2017 IEEE 1st International Conference on Edge Computing, EDGE 2017, pp. 17–24.

R. Beraldi et al., “Distributed load balancing for heterogeneous fog computing infrastructures in smart cities”, Pervasive and Mobile Computing, pp. 101221, 2020.

V. V. Gryzunov, “Conceptual model of geoinformation system adaptive control under conditions of destabilization”, Information security problems. Computer systems, no. 1 (45), pp. 102–108, 2021.

M. Mukherjee, R. Matam, L. Shu, L. Maglaras, M. A. Ferrag, N. Choudhury, and V. Kumar, “Security and privacy in fog computing: Challenges”, IEEE Access, vol. 5, pp. 19293–19304, 2017.

V. V. Gryzunov, “The analytical model of the whole information system”, Doklady Tomskogo gosudarstvennogo universiteta sistem upravlenija i radiojelektroniki, no. 1-1 (19), pp. 226–230, 2009.

V. G. Burlov and A. M. Grobickaja, “Construction management in terms of indicator of the successfuly fulfilled production task”, Inzhenerno-stroitel'nyj zhurnal, no. 3, pp. 77–91, 2016.

R. M. Yusupov and others, “Elements of the theory of testing and control of technical systems”. Leningrad: Energy. Leningrad. unit,1978, 191 p.

Y. Sun, F. Lin, and H. Xu, “Multi-objective optimization of resource scheduling in fog computing using an improved NSGA-II”, Wireless Personal Communications, vol. 102, no. 2, pp. 1369–1385, 2018.

M. Aazam, S. Zeadally, and K. A. Harras, “Offloading in fog computing for IoT: Review, enabling technologies, and research opportunities”, Future Generation Computer Systems, vol. 87, pp. 278–289, 2018.

V. V. Gryzunov, “The estimation of the survivability of heterogeneous structure”, Vestnik SibGUTI, no. 1, pp. 28–35, 2011.

V. V. Gryzunov, “Problem solving method of measuring and calculating tasks under conditions of data computing system degradation”, Vestnik SibGUTI, no. 1, pp. 35–44, 2015.

Federal law No. 405-FZ of December 2, 2019 "On amendments to certain legislative acts of the Russian Federation".

S. N. Leonenkov, “Target optimization of a supercomputer task flow”, Vychislitel'nye metody i programmirovanie, vol. 20, no. 3, pp. 199–210, 2019.

V. V. Gryzunov and D. A. Ukrainceva, “Technical features of the investigation of computer crimes”, in Information security of russian regions (ISRR-2019): XI St. Petersburg interregional conference, SPb., 2019, pp. 172–173.

“Architecture choices for big data processing”. Available: www.dataved.ru/2014/06/big-data-architecture.html.

The cloud data analytics platform (Teradata). Available: www.teradata.ru/Products/Software/Vantage/Analyst.

Z. Zhang H. Sun, Z. Liu, C. Xu, and L. Wang, “Dart: A geographic information system on hadoop”, in 2015 IEEE 8th International Conference on Cloud Computing, pp. 90–97.

R. K. Lenka, R. K. Barik, N. Gupta, S. M. Ali, A. Rath, and H. Dubey, “Comparative analysis of SpatialHadoop and GeoSpark for geospatial big data analytics”, in 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), pp. 484–488.


Refbacks

  • There are currently no refbacks.


Abava  Кибербезопасность MoNeTec 2024

ISSN: 2307-8162