A.V. Smirnov, A.V. Ponomarev, A.M. Kashevnik, T.V. Levashova, N.N. Teslia Human-Computer Cloud for Decision Support: Platform Methodology and Architecture
A.V. Smirnov, A.V. Ponomarev, A.M. Kashevnik, T.V. Levashova, N.N. Teslia Human-Computer Cloud for Decision Support: Platform Methodology and Architecture


Rapid development of cloud services can be seen last years in Russia and other countries. Usually companies prefer to get services in the minor areas as cloud services instead of internal staff. Integration of cloud computing concept with crowd computing allows to provide customers completely new services based on competencies of group of people. The paper presents state-of-the-art in the area of cloud computing for controlling of human resource and sensor networks; requirements for humancomputer cloud systems; methodology and architecture for development of distributed decision support systems based on human-computer cloud.

Ключевые слова:

human-computer cloud, decision support, crowd computing, ontologies.

PP. 30-39.


1. Gavrilov, D. 2016. Russia Cloud Services Market 2016–2020 Forecast and 2015 Vendor Shares. IDC. Available at: (accessed December 1, 2016).
2. Distefano, S., Merlino, G., Puliafito, A. 2012. SaaS: A Framework for Volunteer-Based Sensing Clouds. Parallel and Cloud Computing. 1(2):21-33.
3. Merlino, G., Arkoulis, S., Distefano, S., Papagianni, C., Puliafito, A., Papavassiliou, S. 2016. Mobile Crowdsensing as a Service: A Platform for Applications on Top of Sensing Clouds. Future Generation Computer Systems. 56:623-639.
4. Formisano, C. et al. 2015. The Advantages of IoT and Cloud Applied to Smart Cities. In 3rd International Conference Future Internet of Things and Cloud. Rome. 325-332.
5. Dustdar, S., Bhattacharya, K. 2011. The social compute unit // IEEE Internet Computing. 15(3):64-69.
6. Sengupta, B., Jain, A., Bhattacharya, K., Truong, H.-L., Dustdar, S. 2013. Collective Problem Solving Using Social Compute Units. International Journal of Cooperative Information Systems. 22(4).
7. Mavridis, N. et al. 2013 CLIC: A Framework for Distributed, On-Demand, Human-Machine Cognitive Systems. Available at: (accessed December 1, 2016).
8. Mavridis, N. et al. 2015. Smart buildings and the human-machine cloud. 2015 IEEE 8th GCC Conference and Exhibition. 1-4.
9. Mavridis, N. et al. 2012. The Human-Robot Cloud: Situated collective intelligence on demand // Proceedings - 2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems. 360-365.
10. Schall, D. 2011. A human-centric runtime framework for mixed service-oriented systems // Distributed and Parallel Databases. 29:333-360.
11. Schall, D. 2012. Service-Oriented Crowdsourcing: Architecture, Protocols and Algorithms. SpringerBriefs in Computer Science. Springer New York. 94 p.
12. Schall, D. 2013. Service Oriented Protocols for Human Computation // Handbook of Human Computation. Springer New York. 551-560.
13. Power D.J. 2002. Decision Support Systems: Concepts and Resources for Managers // Greenwood/Quorum Books. Westport, 251 p.
14. Iren, D. et al. 2014. Utilization of synergetic human-machine clouds: A big data cleaning case. 1st International Workshop on CrowdSourcing in Software Engineering. 15–18.
15. Sarasua, C., Simperl, E., Noy, N.F. 2012. CrowdMap: crowdsourcing ontology alignment with microtasks. In Proceedings of the 11th international conference on The Semantic Web. Springer-Verlag, Berlin, Heidelberg, 1:525-541.


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