Mobile cloud micro services actor model of monitoring

Y.E. Shishkin1,2, A.V. Skatkov1

 1 Federal State Educational Institution of Higher Education «Sevastopol State University», Russian Federation, Sevastopol, Universitetskaya St., 33

2 Institute of Natural and Technical Systems, Russian Federation, Sevastopol, Lenin St., 28

Email: yourockpro@gmail.com

DOI: 10.33075/2220-5861-2018-4-56-62

UDC 004.9:004.41

Abstract:

     An actor model of the monitoring information system based on cloud services technology with the use of mobile applications to continuously provide decision making support for managing the interaction of mobile IT service agents is proposed. The article is aimed at the development of information technologies special issues in solving problems of detecting anomalous values of critical objects and processes (A-task) using digital filtering and gradient methods in cloud systems.

     As the basic architecture of the developed actor model for the cloud environment it is suggested to use the architecture of the reference cloud infrastructure model, containing additional components essential for the developed system. To achieve this goal, the reference architecture was expanded by the introduction of additional types of mobile actors: a mobile services provider, a network administrator and a cloud crisis manager, which form a multi-agent model of the computing system.

      The developed model meets the requirements of functional flexibility, information security, decentralization, flexibility of the microservice structure, extensibility through the provision of specialized API-interfaces and is aimed at increasing the validity of the decision-making process. At the system-wide level interaction processes and roles of service agents, actors interaction scenarios for monitoring systems of objects and processes in complex systems are described.

     It is established that at the expert estimation for the case under consideration the technology of cloud mobile microservices got the highest summary quality of service metrics.

Keywords: monitoring, mathematical modeling, cloud computing, multi-agent model, detection of anomalies, clustering, critical systems, data mining, mobile application.

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