The Optimal Resource Self-configuration Method of Cognitive Network for Survivability Enhancement

  • Jian Wang School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China https://orcid.org/0000-0003-2909-5456
  • Guosheng Zhao School of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China
  • Zhongnan Zhao School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
  • Zhixin Li School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
Keywords: Survivability enhancement, cognitive network, self-configuration, utility function

Abstract

In view of that general lack of intelligence and flexibility of the existing network resource allocation methods in the case of time-varying environments and diversified requirements, an efficient self-configuration method is put forward to optimize the allocation of resources and improve the survivability of system. First of all, the utility function of consumption domain is introduced as an indicator to pre-arrange the priority of user’s QoS, as a result, the utility maximization of the system under resource constraint is obtained. Then, based on this definition, a multidimensional dynamic programming framework is proposed to define and describe the self-configuration process, and the problem model is constructed under certain constraints. Furthermore, the adaptive adjustment and configuration of resources are implemented by determining the priority sequence of user services, finding the optimal resource configuration scheme, and optimizing the time configuration window. Finally, The simulation results show that the proposed method is superior to the traditional resource allocation scheme in terms of system reliability, connectivity, broadband utilization, average response time and transmission rate, which improves the system’s ability to adapt to the environment intelligently and survivability effectively.

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Author Biographies

Jian Wang, School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China

Jian Wang received the PhD degree in computer applications in 2009 from Harbin Engineering University, China. She is currently a professor and doctoral supervisor in school of computer science and technology, Harbin University of Science and Technology. Her research interests include cognitive network, survivability, trusted computing and crowd sensing.

Guosheng Zhao, School of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China

Guosheng Zhao received the PhD degree in computer applications in 2009 from Harbin Engineering University, China. He is currently a professor and master supervisor in school of computer science and information engineering, Harbin Normal University. His research interests include cognitive network, trusted computing and IoT security.

Zhongnan Zhao, School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China

Zhongnan Zhao received the PhD degree in computer applications in 2017 from Harbin University of Science and Technology, China. He is currently an associate professor in school of computer science and technology, Harbin University of Science and Technology. His research interests include security situation awareness, intelligent computing and fault-tolerance.

Zhixin Li, School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China

Zhixin Li is currently a postgraduate in school of computer science and technology, Harbin University of Science and Technology. Her main research interests include survivability, cognitive computing and SDN.

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Published
2020-08-03
Section
Articles