ZTE Communications ›› 2011, Vol. 9 ›› Issue (2): 44-48.

• Research Paper • Previous Articles     Next Articles

Self-Adaptive QoS Control in Cognitive Networks That Is Based on Service Awareness

Chengjie Gu, Shunyi Zhang, and Yanfei Sun   

  1. Institute of Information Network Technology, Nanjing University of Posts and Telecommunications
  • Online:2011-06-25 Published:2011-06-25
  • About author:Chengjie Gu (jackiee.gu@gmail.com) is a Ph.D candidate at Nanjing University of Posts and Telecommunications. He is currently researching communication networks, IP technologies, distributed network management, and cognitive networks.

    Shunyi Zhang (dirzsy@njupt.edu.cn) is a professor at Nanjing University of Posts and Telecommunications, a Ph.D tutor, a member of China Communication Academy and the director of the IP Application and Value-added Telecommunication Technique Commission. He is also the associate director of the China Electronic Academy, and director of Jiangsu Province Engineering Research Center of Telecommunication and Network Technology. He is currently researching the computer network communication, communication network and IP technology.

    Yanfei Sun (sunyanfei@njupt.edu.cn) is an associate professor at Nanjing University of Posts and Telecommunications. He is also a master’s tutor. He is currently researching the network performance monitoring and optimization, QoS control and management, and multimedia network communication.
  • Supported by:
    This work was funded by the National High Technology Research and Development Planning ( “863”Project) under Grant No. 2006AA01Z232, 2009AA01Z212, 2009AA01Z202, and the National Natural Science Foundation Project under Grant No. 61003237.

Abstract: This paper analyzes a self-adaptive Quality of Service (QoS) control architecture for cognitive networks (CNs) that is based on intelligent service awareness. In this architecture, packets can be identified and classified using an intelligent service-aware classification model. Drawing on Control Theory, network traffic can be controlled with a self-adaptive QoS control mechanism that has side-road collaboration. In this architecture, perception, analysis, correlation, feedback, decision making, allocation, and implementation QoS mechanisms are created automatically. These mechanisms can adjust resource allocation, adapt to a changeable network environment, optimize end-to-end performance of the network, and ensure QoS.

Key words: cognitive network, service-awareness, self-adaptive control, QoS