Adaptive Cross-layer QoS mechanism for cognitive network applications

Given limited network resources, applications, particularly those that support real-time services, must deliver an ambient quality-guaranteed service. Different applications are associated with different Quality of Service (QoS) concerns, as well as different QoS control parameters. This work discusses the QoS specifications of three wireless access technologies, 3G, WiMAX and WiFi, in the design of an ambient QoS mechanism. By exploiting the concepts of Cross-Layer and Cognition, this study integrates these environmental parameters with the sensing of spectral and received signal strength from a cognitive radio paradigm, and proposes the ambient QoS algorithm to select the best access network for services. The proposed QoS mechanism not only meets the requirements of various applications but also guarantees QoS. From the simulation results, the proposed ambient QoS mechanism outperforms existing mechanisms in real-time applications. Comparison with traditional mechanisms reveals that the proposed ambient intelligence reduces average delay time and jitter to 0.157 seconds and 0.086 milliseconds, respectively, for VoIP services, and reduces the packet loss ratio for high-definition video stream by 3.42%.

[1]  Kang G. Shin,et al.  In-band spectrum sensing in cognitive radio networks: energy detection or feature detection? , 2008, MobiCom '08.

[2]  V. S. Abhayawardhana,et al.  A Traffic Model for the IP Multimedia Subsystem (IMS) , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[3]  Zhou Lian-ying Cross-Layer Design in Wireless Network , 2008 .

[4]  Theodore S. Rappaport,et al.  Cross-layer design for wireless networks , 2003, IEEE Commun. Mag..

[5]  Joseph Mitola,et al.  Cognitive Radio An Integrated Agent Architecture for Software Defined Radio , 2000 .

[6]  Dongfeng Yuan,et al.  Cross Layer Opportunistic Scheduling for Multiclass Users in Cognitive Radio Networks , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[7]  R. Good,et al.  An evaluation of transport layer Policy Control in the IP multimedia subsystem , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[8]  Farid Nait-Abdesselam,et al.  802.11 Qos Cross-Layer Protocol Based Propagation Conditions Adaptation , 2007 .

[9]  Fotis Foukalas,et al.  Cross-layer design proposals for wireless mobile networks: a survey and taxonomy , 2008, IEEE Communications Surveys & Tutorials.

[10]  Georgios B. Giannakis,et al.  Cross-layer scheduling with prescribed QoS guarantees in adaptive wireless networks , 2005, IEEE Journal on Selected Areas in Communications.

[11]  Jiann-Liang Chen,et al.  Cross-layer QOS architecture for 4G heterogeneous network services , 2009, 2009 11th International Conference on Advanced Communication Technology.

[12]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[13]  Wenbo Wang,et al.  Spectrum Sensing, Access and Coexistence Testbed for Cognitive Radio using USRP , 2008, 2008 4th IEEE International Conference on Circuits and Systems for Communications.

[14]  H.A. Chan,et al.  Extending the Scope of the Resource Admission Control Subsystem (RACS) in IP Multimedia Subsystem Using Cognitive Radios , 2008, 2008 IEEE Sarnoff Symposium.

[15]  Farid Naït-Abdesselam,et al.  802.11 Qos Cross-Layer Protocol Based Propagation Conditions Adaptation , 2007, 32nd IEEE Conference on Local Computer Networks (LCN 2007).

[16]  Andrea J. Goldsmith,et al.  Design challenges for energy-constrained ad hoc wireless networks , 2002, IEEE Wirel. Commun..