Analyzing Peer Specific Power Saving in IEEE 802.11s Through Queuing Petri Nets: Some Insights and Future Research Directions

The IEEE 802.11s wireless mesh networking standard supports power save mode where a mesh station can switch from the awake state to the doze state when there is no data to transmit. In the standard, the doze state is peer specific and has two different modes of operations - light sleep mode and deep sleep mode. This paper analytically evaluates the performance of a mesh basic service set under the operation of different power save modes, with the help of a queuing Petri net modeling. The analytical model gives several insights of the power save mode operations, which are further validated using simulation results as well as results from a practical mesh networking testbed. Our analysis reveals that there exists interesting performance tradeoffs among light sleep mode and deep sleep mode, that can be explored to design an efficient power profile for mesh networks.

[1]  P. Kumar,et al.  Capacity of Ad Hoc Wireless Networks , 2002 .

[2]  Mohsen Guizani,et al.  Home M2M networks: Architectures, standards, and QoS improvement , 2011, IEEE Communications Magazine.

[3]  Yu-Chee Tseng,et al.  Power-saving protocols for IEEE 802.11-based multi-hop ad hoc networks , 2003, Comput. Networks.

[4]  Jun Li,et al.  The IEEE 802.11 Power Saving Mechanism: An Experimental Study , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[5]  Sunghyun Choi,et al.  Performance Analysis of Sleep Mode Operation in IEEE 802.16e Mobile Broadband Wireless Access Systems , 2006, 2006 IEEE 63rd Vehicular Technology Conference.

[6]  Samuel Kounev,et al.  QPME: a performance modeling tool based on queueing Petri Nets , 2009, PERV.

[7]  Hari Balakrishnan,et al.  Cabernet: vehicular content delivery using WiFi , 2008, MobiCom '08.

[8]  C.C. Reinwand Municipal Broadband - The Evolution of Next Generation Wireless Networks , 2007, 2007 IEEE Radio and Wireless Symposium.

[9]  Marco Porsch,et al.  A Testbed Evaluation of the Scalability of IEEE 802.11s Light Sleep Mode , 2013, EUNICE.

[10]  Bong Dae Choi,et al.  Performance analysis of power save mode in IEEE 802.11 infrastructure WLAN , 2008, 2008 International Conference on Telecommunications.

[11]  Samuel Kounev,et al.  SimQPN - A tool and methodology for analyzing queueing Petri net models by means of simulation , 2006, Perform. Evaluation.

[12]  Riku Jäntti,et al.  Performance Analysis of the IEEE 802.11s PSM , 2012, J. Comput. Networks Commun..

[13]  Sandip Chakraborty,et al.  Performance modeling and evaluation of IEEE 802.11 IBSS power save mode , 2014, Ad Hoc Networks.

[14]  Ian F. Akyildiz,et al.  A survey on wireless mesh networks , 2005, IEEE Communications Magazine.

[15]  David Wetherall,et al.  Predictable 802.11 packet delivery from wireless channel measurements , 2010, SIGCOMM '10.

[16]  Sandip Chakraborty,et al.  Performance analysis of IEEE 802.11 IBSS power save mode using a discrete-time markov model , 2012, SAC '12.

[17]  F. Richard Yu,et al.  IEEE 802.11 DCF PSM Model and a Novel Downlink Access Scheme , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[18]  George F. Riley,et al.  The ns-3 Network Simulator , 2010, Modeling and Tools for Network Simulation.

[19]  Falko Bause,et al.  Queueing Petri Nets , 1996 .

[20]  Nitin H. Vaidya,et al.  Improving IEEE 802.11 power saving mechanism , 2008, Wirel. Networks.

[21]  Nei Kato,et al.  Relay-by-smartphone: realizing multihop device-to-device communications , 2014, IEEE Communications Magazine.

[22]  Marco Porsch,et al.  A Testbed Analysis of the Effects of IEEE 802.11s Power Save on Mesh Link Performance , 2012, EUNICE.