Modeling Power Saving Protocols for Multicast Services in 802.11 Wireless LANs

In recent years, a series of power saving (PS) protocols has been proposed in the family of 802.11 standards to save energy for mobile devices. To evaluate their performance, many works have been carried out on testbeds or simulation platforms. However, till now, there is a lack of accurate theoretical models to analyze the performance for these protocols. In an effort to fill this gap, we present a Markov chain-based analytical model in this paper to model these PS protocols, with its focus on multicast services in wireless LANs. The proposed analytical model successfully captures the key characteristic of the power saving system: the data delivery procedure starts periodically at the previously negotiated time, but ends at a rather random time with its distribution depending on the end time of data delivery in the last delivery period as well as the arrival rate of incoming traffic. In the situations with light to moderate traffic loads and under the Poisson assumption for incoming traffic, the amount of data delivered between consecutive delivery periods possesses the Markov property, which builds up our Markov chain-based model. For incoming traffic with long-range dependence (LRD), a multistate Markov-Modulated Poisson Process (MMPP) is used to approximate the traffic, making the analytical model valid in more general cases. We verify our model by simulations on ns2 and the results show that the model can faithfully predict the performance of these PS protocols over a wide variety of testing scenarios.

[1]  Rong Zheng,et al.  Performance analysis of power management policies in wireless networks , 2006, IEEE Transactions on Wireless Communications.

[2]  Arne A. Nilsson,et al.  Queuing Analysis of Power Management in the IEEE 802.11 Based Wireless LANs , 2007, IEEE Transactions on Wireless Communications.

[3]  N. U. Prabhu Foundations of Queueing Theory , 1997 .

[4]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1996, SIGCOMM '96.

[5]  A. M. Abdullah,et al.  Wireless lan medium access control (mac) and physical layer (phy) specifications , 1997 .

[6]  Sally Floyd,et al.  Wide-area traffic: the failure of Poisson modeling , 1994 .

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

[8]  Frank H. P. Fitzek,et al.  Video Traces for Network Performance Evaluation , 2006 .

[9]  Yang Xiao Energy saving mechanism in the IEEE 802.16e wireless MAN , 2005, IEEE Communications Letters.

[10]  Michele Garetto,et al.  Modeling the performance of wireless sensor networks , 2004, IEEE INFOCOM 2004.

[11]  Yong He,et al.  A Novel Scheduled Power Saving Mechanism for 802.11 Wireless LANs , 2009, IEEE Transactions on Mobile Computing.

[12]  N. U. Prabhu,et al.  Queues and Inventories , 1966 .

[13]  Hari Balakrishnan,et al.  Minimizing Energy for Wireless Web Access with Bounded Slowdown , 2002, MobiCom '02.

[14]  Songqing Chen,et al.  PSM-throttling: Minimizing Energy Consumption for Bulk Data Communications in WLANs , 2007, 2007 IEEE International Conference on Network Protocols.

[15]  Daniel P. Heyman,et al.  Modeling multiple IP traffic streams with rate limits , 2003, TNET.

[16]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[17]  Jason Flinn,et al.  Self-Tuning Wireless Network Power Management , 2003, MobiCom '03.

[18]  Arne A. Nilsson,et al.  An M/G/1 queue with bulk service model for power management in wireless LANs , 2005, PE-WASUN '05.

[19]  Bo Friis Nielsen,et al.  A Markovian approach for modeling packet traffic with long-range dependence , 1998, IEEE J. Sel. Areas Commun..

[20]  Yan Zhang,et al.  Performance Modeling of Energy Management Mechanism in IEEE 802.16e Mobile WiMAX , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[21]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[22]  Lixin Gao,et al.  Towards energy efficient VoIP over wireless LANs , 2008, MobiHoc '08.

[23]  Walter Willinger,et al.  Long-range dependence in variable-bit-rate video traffic , 1995, IEEE Trans. Commun..

[24]  Prasant Mohapatra,et al.  Energy Consumption and Conservation in WiFi Based Phones: A Measurement-Based Study , 2007, 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[25]  Luca Benini,et al.  Dynamic power management for portable systems , 2000, MobiCom '00.

[26]  Donald F. Towsley,et al.  Self-similarity and long range dependence on the internet: a second look at the evidence, origins and implications , 2005, Comput. Networks.

[27]  Yan Zhang,et al.  Energy management in the IEEE 802.16e MAC , 2006, IEEE Communications Letters.

[28]  Hui-Nien Hung,et al.  Modeling UMTS Power Saving with Bursty Packet Data Traffic , 2007, IEEE Transactions on Mobile Computing.

[29]  Jun Li,et al.  Scheduled PSM for Minimizing Energy in Wireless LANs , 2007, 2007 IEEE International Conference on Network Protocols.