User-motivated topology formation for green communication networks

The energy consumption in communication networks has attracted increasing attentions. However, the survey shows that the network is still idle at some time due to the redundant deployment of networks and varying traffic requirements. Sleeping in the network is an efficient way to save energy since the network in idle state consumes almost 90% of that in busy state. Considering that a centralized sleeping scheduling in communication networks is complicated for implementation, we propose a user-motivated topology formation scheme for green communication networks. Furthermore, we model and analyze our proposal using a potential game. The equilibrium topology formation is proved to exist and the performance of our proposal in terms of price of stability are discussed in the paper. Simulations are also conducted to show the performance of the equilibrium solution, comparing with the optimal sleeping scheduling solution.

[1]  Marco Listanti,et al.  Enabling backbone networks to sleep , 2011, IEEE Network.

[2]  Kevin C. Almeroth,et al.  Green WLANs: On-Demand WLAN Infrastructures , 2009, Mob. Networks Appl..

[3]  L. Chiaraviglio,et al.  Switch-Off Transients in Cellular Access Networks with Sleep Modes , 2011, 2011 IEEE International Conference on Communications Workshops (ICC).

[4]  Daniel F. García,et al.  Analysis and modeling of traffic on a hybrid fiber-coax network , 2004, IEEE Journal on Selected Areas in Communications.

[5]  Marco Listanti,et al.  An Energy Saving Routing Algorithm for a Green OSPF Protocol , 2010, 2010 INFOCOM IEEE Conference on Computer Communications Workshops.

[6]  Dario Rossi,et al.  A Survey of Green Networking Research , 2010, IEEE Communications Surveys & Tutorials.

[7]  Sujata Banerjee,et al.  Energy Aware Network Operations , 2009, IEEE INFOCOM Workshops 2009.

[8]  Sergiu Nedevschi,et al.  Reducing Network Energy Consumption via Sleeping and Rate-Adaptation , 2008, NSDI.

[9]  Michael Franz,et al.  Power reduction techniques for microprocessor systems , 2005, CSUR.

[10]  Roger B. Myerson,et al.  Game theory - Analysis of Conflict , 1991 .