Addressing the energy-delay tradeoff in wireless networks with load-proportional energy usage

Hardware techniques such as dynamic voltage and frequency scaling may be used to reduce the energy consumption of network interfaces and achieve load-proportional energy usage. These techniques slow down the operation of the hardware and thus their power savings come at the cost of increased packet delays. This paper presents a methodology to address the energy-delay tradeoff while achieving load-proportional energy usage in wireless networks. The proposed system uses a pipelined implementation of the functional blocks of the medium access control (MAC) layer. Each functional block has its own job queue and is treated as an individual system with an independent clock. The clock frequency of each functional block is dynamically selected based on the length of its job queue. While the pipelined implementation reduces the MAC layer processing delays, the use of queue-length based frequency scaling provides load-proportional energy usage and enhances the overall stability of the system. The performance of the proposed system has been verified through extensive simulations.

[1]  Yuke Wang,et al.  Optimized software implementation of a full-rate IEEE 802.11a compliant digital baseband transmitter on a digital signal processor , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[2]  Biplab Sikdar,et al.  A study of the environmental impact of wired and wireless local area network access , 2013, IEEE Transactions on Consumer Electronics.

[3]  Jan M. Rabaey,et al.  Digital Integrated Circuits , 2003 .

[4]  Raffaele Bolla,et al.  Dynamic voltage and frequency scaling in parallel network processors , 2012, 2012 IEEE 13th International Conference on High Performance Switching and Routing.

[5]  Chita R. Das,et al.  A case for dynamic frequency tuning in on-chip networks , 2009, 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

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

[7]  Gerhard Fettweis,et al.  Power consumption modeling of different base station types in heterogeneous cellular networks , 2010, 2010 Future Network & Mobile Summit.

[8]  Suresh Singh,et al.  A feasibility study for power management in LAN switches , 2004, Proceedings of the 12th IEEE International Conference on Network Protocols, 2004. ICNP 2004..

[9]  Sin-Chong Park,et al.  A Multi-Processor NoC platform applied on the 802.11i TKIP cryptosystem , 2008, 2008 Asia and South Pacific Design Automation Conference.

[10]  Ali Afzali-Kusha,et al.  Dynamic Voltage and Frequency Scheduling for Embedded Processors Considering Power/Performance Tradeoffs , 2011, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[11]  Biplab Sikdar,et al.  A mechanism for load proportional energy use in wireless local area networks , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[12]  Li Shang,et al.  Dynamic voltage scaling with links for power optimization of interconnection networks , 2003, The Ninth International Symposium on High-Performance Computer Architecture, 2003. HPCA-9 2003. Proceedings..

[13]  Massoud Pedram,et al.  Dynamic voltage and frequency scaling based on workload decomposition , 2004, Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758).

[14]  Min Yeol Lim,et al.  Determining the Minimum Energy Consumption using Dynamic Voltage and Frequency Scaling , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[15]  Massoud Pedram,et al.  Predictive-Flow-Queue-Based Energy Optimization for Gigabit Ethernet Controllers , 2009, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[16]  Zhangqin Huang,et al.  Performance modeling and analysis of IEEE 802.11 protocol using POOSL , 2009, 2009 4th IEEE Conference on Industrial Electronics and Applications.