System-Level Energy Tradeoffs for Collaborative Computation in Wireless Networks

Energy is a critical performance metric in collaborative and distributed wireless networks. An integrated approach that considers system-level energy tradeoffs (such as communication versus computation energy) is essential for energy efficient application development in these networks. In this chapter, we present a system-level model for estimating the energy dissipation in these networks, and discuss energy reduction techniques for the Automatic Target Recognition (ATR) problem in a wireless environment. We show that by using our techniques and analysis up to 80% reduction can be achieved in the overall system energy. Finally, we discuss the impact of changing technology and energy costs on the effectiveness of these techniques.

[1]  Krzysztof Kuchcinski,et al.  Low-energy directed architecture selection and task scheduling for system-level design , 1999, Proceedings 25th EUROMICRO Conference. Informatics: Theory and Practice for the New Millennium.

[2]  Viktor K. Prasanna,et al.  Power-Aware Embedded System Design Using the Milan Framework , 2002 .

[3]  R. O Handley,et al.  An Innovative Passive Solid-State Magnetic Sensor , 2000 .

[4]  Stephen P. Crago,et al.  Power-Aware Design Synthesis Techniques for Distributed Real-Time Systems , 2001, OM '01.

[5]  Mark Weiser,et al.  Some computer science issues in ubiquitous computing , 1993, CACM.

[6]  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).

[7]  Viktor K. Prasanna,et al.  Rapid design space exploration of heterogeneous embedded systems using symbolic search and multi-granular simulation , 2002, LCTES/SCOPES '02.

[8]  Trevor Pering,et al.  Dynamic Voltage Scaling and the Design of a Low-Power Microprocessor System , 1998 .

[9]  Adam Wolisz,et al.  A trace-based approach for determining the energy consumption of a WLAN network interface , 2002 .

[10]  Luca Benini,et al.  System-level power optimization: techniques and tools , 2000, Proceedings. 1999 International Symposium on Low Power Electronics and Design (Cat. No.99TH8477).

[11]  Suresh Singh,et al.  PAMAS—power aware multi-access protocol with signalling for ad hoc networks , 1998, CCRV.

[12]  Debashis Panigrahi.  Energy Modeling for Wireless Internet Access , 2001 .

[13]  Mahmut T. Kandemir,et al.  The design and use of simplePower: a cycle-accurate energy estimation tool , 2000, Proceedings 37th Design Automation Conference.

[14]  Luciano Lavagno,et al.  Efficient power co-estimation techniques for system-on-chip design , 2000, DATE '00.

[15]  Viktor K. Prasanna,et al.  An energy efficient adaptive distributed source coding scheme in wireless sensor networks , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[16]  Anantha Chandrakasan,et al.  Energy efficient system partitioning for distributed wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).