Energy Reduction and Delay Minimization in Wireless Sensor Networks through Asips

Low energy consumption is a major design constraint for battery operated embedded systems such as wireless sensor networks or WSN. Low energy is more important compared to low power for such systems as it will increase lifetime of the system. The major component which can reduce energy is to reduce delay. WSN motes must power sensors, a processor, and a radio for wireless communication over long periods of time, and are therefore particularly sensitive to energy use. Recent techniques for reducing WSN energy consumption, such as aggregation, require additional computation to reduce the cost of sending data by minimizing radio data transmissions. Larger demands on the processor will require more computational energy, but traditional energy reduction approaches, such as multi-core scaling with reduced frequency and voltage may prove heavy handed and ineffective for motes. Instead, application-specific instruction set processor (ASIP) can reduce computational energy consumption by processing operations common to specific applications more efficiently than a general purpose processor. By the nature of their deeply embedded operation, motes support a limited set of applications, and thus the conventional general purpose computing paradigm may not be well-suited to mote operation. Both simple and complex operations can improve performance and use orders of magnitude less energy with ASIPs. This paper examines the design considerations of a ASIP for compressed Bloom filters, a data structure for efficiently storing set membership.