Wireless sensor network consists of a large number of simple sensor nodes
that collect information from external environment with sensors, then process
the information, and communicate with other neighboring nodes in the network.
Usually, sensor nodes operate with exhaustible batteries unattended. Since
manual replacement or recharging of the batteries is not an easy, desirable
or always possible task, the power consumption becomes a very important issue
in the development of these networks. The total power consumption of a node
is a result of all steps of the operation: sensing, data processing and radio
transmission. In most published papers in literature it is assumed that the
sensing subsystem consumes significantly less energy than a radio block.
However, this assumption does not apply in numerous applications, especially
in the case when power consumption of the sensing activity is comparably
bigger than that of a radio. In that context, in this work we focus on the
impact of the sensing hardware on the total power consumption of a sensor
node. Firstly, we describe the structure of the sensor node architecture,
identify its key energy consumption sources, and introduce an energy model
for the sensing subsystem as a building block of a node. Secondly, with the
aim to reduce energy consumption we investigate joint effectiveness of two
common power-saving techniques in a specific sensor node: duty-cycling and
power-gating. Duty-cycling is effective at the system level. It is used for
switching a node between active and sleep mode (with the duty-cycle factor of
1%, the reduction of in dynamic energy consumption is achieved). Power-gating
is used at the circuit level with the goal to decrease the power loss due to
the leakage current (in our design, the reduction of dynamic and static
energy consumption of off-chip sensor elements as constituents of sensing
hardware within a node of is achieved). Compared to a sensor node
architecture in which both energy saving techniques are omitted, the
conducted MATLsimulation results suggest that in total, thanks to
involving duty-cycling and power-gating techniques, a three order of
magnitude reduction for sensing activities in energy consumption can be
achieved.