| 9 | | The past decade has seen significant progress towards the goal of making long-term, embedded, environmental sensing a reality. Within a typical mote-class device, current technology dictates that the vast majority of energy is consumed by the physical radio. As such, duty-cycling of the radio has been the key method employed to reduce energy consumption, typically in order of 5\% duty cycles for practical deployments\cite{gdi04sensys,tolle05sensys,firewxnet06mobisys,sensorscope08ipsn}. |
| 10 | | Whilst ultra-low duty cycle MAC's have been validated under controlled conditions\cite{ye06sensys,dozer07ipsn}, |
| 11 | | in general, breaking through the 1\% duty-cycle barrier for practical, multi-hop deployment scenarios requiring highly reliable, ``always available'' operation, is very difficult with current radio technology. |
| | 9 | The past decade has seen significant progress towards the goal of making long-term, embedded, environmental sensing a reality. Within a typical mote-class device, current technology dictates that the vast majority of energy is consumed by the physical radio. As such, duty-cycling of the radio has been the key method employed to reduce energy consumption in practical deployments.~\cite{gdi04sensys,tolle05sensys,firewxnet06mobisys,sensorscope08ipsn} A number of ultra-low power MAC layers have sustained the race to zero consumption at the link layer\cite{ye06sensys,dozer07ipsn}, where the current state-of-the-art has a duty cycle of 0.65\%~\cite{hui08sensys}). However, we believe that with current technology, there is minimal further improvement possible for duty-cycling link layers. |
| | 10 | |
| | 11 | A common thread among most of the deployments mentioned is an implicit requirement that the network is 'always available' - the link layer provides the ability to interact with any node in the network at any time. Though this provides a degree of comfort for network operators, it often limits the capacity of the network to make sensor measurements by monopolizing energy resources. |
| | 12 | |
| | 13 | To get a sense for how much the radio dominates an example environmental sensing application energy budget, we show two pie charts in Figure~\ref{fig:energy}: (a) shows the energy distribution between the hardware components for a node running the Low Power Listening (LPL) radio duty-cycling MAC layer~\cite{polastre05bmac} and (b) shows the same distribution for a node that runs the same LPL layer, but only 10\% of the time; the other 90\% of the time is spent with the radio completely off. Though the radio in each case is the majority consumer, the magnitude of consumption is nearly an order of magnitude less in the latter. This provides an opportunity to reassign the Joules previously reserved for radio idle listening to more useful tasks like increased sensing. |
| | 14 | |
| | 15 | Two challenges arise from this approach - the need to reconstruct routing links and trees after waking up and the increased cost of transmission due to batching. First, examining network reconstruction |
