| 7 | | Within the hardware layer, 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}. |
| | 6 | %Within the broad scope of research that has subsequently evolved, a key constraint that has defined much of the field is that of energy resources. Energy must either be stored at a node level for the life of a deployment, manually replaced or harvested from the environment. Given the limitations around stored energy density |
| | 7 | %\cite{roundy04ewsn} and challenges in the cost and predicability of harvested energy from sources such as solar or wind energy, much of the field today has focussed on reduction of energy consumption at the load side. |
| | 8 | |
| | 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}. |
