Changeset 2822

Timestamp:

10/30/09 20:48:39 (4 weeks ago)

Author:

jaein

Message:

 

Location:

HydroWatch/Tim/doc/ipsn10

Files:

• sec_conc.tex (modified) (1 diff)
• sec_energy.tex (modified) (1 diff)
• sec_eval.tex (modified) (1 diff)

HydroWatch/Tim/doc/ipsn10/sec_conc.tex

@@ -4 +4 @@
 
 Given this model of thinking we propose a means by which nodes can adapt and optimize their operating point in order to maximize network utility given some prediction of future energy resources. As such, we are advocating moving away from the ``slow and steady'' approach to long-term sensing where a node adopts a fixed operating point and attempts to consume as little energy as possible. Given we have the ability to estimate future energy resources, we believe nodes should consume as \emph{much} energy as possible in order to fully utilize all available harvested energy and maximize both the data fidelity and network responsiveness. Using retrospective environmental data, we have shown how our system performs over extended periods in being able to sustain long-term operation whilst maximizing network utility given energy constraints. Finally we compare our approach with other proposed methods for adapting node operating point, and show that we are able to achieve greater levels of network utility at the same levels of energy consumption.
-
-%By moving away from the ``sample-listen-send'' paradigm which has dominated so much of sensor network protocols to date, we see a wealth of new research questions for the community. 
 Moving forward we intend to further demonstrate the benefit of our proposed approaches via long-term field trials. Of particular interest will be cases where there is significant variation in the amount of energy nodes in the network harvest. Currently there is not an energy-aware component in the routing protocol, thus we believe the inclusion of such a parameter will be useful in these scenarios. Finally, we believe many of the ideas presented in this paper will have broad applicability in the growing field of multimedia networks, where nodes can assume many operating points with high variations in power consumption and performance. Optimizing the operating point for these types of nodes will become crucial for long-term operation, and will greatly change the way these kinds of technologies can be used into the future.

HydroWatch/Tim/doc/ipsn10/sec_energy.tex

@@ -1 +1 @@
 %%%%%%%%%%%%%%%%%%%%%%%
 \section{Energy Prediction}~\label{sec:energypredict}
-As described in Section~\ref{sec:energyrelation}, the optimization process relies on an estimate of harvested energy at various intervals ahead in time in order to make use of opportunities of high amounts of energy in order to maximize utility. In order to form this prediction $\hat{E_h}(n,k+i)}$, we make use of a number of different information inputs including an astronomic model, solar radiation measurements
+As described in Section~\ref{sec:energyrelation}, the optimization process relies on an estimate of harvested energy at various intervals ahead in time in order to make use of opportunities of high amounts of energy in order to maximize utility. In order to form this prediction $\hat{E_h}(n,k+i)$, we make use of a number of different information inputs including an astronomic model, solar radiation measurements
 and the measurement and forecast of weather conditions. The prediction process is shown in Figure~\ref{fig:energy_prediction_process}.
 

HydroWatch/Tim/doc/ipsn10/sec_eval.tex

@@ -290 +290 @@
 
 
-\subsection{Implementation}
-
-[Testbed results on cross-over point]
+%\subsection{Implementation}
+%
+%[Testbed results on cross-over point]
 
 %\subsubsection{Hardware Platform}