Changeset 2800

Timestamp:

10/30/09 18:16:09 (4 weeks ago)

Author:

jaein

Message:

 

Files:

• HydroWatch/Tim/doc/ipsn10/sec_adaptive.tex (modified) (4 diffs)

HydroWatch/Tim/doc/ipsn10/sec_adaptive.tex

@@ -3 +3 @@
 
 \subsection{Linking Utility and User Policy}~\label{sec:utility_policy}
-As discussed in Section~\ref{sec:motivation}, one of the central aims of this paper is to argue to we should move beyond an ``always on'' model for environmental sensing. Whilst it is important that nodes in the network have some level of responsiveness (e.g. for reporting data or receiving user commands), by removing the cost burden brought about by continuous responsiveness, we can move energy resources onto other roles. Given this revised model of thinking, we argue that a useful node and network level \emph{utility} can be defined as a combination of metrics for both \emph{network responsiveness} and \emph{data fidelity}. Furthermore we argue that a suitable utility function (which is by definition somewhat subjective) can be inferred from a combination of these parameters and a \emph{user-policy} which defines bounds for network performance.
+As discussed in Section~\ref{sec:motivation}, one of the central aims of this paper is to argue that we should move beyond an ``always on'' model for environmental sensing. Whilst it is important that nodes in the network have some level of responsiveness (e.g. for reporting data or receiving user commands), by removing the cost burden brought about by continuous responsiveness, we can move energy resources onto other roles. Given this revised model of thinking, we argue that a useful node and network level \emph{utility} can be defined as a combination of metrics for both \emph{network responsiveness} and \emph{data fidelity}. Furthermore we argue that a suitable utility function (which is by definition somewhat subjective) can be inferred from a combination of these parameters and a \emph{user-policy} which defines bounds for network performance.
 
 In the simplest case, we define the role of the user-policy to assign lower and upper bounds on the report/responsiveness frequency for a node $\{F_r^{min}  F_r^{max}\}$ and the lower/upper bounds on the sampling rate for all sensors\footnote{For the purpose of this work, we assume that all sensors sample at the same rate} $\{F_s^{min}  F_s^{max}\}$ as well as a streaming interval $T_{data}$ for raw data.  Thus for a node $n$ over some interval of time $k$ we assign two key parameters:
@@ -39 +39 @@
 Report periods, occurring at frequency $F_r(n,k)$ during interval $k$, play three important roles regarding the responsiveness of the network. Firstly they allow nodes to send back summary reports of the average or latest values of sensor readings. Second they allow a period when user requests can be sent out to nodes, which can contain requests for status data or most importantly, provide the periods when nodes can have their scheduling parameters updated. Thirdly they allow the base to send out synchronization beacons to nodes to ensure the network sync stays within a reasonable error bounds.
 
-Streaming periods, occurring at a user pre-defined period of $T_{data}$, are are used for sending back buffered (stored in flash) high-fidelity data sampled at $F_s(n,k)$. An example streaming period maybe be once per day chosen to coincide with the brightest part of the day. Our work assumes that a standard protocol for reliably streaming back data is used during these periods~\cite{koala08ipsn,lance08sensys}, where data is streamed sequentially from leaf nodes through to 1-hop nodes, allow nodes closer to the leaves to turn off once they have streamed their data. 
+Streaming periods, occurring at a user pre-defined period of $T_{data}$, are used for sending back buffered (stored in flash) high-fidelity data sampled at $F_s(n,k)$. An example streaming period maybe be once per day chosen to coincide with the brightest part of the day. Our work assumes that a standard protocol for reliably streaming back data is used during these periods~\cite{koala08ipsn,lance08sensys}, where data is streamed sequentially from leaf nodes through to 1-hop nodes, allow nodes closer to the leaves to turn off once they have streamed their data. 
 
 %Discuss how this relies on flash storage - thus the cost analysis in the next section.
@@ -55 +55 @@
 
 
-We assume during flash memory operation, that it is one
+We assume during flash memory operation, that it is
 one of the three states: \textit{off}, \textit{transition}
 and \textit{active}. The flash memory stays in the off mode 
@@ -90 +90 @@
 Figure~\ref{fig:flash_cost}(d) compares the energy-per-cost
 for the flash memory and the radio. There are two take-aways
-from this graph. First. it shows the importance
+from this graph. First, it shows the importance
 of choosing the RAM buffer size. For the flash to achieve
 the energy-per-cost of the radio at 0.5\% duty-cycle, which