% $Id: intro.tex,v 1.10 2005/03/01 10:06:58 gokhale Exp $

\section{Introduction}
\label{sec:intro}

A wireless sensor network (WSN) consists of low power, low cost,
multifunctional and miniature collaborating sensor nodes, which are
spread across a geographical area. The nodes are usually deployed
inside or very close to a phenomenon being tracked. The sensor nodes
carry a small processor, which can perform several localized
computations, such as data aggregation or routing data packets. 
This enables them to process raw data generated by the phenomenon,
filter it and send only the required information to the
observer(s). 

Moreover, the position of sensor nodes need not be
pre-determined thereby allowing any random deployment of these nodes
and facilitating tracking of mobile phenomenon. 
These properties make the sensor networks applicable in a variety of
applications ranging from military, to industrial, to scientific, to
healthcare, to home. Most of these applications are aimed at (a)
minimizing humans in the loop so that tasks can be executed remotely,
such as remotely monitoring a patient's health and (b) collection of
data in the environments that are hazardous to humans. 

In WSNs a large number of sensor nodes collect the sensed
data, which is then routed to a number of observers interested in this
data. We call the sensor node generating data reports of an observed
phenomenon as a {\em source node} and the node requesting the report
as a {\em sink node}, both of which may be fixed or mobile. For
example, soldiers collecting location information of the enemy using
the sensor networks deployed 
in the battlefield act as sink nodes. The movement of the enemy acts
as the phenomenon being tracked, whereas the sensor nodes in the
immediate vicinity of that phenomenon act as source nodes. The source
nodes detect the movement, generate appropriate data reports, which are
then forwarded to each of the sink nodes interested in the event.   

The unique characteristics of wireless sensor networks described
below, however, makes the problem of disseminating the data generated
by sensor nodes non-trivial and different than conventional wired
networks. The main challenges are: 
\begin{enumerate}
\item Wireless sensor networks are usually large to ensure that a
      mobile phenomenon can be covered, which might occur over a wide
      geographical terrain.  
\item Computational power, storage capacity, battery life are limited,
      since the nodes themselves have to be large. Further, the nodes
      themselves can not be reconfigured (to add some resources for
      example) once deployed. 
\item Node failures and frequent topology changes, due to node
      failures or sensor movement.  
\end{enumerate}

These problems form the motivation for a data-centric family of sensor
network routing protocols called data-dissemination protocols, where
the focus is on the data rather than the nodes. It follows that the
protocols must be scalable, efficient, fault-tolerant and adaptable. A
number of data-dissemination protocols have been
suggested~\cite{Zhang_GRAB:03,Khanna:04,Estrin_DD:00,Zhang_TTDD:02},
which aim to address these challenges. 

Although significant work in WSN area has been done on designing and 
building sensor networks, most of it focuses on designing new
applications and routing protocols.  For example,
Bokareva et al~\cite{Bokareva:04} recently proposed a comparative
study of  data-dissemination protocols comprising uniform node
distribution under two different topologies. However, this is a more
direct comparative
% Amogh, what do you mean by ``more direct comparative''
%Andy, although we do study the protocol comparison, that is in
%addition to resource tradeoff (which is the main subject we address
%in this paper). Hence to differentiate our work from theirs I
%mentioned 'more direct comparative' since their study is *only*
%a comparative protocol study.
% OK (I am keeping this comment and explanation here)
analysis and does not study the effect of variations in availability
of network resources on the overall performance.  This paper aims to
address the resource tradeoffs in designing a WSN and its
ramifications on network performance and its design. We also compare
two dissemination protocols {\em e.g.}, the Two-tier Data
Dissemination (TTDD)~\cite{Zhang_TTDD:02} and Directed Diffusion
(DD)~\cite{Estrin_DD:00} protocols, in order to provide useful
insights into the design choices and optimizations for WSNs. The
direct impact of our work is thus on providing useful insights in
network and protocol optimizations, studying the best possible design and
optimal resource decisions in the context of the dissemination
protocols studied.
%Andy:  we had a section for lessons learnt from the paper, at the end 
%of introduction, however this doesnt show up here in the pdf.
% Went to conclusions. But the small para from conclusions came
% here. This is how things should be arranged in intro - Andy

Our experiments analyzing network reliability indicate that increasing
the number of nodes per unit sensing area does not make network more
redundant; instead this might very well result in fast depleting
network which is counter intuitive. One of the important findings from
the analysis is that the the network needs to intelligently manage the
resources. At increased network densities and sink sizes the energy
consumption starts increasing very rapidly on account of the added
traffic. This argues for a better energy utilization mechanism which
scales the network well as network density, while maintaining other
performance parameters (for example, delivery fraction, average delay)
within acceptable limits.  

\noindent\paragraph*{\bf Organization}

The rest of the paper is organized as follows:
Section~\ref{sec:overview} provides a brief overview of the data
dissemination protocols used in our study; Section~\ref{sec:eval} 
describes the experimental setup used for our protocol simulations;
Section~\ref{sec:results} presents and analyzes the results of our
simulation studies; and finally Section~\ref{sec:conclusions} provides
concluding remarks outlining lessons learned.

