% $Id: relwork.tex 20822 2010-01-03 14:28:25Z gokhale $
\section{Related Work}
\label{sec:relwork}

Prior research closely related to the ideas presented in this paper
can be classified along two dimensions: (1) those that evaluate the
performance of the wireless channel for vehicular communications and
(2) those that develop higher-level capabilities (\emph{e.g.}, in
middleware) to overcome the challenges imposed by mobility.  These
prior efforts are important since they provide crucial insights into
the behavior and performance of the physical medium, or provide key
software-based algorithms that can tune performance.

\subsection{Research on Performance Evaluation of Wireless Networks in the Presence of Mobility} 

The IEEE 802.11 technologies form the basis of most wireless networks
in wireless LANs and Wi-Fi, which have become affordable and
commoditized.  The vehicular networks are also designed to leverage
these dominant technologies.  In particular, the IEEE
802.11p~\cite{Jiang_DSRC:06,VTC_80211p:08} is an emerging standard for
dedicated short range communication (DSRC) used in vehicular networks.

Bai~\cite{Bai_ITSC:06} describes real-world experiments involving
three vehicles.  The authors focus primarily on the reliability aspect
of 802.11p DSRC for vehicular safety communications needed in
applications, such as forward collision warning or blind spot
advising.  The authors measured the packet delivery ratio
(\emph{i.e.}, the percentage of packets transmitted that were
correctly received) and distribution of consecutive packet drops
(\emph{i.e.}, the probability distribution of consecutive packet
drops).  The authors concluded that DSRC does not incur packet loss in
bursts and hence the reliability of DSRC is adequate.

Despite their critical findings, the insights in~\cite{Bai_ITSC:06}
are limited due to measurements with only three vehicles using only
V2V communications.  Vehicular networks simultaneously must
support both the V2V and V2I communication networks, and that too with
variation in density of vehicles, speeds, and direction of traffic
flow.

Prior
studies~\cite{Bilstrup_VTC:08,Eichler_VTC:07,Wang_ISCC:08,Wang_ICVES:08,Wellens_VTC:07}
have evaluated the performance of 802.11p using simulations and
analytical models.  Eichler~\cite{Eichler_VTC:07} conducted
OMNeT++-based simulations to measure the collision probability,
throughput, and delay for 802.11p.  The study determined that 802.11p
was unable to handle many high priority messages in a dense network of
vehicles.  Similarly, lower priority messages suffer from exponential
delays as the density of the network increases.

Bilstrup et. al.~\cite{Bilstrup_VTC:08} 
%~\cite{Bilstrup_ITS:08,Bilstrup_VTC:08} 
study 802.11p MAC layer for supporting real-time
applications.  In contrast to the findings in~\cite{Bai_ITSC:06}, they
conclude that the channel access (which is a property controlled by
the MAC layer) cannot be assured in a manner that supports predictable
behavior.  As a result, 802.11p is not suitable for low-latency
communications.

Similarly, Wang et. al~\cite{Wang_ICVES:08} conclude that certain
parameter settings in 802.11p MAC can lead to undesirable throughput.
For example, the backoff window sizes (which are needed after
collisions) are not adaptive to the dynamics of the number of vehicles
involved in the communication.  This problem stems from the density of
vehicles and the percentage of them trying to communicate.

All these findings are crucial since solutions to overcome the
inherent limitations are needed.  In~\cite{Wang_ISCC:08}, the authors
modify the 802.11p MAC layer to avoid wastage of bandwith resulting
from switching of channels between 802.11p's control channel and
service channel.  This results in better observed performance at the
TCP/UDP level.  Similarly, in~\cite{Bui_RTAS:07}, the authors modify
the MAC layer to alleviate the problems of collisions and priority
inversions thereby supporting real-time communications.  Although the
solutions in our paper also overcome similar challenges, we focus on
integrating individual solutions at the both the physical and cyber
level.

\subsection{Research on Application Layer Software Capabilities}
The JECho event infrastructure research~\cite{Chen_MW:03} argues that
a static topology of brokers is insufficient to assure reliable
delivery of information when end hosts are mobile.  To overcome this
problem, the authors present an approach called \emph{opportunistic
event channels,} in which brokers are dynamically created or deleted
depending on the mobility of the producers and consumers.  An
algorithm to optimize the event delivery path is presented that
considers the network-level handoffs to kickstart an application-level
handoff of the producer or consumer from its broker to a new broker
that can provide higher assurances of data delivery. 

The RT-STEAM~\cite{Cahill_WOWMOM:06} project describes a space-elastic
model to provide real-time information dissemination.  The model is
elastic because the range of dissemination can be adapted to continue
to meet real-time requirements.  The approach is spatial because it
relies on geographical proximity of interested subscribers from the
producers to adapt the region of dissemination.  This approach is
geared towards ad hoc communications between vehicles.

The ComPoScan~\cite{ComPoScan_MobiSys:08} project trades off the
available window for data communications with positioning accuracy by
switching between active scanning of signal-to-noise ratio versus
monitor sniffing, which is supported on majority of 802.11 cards.
This work is important since it can form a building block for a more
holistic ITS capability.

Despite significant prior work, however, these efforts tend to focus
on individual problems addressing them in isolation.  Our focus is to
address the challenges holistically as a CPS.
% Andy, you might briefly explain how the rest of the paper addresses
% these challenges.
% DONE
Our CPS solution relies on sensing physical parameters, such as
vehicle speed and signal-to-noise ratio, to trigger the runtime
adaptation logic supported by the cyber layer, which in turn controls
physical parameters, such as wireless radio power.

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