The Poster (.PDF)
Abstract: (.PDF)
We study the effects of mobility on packet loss in mobile ad-hoc networks (MANETs). Mobility is generally accepted as a cause of packet loss. Other broad causes of loss in MANETs are losses in the wireless channel and losses due to congestion. While there exist many models for wireless channel and congestion losses, mobility-related losses have not been studied in depth. Past studies have investigated the effect of mobility on actual transport-layer throughput, an approach that does not capture the charac ter of losses that occur and are then corrected by the transport layer. Our approach is to measure the likelihood of a packet being affected by mobility-related loss, rather than to measure the throughput achieved by any particular MANET transport layer.
Loss Metric
A mobility-related packet
loss may occur in one of many different ways. In order to distinguish
mobility-related
packet loss from other kinds of packet loss, we need to decide which
mechanisms at
which layers of the protocol stack are responsible for this kind of loss.
This
involves assuming particular link layer and ro uting protocols. In our
simulations, we
use 802.11 and DSR respectively. A challenge we face is that some kinds of
mobility-related losses occur through similar mechanisms as losses due to
congestion
(namely, buffer overflow and timeout). We have identifi ed four mechanisms
that cause
the complete set of losses that we attribute to mobility. [1] Drops at
intermediate
hops because the source route was invalid and salvaging did not succeed.
[2] Drops due
to send failure at the source. [3] Drops from the so urce's send buffer
because of
timeout. [4] Drops at the source's send buffer due to insufficient space
to queue all
packets which are pending route discovery. We include losses due to these
four causes
in the loss metric we define, the MILMAN metric.
In addition, we count the number of packets that had their original source
routes
modified en-route in the salvaging process, and reached the destination
successfully.
Though these packets are not lost, they are clearly affected by mobility,
and we
include them in the metric. Through experimentation, we found that this
component
contributes a very small percentage to the metric.
Connectivity Metric
We studied the correlation of the MILMAN metric with a metric that
measures the number of changes in the shortest path
between the source and destination on the connectivity graph. We find that
there is weak positive correlation for dense
graphs, but strong negative correlation for sparsely connected graphs.
However, we note that
for sparse networks, the above metric has negative correlation with
velocity, and hence may not be representative of
mobility. We considered another metric, the disconnection time
between the source and destination and as expected
we found that the MILMAN metric varies directly with this metric.
Setup
Simulations were conducted in ns-2 with the random waypoint mobility model
for CBR traffic. A single source-destination
pair was used for each of the simulations. We varied the area from
1000sq.m. to 2400 sq.m. at intervals of 100 sq.m.
The maximum velocity of nodes was varied from 5 m/s to 25 m/s in steps of
5. Ten different scenarios were chosen for
each area-velocity combination. Hence, a total of 750 simulations were
conducted.
Results and Future Work
Our preliminary results indicate that though an
increase in mobility(velocity) leads to greater packet loss in densely
connected networks, we can observe some
interesting (though isolated) cases where it leads to a decrease in
packet loss in case of
sparsely connected networks.
We plan to study the characteristics of these interesting cases, losses in
other mobility models and routing protocols
as well as formulating models for mobility-related losses for particular
mobility models, with the goal of being able
to us e the model in the performance analysis of specific transport
layers.