Fault Tolerant Localization and Tracking of Multiple
Sources in WSNs Using Binary Data
ABSTRACT:
This paper investigates the use of a Wireless Sensor Network for localizing and
tracking multiple event sources (targets) using only binary data. Due to the simple
nature of the sensor nodes, sensing can be tampered (accidentally or maliciously),
resulting in a significant number of sensor nodes reporting erroneous observations.
Therefore, it is essential that any event tracking algorithm used in Wireless Sensor
Networks (WSNs) exhibits fault tolerant behavior in order to tolerate misbehaving
nodes. The main contribution of this paper is the development and analysis of a
low-complexity, distributed, real-time algorithm that uses the binary observations
of the sensors for identifying, localizing, and tracking multiple targets in a fault
tolerant way. Specifically, our results indicate that the proposed algorithm retains
its performance in tracking accuracy in the presence of noise and faults, even when
a large percentage of sensor nodes (25 percent) report erroneous observations.
EXISTING SYSTEM:
Sensor nodes are often envisioned to operate unattended for long periods of time in
hostile environments, e.g., air-dropped inside an area for localizing potential
targets and intruders. From a security point of view, there is an increased
probability that the sensor readings are affected by a malicious attacker. For
instance, the authors present a scenario with malicious actuator nodes deployed to
perturb or distort the readings of neighboring sensor nodes within their actuation
radius. In addition, sensor nodes can provide erroneous observations for a variety
of other reasons: noise, energy depletion, and environmental harsh conditions of
operation and software problems.
DISADVANTAGES OF EXISTING SYSTEM:
In addition, sensor nodes can provide erroneous observations for a variety of
other reasons: noise, energy depletion, environmental harsh conditions of
operation and software problems. For example, the authors in report situations
where a node would constantly report the presence of an event (false positive)
when its processing board was overheated, or scenarios in which sensor nodes
exhibited unexpected behavior due to soft-ware bugs that were not detected.
PROPOSED SYSTEM:
Wireless sensor networks (WSNs) have been proposed for monitoring large areas
against the presence of event sources. The events can be intruders, enemy vehicles,
pollutant sources or fires depending on the application. In all situations, each event
source emits a signal or sub-stance that attenuates inside the area under observation
and is measured by some of the sensor nodes based on their location relative to the
events. In this paper, we develop a fault tolerant localization and tracking algorithm
for multiple event sources in WSNs using only binary sensor observations. The
proposed algorithm, FTLT (Fault Tolerant Localization and Tracking), has the
following three main phases: (i) Identification, (ii) Localization, and (iii)
Smoothing.
ADVANTAGES OF PROPOSED SYSTEM:
 The FTLT algorithm, which constitutes the main contribution of this work,
features low complexity, distributed implementation, real-time application, and
fault tolerance in all three phases of its implementation. The algorithms used in
both the Identification and the Localization phase require only simple
operations (i.e., additions of ±1).
 Furthermore, the Kalman filter used in the Smoothing phase was found to be
the most efficient tracking method in terms of memory and computation out of
the different Bayes filters tested; however, we point out that for certain
applications (e.g., maneuvering targets), other filtering techniques may provide
more accurate tracking at the expense of computational complexity.
MODULES:
1. Identification
2. Localization
3. Smoothing
MODULES DESCSRIPTION:
Identification Phase:
In the Identification phase, all alarmed sensor nodes broadcast their status in their
own neighborhood. Then, based on the received information and using a
distributed leader election protocol a subset of the alarmed sensor nodes are selfappointed as leaders. After the first phase, the number of elected leaders should
correspond to the number of sources present in the field.
Localization Phase:
In the Localization phase, each leader runs d SNAP (distributed Subtract on
Negative observation and Add on Positive) to determine the location of the source
by only contacting the sensor nodes in its own neighborhood that are relevant to
the estimation problem.
Smoothing phase:
The location estimates are further refined in the Smoothing phase, where each
leader uses a smoothing algorithm to better approximate the path of the source and
in order to predict the next leader responsible for tracking it.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
 System
:
Pentium IV 2.4 GHz.
 Hard Disk
:
40 GB.
 Floppy Drive
:
1.44 Mb.
 Monitor
:
15 VGA Colour.
 Mouse
:
Logitech.
 Ram
:
512 Mb.
SOFTWARE REQUIREMENTS:
 Operating system :
Windows XP/7.
 Coding Language :
C#.net
 Tool
:
Visual Studio 2010
 Database
:
SQL SERVER 2008
]
REFERENCE:
Michalis P. Michaelides,Member, IEEE, Christos Laoudias,Student Member,
IEEE, and Christos G. Panayiotou,Senior Member, IEEE “Fault Tolerant
Localization and Tracking of Multiple Sources in WSNs Using Binary Data”IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 6, JUNE
2014.