Abstract (Summary)
Awareness of location is one of the important and critical issue and challenge in wireless sensor network. Knowledge of Location among the participating nodes is one of the crucial requirements in designing of solutions for various issues related to Wireless sensor networks. Wireless sensor networks are being used in environmental applications to perform the number of task such as environment monitoring, disaster relief, target tracking, defenses and many more. Node localization is required to report the origin of events, assist group querying of sensors, routing and to answer questions on the network coverage. The proposed algorithm based on Enhanced composite with mobile beacon shortest path localization that gives the high accuracy in wireless sensor network. In this algorithm we merge enhanced mobile beacon method and DV hop method to take the advantage of both methods. We proposed an enhanced mobile beacon algorithm with the shortest path which is the updated method of previous given mobile beacon method. An enhanced composite localization algorithm is proposed that considers the existence of obstacles in mobility assisted wireless sensor networks. An optimal movement scheduling method with mobile beacon is proposed to address limitations of static wireless sensor network in node localization. In this scheme, a mobile beacon node cooperates with static sensor nodes and moves actively to refine location performance. It takes advantage of cooperation between mobile beacon and static sensors while, at the same time, taking into account the relay node availability to make the best use of beacon signals. Enhanced composite approach is based on both range free and range based method. It increases the accuracy in wireless sensor network to solve the localization problem. The proposed method is less expensive and consumes low power for computation, which increases the importance of this algorithm in wireless sensor network.
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Bibliographical Information:


School:Shobhit University

School Location:India

Source Type:Master's Thesis



Date of Publication:02/20/2011

Document Text (Pages 1-10)

Chapter 1

A sensor is a device that measures a physical quantity and converts it into a
signal which can be read by an observer or by an instrument. Sensor in wireless
network receives input information, store the information, compute and forward
the data to other devices. For example, a thermocouple converts temperature to
an output voltage which can be read by a voltmeter.
A Wireless Sensor Network (WSN) consists of spatially distributed autonomous
sensors to cooperatively monitor physical or environmental conditions, such as
temperature, sound, vibration, pressure, motion or pollutants. The development
of wireless sensor networks was motivated by military applications such as
battlefield surveillance and is now used in many industrial and civilian
application areas, including industrial process monitoring and control, machine
health monitoring, environment and habitat monitoring, healthcare applications,
home automation, and traffic control [21].


Sensor Node
Gateway Sensor Node
Figure 1.1: Typical multi-hop wireless sensor network architecture

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In addition to one or more sensors, each node in a sensor network is typically
equipped with a radio transceiver or other wireless communications device, a
small microcontroller, and an energy source, usually a battery. A sensor node
might vary in size from that of a shoebox down to the size of a grain of dust.
The cost of sensor nodes is similarly variable, ranging from thousand rupees to
a few pennies, depending on the complexity of the individual sensor nodes. Size
and cost constraints on sensor nodes result in corresponding constraints on
resources such as energy, memory, computational speed and communications
A sensor network normally constitutes a wireless ad-hoc network, meaning that
each sensor supports a multi-hop routing algorithm where nodes function as
forwarders, relaying data packets to one of more "base stations".

Figure 1.2: wireless ad-hoc sensor networks


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A wireless ad hoc sensor network consists of a number of sensors spread across
a geographical area. Each sensor has wireless communication capability and
some level of intelligence for signal processing and networking of the data. In
computer science and telecommunications, wireless sensor networks are an
active research area with numerous workshops and conferences arranged each
The applications for wireless sensor network are varied, typically involving
some kind of monitoring, tracking, or controlling. Specific applications include
habitat monitoring, object tracking, fire detection, land slide detection and
traffic monitoring. In a typical application, a wireless sensor network is
deployed in a region where it is meant to collect data through its sensor nodes.
1.2.1 Area monitoring
Area monitoring is a common application of wireless sensor networks. In area
monitoring, the wireless sensor network is deployed over a region where some
phenomenon is to be monitored. For example, a large quantity of sensor nodes
could be deployed over a battlefield to detect enemy intrusion [21]. When the
sensors detect the event being monitored (heat, pressure, sound, light, electromagnetic
field, vibration, etc.), the event is reported to one of the base stations,
which then takes appropriate action (e.g., send a message on the internet or to a
satellite). Similarly, wireless sensor networks can use a range of sensors to
detect the presence of vehicles ranging from motorcycles to train cars.
1.2.2 Environmental monitoring
A number of WSNs have been deployed for environmental monitoring. Many of
these have been short lived, often due to the prototype nature of the projects.
Examples of longer-lived deployments are glacier monitoring.
1.2.3 Greenhouse monitoring
Wireless sensor networks are also used to control the temperature and humidity
levels inside commercial greenhouses. When the temperature and humidity

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drops below specific levels, the greenhouse manager must be notified via e-mail
or cell phone text message, or host systems can trigger misting systems, open
vents, turn on fans, or control a wide variety of system responses. Because some
wireless sensor networks are easy to install, they are also easy to move as the
needs of the application change.
1.2.4 Landslide detection
A landslide detection system makes use of a wireless sensor network to detect
the slight movements of soil and changes in various parameters that may occur
before or during a landslide. And through the data gathered it may be possible to
know the occurrence of landslides long before it actually happens.
1.2.5 Machine health monitoring
Wireless sensor networks have been developed for machinery condition-based
maintenance (CBM) [21] as they offer significant cost savings and enable new
functionalities. In wired systems, the installation of enough sensors is often
limited by the cost of wiring, which runs between 5oo– 50000 rupees per feet.
Previously inaccessible locations, rotating machinery, hazardous or restricted
areas, and mobile assets can now be reached with wireless sensors. Often,
companies use manual techniques to calibrate, measure, and maintain
equipment. This labor-intensive method not only increases the cost of
maintenance but also makes the system prone to human errors. Especially in US
Navy shipboard systems, reduced manning levels make it imperative to install
automated maintenance monitoring systems. Wireless sensor networks play an
important role in providing this capability.
1.2.6 Water/Wastewater monitoring
There are many opportunities for using wireless sensor networks within the
water/wastewater industries. Facilities not wired for power or data transmission
can be monitored using industrial wireless I/O devices and sensors powered
using solar panels or battery packs.
1.2.7 Landfill ground well level monitoring and pump counter
Wireless sensor networks can be used to measure and monitor the water levels
within all ground wells in the landfill site and monitor leachate accumulation
and removal. A wireless device and submersible pressure transmitter monitors
the leachate level. The sensor information is wirelessly transmitted to a central

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data logging system to store the level data, perform calculations, or notify
personnel when a service vehicle is needed at a specific well. It is typical for
leachate removal pumps to be installed with a totalizing counter mounted at the
top of the well to monitor the pump cycles and to calculate the total volume of
leachate removed from the well. For most current installations, this counter is
read manually. Instead of manually collecting the pump count data, wireless
devices can send data from the pumps back to a central control location to save
time and eliminate errors. The control system uses this count information to
determine when the pump is in operation, to calculate leachate extraction
volume, and to schedule maintenance on the pump.
1.2.8 Water tower level monitoring
Water towers are used to add water and create water pressure to small
communities or neighborhoods during peak use times to ensure water pressure
is available to all users. Maintaining the water levels in these towers is
important and requires constant monitoring and control. A wireless sensor
network that includes submersible pressure sensors and float switches monitors
the water levels in the tower and wirelessly transmits this data back to a control
location. When tower water levels fall, pumps to move more water from the
reservoir to the tower are turned on [21].
1.2.9 Agriculture
Using wireless sensor networks within the agricultural industry is increasingly
common. Gravity fed water systems can be monitored using pressure
transmitters to monitor water tank levels, pumps can be controlled using
wireless I/O devices, and water use can be measured and wirelessly transmitted
back to a central control center for billing. Irrigation automation enables more
efficient water use and reduces waste.
1.2.10 Fleet monitoring
It is possible to put a mote with a GPS module on-board of each vehicle of a
fleet. The mote gathers it's position via the GPS module, and reports its

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coordinates so that the location is tracked in real-time. The motes can be
equipped with temperature sensors to avoid any disruption of the cold chain,
helping to ensure the safety of food, pharmaceutical and chemical shipments. In
situations where there is not reliable GPS coverage, like inside buildings,
garages and tunnels, using information from GSM cells is an alternative for to
GPS localization. Wireless sensor networks mainly used in controlling and
monitoring purposes. Various fields as we saw in above applications depend on
wireless sensor network. Traffic control is one of the best examples.
With the coming availability of low cost, short range radios along with advances
in wireless networking, it is expected that wireless ad hoc sensor networks will
become commonly deployed. In these networks, each node may be equipped
with a variety of sensors, such as acoustic, seismic, infrared, still/motion video
camera, etc. These nodes may be organized in clusters such that a locally
occurring event can be detected by most of, if not all, the nodes in a cluster.
Each node may have sufficient processing power to make a decision, and it will
be able to broadcast this decision to the other nodes in the cluster. One node
may act as the cluster master, and it may also contain a longer range radio using
a protocol such as Bluetooth. Unique characteristics of a WSN include:
• Limited power they can harvest or store
• Ability to withstand harsh environmental conditions
• Ability to cope with node failures
• Coping with mobility of nodes
• Communication failures
• Heterogeneity of nodes
• Large scale of deployment
• Network self-organization
• Unattended operation

• Node capacity is scalable, only limited by bandwidth of gateway


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Sensor nodes can be imagined as small computers, extremely basic in terms of
their interfaces and their components. They usually consist of a processing unit
with limited computational power and limited memory, sensors (including
specific conditioning circuitry), a communication device (usually radio
transceivers or alternatively optical), and a power source usually in the form of
a battery.
The base stations are one or more distinguished components of the WSN with
much more computational, energy and communication resources. They act as a
gateway between sensor nodes and the end user as they typically forward data
from the WSN on to a server. Many are ARM-processor based due to that
CPU's low power requirements and typically store-and-forward data when
wide-area-networking is available. Many techniques are used to connect to the
outside world including mobile phone networks, satellite phones, radio
modems, high power Wi-Fi links etc.
1.3.1 Hardware
The main challenge is to produce low cost and tiny sensor nodes. With respect
to these objectives, many current sensor nodes are prototypes. There are an
increasing number of small companies producing wireless sensor network
hardware and the commercial situation can be compared to home computing in
the 1970s. Some of the existing sensor nodes are given below. Many of the
nodes are still in the research and development stage, particularly their software.
Also inherent to sensor network adoption is the availability of a very low power
method for acquiring sensor data wirelessly. Low power integrated radio
transceivers are beginning to appear in "System on chip" ("SoC") CPUs which
dramatically reduce the system size.
1.3.2 Software
Energy is the scarcest resource of WSN nodes, and it determines the lifetime of
wireless sensor networks. Wireless sensor networks are meant to be deployed in
large numbers in various environments, including remote and hostile regions,

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with ad-hoc communications as key. For this reason, algorithms and protocols
need to address the following issues:

• Lifetime maximization
• Robustness and fault tolerance
• Self-configuration
1.3.3 Some of the "hot" topics in WSN software research are
• Security
• Mobility (when sensor nodes or base stations are moving)

• Usability - human intereface for deployment and management,
debugging and end-user control
• Middleware: the design of middle-level primitives between high level
software and the systems
1.3.4 Operating systems
Operating systems for wireless sensor network nodes are typically less complex
than general- purpose operating systems. They more strongly resemble
embedded systems, for two reasons. First, wireless sensor networks are typically
deployed with a particular application in mind, rather than as a general platform
for installing new applications. Second, a need for low costs and long lifetimes
on limited batteries leads most wireless sensor nodes to have low-power
microcontrollers, rather than high-power processors: mechanisms such as virtual
memory either unnecessary or too expensive to implement. Examples of
Operating system are TinyOS, MANTIS, BTnut, LiteOS, and Nano-RK. Early
versions of TinyOS required writing all code in event-driven nesC, versions 2.1
1.3.5 Algorithms
Wireless sensor network s are composed of a large number of sensor nodes,
therefore, distributed algorithms are often targeted. WSNs are often energy-

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constrained, that is, energy is a scarce resource, and one of the most energyexpensive
operations is data transmission and idle listening. For this reason,
much algorithmic research in wireless sensor networks focuses on the study and
design of energy aware algorithms for saving energy by reducing the amount of
data being transmitted. To this end, techniques often employed are data
aggregation, power cycling and the use of topology control algorithms.
Another characteristic to take into account is that due to the constrained radio
transmission range and the polynomial growth in the energy-cost of radio
transmission with respect to the transmission distance, it is very unlikely that
every node will reach the base station, so data transmission is usually multi-hop
(from node to node, towards the base stations).
The algorithmic approach to modeling, simulating and analyzing WSNs
differentiates itself from the protocol approach by the fact that the idealized
mathematical models used are more general and easier to analyze. However,
they are sometimes less realistic than the models used for protocol design, since
an algorithmic approach often neglects timing issues, protocol overhead, the
routing initiation phase and sometimes distributed implementation of the
1.3.6 Simulators
Simulators of Wireless Sensor networks come in all shapes and sizes. These
range from those based on NS2, NS3, OMNET++ and OPNET, Jemula802, etc.
to others which are based on advanced programming paradigms such as Agentbased
There are network simulator platforms specifically designed to model and
simulate Wireless Sensor Networks, like TOSSIM, which is a part of TinyOS
and COOJA which is a part of Contiki. Traditional network simulators like ns-2
have also been used. A platform independent component based simulator with
wireless sensor network framework, J-Sim ([2]) can also be used. In addition,
there is a simulator focused on the evaluation of topology control protocols in


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WSNs called Atarraya. An extensive list of simulation tools for Wireless Sensor
Networks can be found at the CRUISE WSN Simulation Tool Knowledgebase.
Based on the OMNeT++ network simulator architecture, Mobility Framework
and Castalia can be used for simulation of wireless sensor networks.

Localization in sensor networks can be defined as ``identification of sensor
node's position''. For any wireless sensor network, the accuracy of its
localization technique is highly desired.
Localization is the issue of locating the geometrical position of the sensor node
in the network. Localization problem is an estimation of position of wireless
sensor nodes and to coordinate with one another. Localization is a challenge
which deals with wireless sensor nodes and it has been studied from many
years. There are different solutions and they are evaluated according to cost,
size and power consumption. Localization is important when there is an
uncertainty of the exact location of some fixed or mobile devices. One example
has been in the supervision of humidity and temperature in forests and/or fields,
where thousands of sensors are deployed by a plane, giving the operator little or
no possibility to influence the precise location of each node [2].
Therefore, the network localization problem—namely, the problem of
determining the positions of nodes in a network—has attraction of many
engineering field and have been researched for many years. The device whose
location is to be estimated is called localization node, and the network entity
with known location is called localization base station. Wireless sensor network
consists of a large set of inexpensive sensor nodes with wireless communication
interface. These sensor nodes have limited processing and computing resources.
Thus, algorithms designed for wireless sensor networks need to be both memory
and energy efficient. In most of the algorithms for wireless sensor network, it is
assumed that the sensor nodes are aware of their locations and also about the
locations of their nearby neighbors. Hence, localization is a major research area
in wireless sensor networks.

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