Wsn by checkmate

2013
CheckMate
Payal Umraliya Roll No: 99
[M.sc (I.T) 7th Semester] VNSGU
10/6/2013
Wireless Sensor Networks (WSN)

Payal Umraliya Roll No: 99 [M.sc (I.T) 7th Semester] VNSGU
CheckMate
2Abstract:
Advances in silicon technology have led to the development of next-generation,
low-cost, low-power, multifunctional, sensor devices. These devices communicate
wirelessly to transmit their readings. They are called wireless sensors and present a new
facet in the field of communication and computer networks. Wireless sensors are
compact devices that integrate communication, computation and microelectrical
mechanical (MEMS) devices into a single chip.
A sensor network is a collection of communicating sensing devices or nodes. A
large number of sensors can be spread across a geographical area and networked in many
applications that require unattended operations, hence producing a wireless sensor
network (WSN). The power of WSNs lies in the ability to deploy large numbers of such
tiny sensor nodes. While the capability of any single device is minimal, the composition
of hundreds of devices offers a significant opportunity for parallel, accurate and reliable
data acquisition.
Introduction:
With the recent technological advances in wireless communications,integrated
digital circuits, and micro electro mechanical systems (MEMS); development of wireless
sensor networks has been enabled and become dramatically feasible.
Wireless sensor networks (WSNs) are large networks made of a numerous number
of sensor nodes with sensing, computation, and wireless communications capabilities.
Many various routing, power management, and data dissemination protocols have
been designed for wireless sensor networks (WSNs) dependent on both the network
architecture and the applications that it is designed for. In this paper, we present the state
of the art of wireless sensor networks' architecture and design features. Also, in this
paper, we introduce recent work on routing protocols for WSNs and their design goals
and challenges. Also, an overview of the application that WSNs assist in is presented.
Finally, several open research questions of wireless sensor networks management and
issues are suggested and put forward.
Wireless sensor network (WSN) is the result of the combination of sensor
techniques, embedded techniques, distributed information processing, and
communication mechanisms. A WSN is a network that is made of hundreds or

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thousands of these sensor nodes which are densely deployed in an unattended
environment with the capabilities of sensing, wireless communications and computations
WSN is a network made of a numerous number of sensor nodes with sensing,
wireless communications and computation capabilities. These sensor nodes are scattered
in an unattended environment situated far from the user
Routing Protocols for WSNs
A. Flooding
Flooding [5] is an old routing mechanism that may also be used in sensor
networks. In Flooding, a node sends out the received data or the management
packets to its neighbors by broadcasting, unless a maximum number of hops for
that packet are reached or the destination of the packets is arrived. here are
some deficiencies for this routing technique [ Implosion: is the case where a
duplicated data or packets are sent to the same node. Overlap: if two sensor
nodes cover an overlapping measuring region, both of them will sense/detect
the same data. As a result, their neighbor nodes will receive duplicated data or
messages. Resource blindness: A WSN protocol must be energy resource-aware
and adapts its sensing, communication and computation to the state of its
energy.
B. Gossiping
Gossiping protocol is an alternative to flooding mechanism. In Gossiping,
nodes can forward the incoming data/packets to randomly selected neighbor
node. Once a gossiping node receives the messages, it can forward the data
back to that neighbor or to another one randomly selected neighbor node. This
technique assists in energy conservation by randomization. Gossiping can solve
the implosion problem.
C. SPIN
SPIN (Sensor Protocols for Information via Negotiation) is a family of adaptive
protocols for WSNs. Their design goal is to avoid the drawbacks of flooding

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protocols mentioned above by utilizing data negotiation and resource-adaptive
algorithms.
D. Directed di_usion
Directed di_usion is another data dissemination and aggregation protocol. It is a
data-centric and application aware routing protocol for WSNs. It aims at
naming all data generated by sensor nodes by attribute-value pairs.
E. LEACH
LEACH (Low Energy Adaptive Clustering Hierarchy) is a self-organizing,
adaptive clustering-based protocol that uses randomized rotation of cluster-
heads to evenly distribute the energy load among the sensor nodes in the
network
F. PEGASIS
PEGASIS (Power-E_client GAthering in Sensor Information Systems) is a
greedy chain-based power e_cient algorithm.
The key features of PEGASIS are
 The BS is fixed at a far distance from the sensor nodes.
 The sensor nodes are homogeneous and energy constrained with
uniform energy.
 No mobility of sensor nodes.
G. GEAR
GEAR (Geographical and Energy Aware Routing) is a recursive data
dissemination protocol WSNs. It uses energy aware and geographically informed
neighbor selection Heuristics to rout a packet to the targeted region
Applications
Various fields of applications of wireless sensor networks are:

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5A. Area Monitoring:
Area monitoring is a common application of WSNs. In area monitoring, the
WSN is deployed over a region where some phenomenon is to be monitored.
A military example is the use of sensors detects enemy intrusion; a civilian
example is the geo-fencing of gas or oil pipelines.
B. Environmental/Earth Monitoring:
The term Environmental Sensor Networks, has evolved to cover many
applications of WSNs to earth science research. This includes sensing
volcanoes, oceans ,glaciers, forests .
C. Air pollution Monitoring:
Wireless sensor networks have been deployed in several cities (Stockholm,
London or Brisbane) to monitor the concentration of dangerous gases for
citizens. These can take advantage of the ad-hoc wireless links rather than
wired installations, which also make them more mobile for testing readings
in different areas. There are various architectures that can be used for such
applications as well as different kinds of data analysis and data mining that
can be conducted.
D. Forest fire Detection:
A network of Sensor Nodes can be installed in a forest to detect when a fire
has started. The nodes can be equipped with sensors to measure temperature,
humidity and gases which are produced by fire in the trees or vegetation.
The early detection is crucial for a successful action of the firefighters;
thanks to Wireless Sensor Networks, the fire brigade will be able to know
when a fire is started and how it is spreading.
E. Landslide Detection:

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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. Through the data gathered it may be
possible to know the occurrence of landslides long before it actually
happens.
F. WaterQulity Monitoring:
Water quality monitoring involves analyzing water properties in dams,
rivers, lakes & oceans, as well as underground water reserves. The use of
many wireless distributed sensors enables the creation of a more accurate
map of the water status, and allows the permanent deployment of monitoring
stations in locations of difficult access, without the need of manual data
retrieval.
G. Natural disaster Prevention:
Wireless sensor networks can effectively act to prevent the consequences of
natural disasters, like floods. Wireless nodes have successfully been
deployed in rivers where changes of the water levels have to be monitored in
real time.
 Industrial Monitoring
H. Machine Health Monitoring:
Wireless sensor networks have been developed for machinery condition-
based maintenance (CBM) 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. Previously inaccessible locations,
rotating machinery, hazardous or restricted areas, and mobile assets can now
be reached with wireless sensors.
I. Data logging:

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Wireless sensor networks are also used for the collection of data for
monitoring of environmental information, this can be as simple as the
monitoring of the temperature in a fridge to the level of water in overflow
tanks in nuclear power plants. The statistical information can then be used to
show how systems have been working. The advantage of WSNs over
conventional loggers is the “live” data feed that is possible.
J. Industrial sense and control applications:
In recent research a vast number of wireless sensor network communication
protocols have been developed. While previous research was primarily
focused on power awareness, more recent research have begun to consider a
wider range of aspects, such as wireless link reliability, real-time
capabilities, or quality-of-service. These new aspects are considered as an
enabler for future applications in industrial and related wireless sense and
control applications, and partially replacing or enhancing conventional wire-
based networks by WSN techniques.
K. Green houses:
Wireless sensor networks are also used to control the temperature and
humidity levels inside commercial greenhouses. When the temperature and
humidity 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.
L. Others:
 Acoustic Detection
 Seismic Detection
 Military Surveillance
 Inventory Tracking
 Medical Monitoring
 Smart Spaces
 Process Monitoring
 Agriculture Sector

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 Medical Sector
WSN Management
The behavior of WSN is highly unpredictable and dynamic. All these factors have to be
incorporated by various sensor network models that describe the current network's states.
Some of the possible suggested models are:
A. Network Topology Model:
It describes the actual topology map and the connectivity and/or reachability of the
network.
B. Residual Energy Model:
Describes the remaining energy level of the nodes or the network. Using this
information as well as the data from network topology coupled together; would
make it possible to identify the weak areas.
C. Cost Model:
Describes the cost of equipment, energy, and human cost to maintain the desired
performance levels of the network.
D. Usage Patterns Model:
Represents the activity of the network in terms of period of time for nodes' activity,
quantity of data transmitted per sensor unit or the movements made by the target,
and tracking of hot spots in the network to avoid hot spot problem.
E. Behavioral Model:
Describes the behavior of the network. Since sensor networks are highly
unpredictable, dynamic, and unreliable, statistical and probabilistic models may be
much more e_cient in estimating the network behavior than estimating the network
behavior than deterministic models.

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F. Coverage Area Model:
A sensing coverage area map that represents the actual sensor's view of the
environment and communications coverage map that describes the communication
coverage area from the range of the RF transceiver.
Operating systems used in WSN
A WSN typically consists of hundreds or thousands of sensor nodes. These nodes have
the capability to communicate with each other using multi-hop communication. Typical
applications of these WSN include but not limited to monitoring, tracking, and
controlling.
The basic functionality of an operating system is to hide the low-level details of the
sensor node by providing a clear interface to the external world.
Processor management, memory management, device management, scheduling policies,
multi-threading, and multitasking are some of the Low
Level services to be provided by an operating system.
In addition to the services mentioned above, the operating system should also provide
services like support for dynamic loading and unloading of modules, providing proper
concurrency mechanisms, Application Programming Interface (API) to access underlying
hardware, and enforce proper power management policies.
A. TinyOS:
TinyOS is an open source, flexible, component based, and application-specific
operating system designed for sensor networks. TinyOS can support concurrent
programs with very low memory requirements. The OS has a footprint that fits in
400 bytes. The TinyOS component library includes network protocols, distributed
services, sensor drivers, and data acquisition tools.
B. Contiki OS

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Contiki is a lightweight open source OS written in C for WSN sensor nodes.
Contiki is a highly portable OS and it is build around an event-driven kernel.
Contiki provides preemptive multitasking that can be used at the individual process
level. A typical Contiki configuration consumes 2 kilobytes of RAM and 40
kilobytes of ROM. A full Contiki installation includes features like: multitasking
kernel, preemptive multithreading, proto-threads, TCP/IP networking, IPv6, a
Graphical User Interface, a web browser, a personal web server, a simple telnet
client, a screensaver, and virtual network computing.
C. MANTIS:
The MultimodAl system for NeTworks of In-situ wireless Sensors (MANTIS)
provides a new multithreaded operating system for WSNs. MANTIS is a
lightweight and energy efficient operating system. It has a footprint of 500 bytes,
which includes kernel, scheduler, and network stack. The MANTIS Operating
System (MOS) key feature is that it is portable across multiple platforms, i.e., we
can test MOS applications on a PDA or a PC [28]. Afterwards, the application can
be ported to the sensor node. MOS also supports remote management of sensor
nodes through dynamic programming. MOS is written in C and it supports
application development in C.
D. Nano-RK:
Nano-RK is a fixed, preemptive multitasking real-time OS for WSNs. The design
goals for Nano-RK are multitasking, support for multi-hop networking, support for
priority-based scheduling, timeliness and schedulability, extended WSN lifetime,
application resource usage limits, and small footprint. Nano-RK uses 2 Kb of
RAM and 18 Kb of ROM. Nano-RK provides support for CPU, sensors, and
network bandwidth reservations. Nano-RK supports hard and soft real-time
applications by the means of different real-time scheduling algorithms, e.g., rate
monotonic scheduling and rate harmonized scheduling. Nano-RK provides
networking support through socket-like abstraction. Nano-RK supports FireFly and
MicaZ sensing platforms.
E. Lite OS:
LiteOS [35] is a Unix-like operating system designed for WSNs at the University
of Illinois at Urbana-Champaign. The motivations behind the design of a new OS

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for WSN are to provide a Unix-like OS for WSN, provide system programmers
with a familiar programming paradigm (thread-based programming mode,
although it provides support to register event handlers using callbacks), a
hierarchical file system, support for object-oriented programming in the form of
LiteC++, and a Unix-like shell. The footprint of LiteOS is small enough to run on
MicaZ nodes having an 8 MHz CPU, 128 bytes of program flash, and 4 Kbytes of
RAM. LiteOS is primarily composed of three components: LiteShell, LiteFS, and
the Kernel.
F. EPOS:
EPOS (Embedded Parallel Operating System) is a component-based framework for
the generation of dedicated runtime support environments. The EPOS system
framework allows programmers to develop platform-independent applications and
analysis tools allow components to be automatically adapted to fulfill the
requirements of these particular applications. By definition, one instance of the
system aggregates all the necessary support for its dedicated application and
nothing else.
Table 1. Operating Systems Summary
Architectur
e
Programm
ing model
Scheduling Memory
Manageme
nt and
Protection
Communic
ation
Protocol
Support
Resource
Sharing
Support
for Real-
time
Applicatio
ns
TinyOS Monolithic Primarily
event
Driven,
support for
TOS
threads
has been
added
FIFO Static
Memory
Manageme
nt with
memory
protection
Active
Message
Virtualizati
on and
Completion
Events
No

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12Contiki Modular Protothrea
ds and
events
Events are
fired as
they occur.
Interrupts
execute
w.r.t.
priority
Dynamic
memory
manageme
nt and
linking. No
process
address
space
protection.
uIP and
Rime
Serialized
Access
No
MANTIS Layered Threads Five
priority
classes and
further
priorities in
each
priority
class.
Dynamic
memory
manageme
nt
supported
but use is
discourage
d, no
memory
protection.
At Kernel
Level COMM
layer.
Networking
Layer is at
user level.
Application
is free to
use custom
routing
protocols.
Through
Semaphore
s.
To some
extent at
process
scheduling
level
(Implement
ation of
priority
scheduling
within
different
processes
types)
Nano-RK Monolithic Threads Rate
Monotonic
and rate
harmonized
scheduling
Static
Memory
Manageme
nt and No
memory
protection
Socket like
abstraction
for
networking
Serialized
access
through
mutexes
and
semaphore
s. Provide
an
implementa
tion of
Priority
Ceiling
Algorithm
for priority
inversion.
Yes
LiteOS Modular Threads Priority Dynamic File based Through No

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13and Events based
Round
Robin
Scheduling
memory
manageme
nt and it
provides
memory
protection
to
processes.
communica
tion
synchroniz
ation
primitives
Miscellaneous:
OS/Feature Communication
Security
File System
Support
Simulation
Support
Programming
Language
Shell
TinyOS TinySec Single level file
system
TOSSIM NesC Not available
Contiki ContikiSec Coffee file
system
Cooja C Unix-like shell
runs on sensor
mote
MANTIS Not available Not available Through AVRORA C Unix-like shell
runs on sensor
mote
Nano-RK Not available Not available Not available C Not available
LiteOS Not available LiteFS Through AVRORA LiteC++ Shell that runs
on base station
Future research directions in OS:
Support for Real-Time Applications, Secondary Storage Management Virtual Memory
Support, Memory Management and Security ,Support for Multiple Applications, Robust
Communication Protocol Stack Security, Database Management System Implementation
Localization and Clock Synchronization API Support, APIs for Signal and Image
Processing. [1][2]

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14WSN Architecture:
A. Transport layer:
This layer is specifically needed when a system is organized to access other
networks. Providing a reliable hop by hop is more energy efficient than end to end.
Other protocol used in this layer is STCP (Sensor Transmission Control Protocol)
PORT (Price-Oriented Reliable Transport Protocol) PSFQ (pump slow fetch
quick).
B. Network layer:
The major function of this layer is routing. This layer has a lot of challenges
depending on the application but apparently, the major challenges are in the power
saving, limited memory and buffers, sensor does not have a global ID and have to
be self organized.
C. Data link layer:

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Responsible for multiplexing data streams, data frame detection, MAC, and error
control, ensures reliability of point–point or point– multipoint. Errors or
unreliability comes from:
Co- channel interference at the MAC layer and this problem is solved by
MAC protocols.
Multipath fading and shadowing at the physical layer and this problem is
solved by forward error correction (FEC) and automatic repeat request
(ARQ).
D. Physical layer:
Can provide an interface to transmit a stream of bits over physical medium.
Responsible for frequency selection, carrier frequency generation, signal detection,
Modulation and data encryption.
E. Application layer:
Responsible for traffic management and provide software for different applications
that translate the data in an understandable form or send queries to obtain certain
information. Sensor networks deployed in various applications in different fields,
for example; military, medical, environment, agriculture fields.
F. MAC layer:
Responsible for Channel access policies, scheduling, buffer management and
error control. In WSN we need a MAC protocol to consider energy efficiency,
reliability, low access delay and high throughput as major priorities.
Different Networking Technologies for Wireless Sensor Networks:
A. Bluetooth:
IEEE 802.15.1 standard, popularly known as Bluetooth, offers moderate data rates
at lower energy levels. Due to this, it is ideally suited for high end WSN
applications that require higher data rates with harder real time constraints.

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Bluetooth is used in star topology because of its basic characteristics. Bluetooth
devices communicate with each other using set of standard Bluetooth profiles
defined by standard body.
B. ZigBee:
IEEE 802.15.4 standard, popularly known as ZigBee, offers low data rates at very
low energy levels. Due to this, it is ideally suited for applications requiring
infrequent smaller data transfers where battery life is an important issue. However,
location estimation based on narrow band DSSS can achieve accuracy only in the
order of several meters.
ZigBee coordinator is responsible for managing the network and supervising
network formation; ZigBee routers have routing capabilities and they are
responsible for linking group of end devices or routers; and ZigBee end devices are
simple network end points capable of communicating with other devices in the
network.
C. UWB:
Ultra wide band is a technology for transmitting information spread over a large
bandwidth (>500 MHz) and it is ideally suited for short distance, high speed
communications with very low power budget. As it is based on wide band
technology, it can achieve very high geo-location accuracy to the sub-meter levels.
UWB provides one of the best options for WSN networking only limited by its
shorter range.
D. Wi-Fi:
Wi-Fi represents group of WLAN technologies defined under IEEE 802.11
standard body. In addition to transmission standards like 802.11a/b/g/n, it also
includes 802.11s standard for mesh networking. Wi-Fi technologies are capable of
providing very high throughput (>100 Mbps) at longer range but required very
high power budget. Also, Wi-Fi can locate end point location to the accuracy of
several meters only. Because of this limitation, use of Wi-Fi is mostly restricted to
devices with fixed power supply.

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Wireless Sensor Networks vs. Ad Hoc Networks (MANET):
WSN MANET
Applications and
equipments
 Small sensor nodes with constrained
hardware and energy supply.
 In general, unattended operation
 Powerful nodes with large
batteries(laptops)
 In general, more
elaborate
Applications.e.g VoIP, with
human interaction.
Redundancy  High  Low
Data rate  Low  High
Application specific  Infinite number of application in terms of
devices,protocols,density etc.
 Although, a few scenarios
not as many as in wsns.
Environment
interaction
 Lot of environmental interactions
 Low data rates, but also data bursts –new
traffic patterns
 More conventional human
driven applications with
well understood traffic
characteristics.
Scale  Huge amount of sensor nodes-more
scalable solutions required(e.g. protocols
without node identifiers)
 Significantly less nodes
than in wsns.
Energy  Tighter requirements, mostly no recharge
or replacement of batteries possible
 Energy constrained, but
often energy can be
recharged
Self Configurability  Almost equal to MANETs, but different data
traffic and energy trade -offs.
 One of the main features
in MANETs
Dependability and
QoS
 Individual node is irrelevant as long as
network is working
 New QoS concepts necessary.
 Each node should be
reliable
 Qos determined by
applications such as VoIP
jitter.
Data centric  Redundant deployment makes data centric
protocols attractive.
 Slightly limited resources,
but in general normal os
and applications can run
on the nodes.
Simplicity &  Os and s/w must be simpler than on  Slightly limited resources,

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18scarceness ‘normal’ PCs
 Breaking of strict network layers isolation
to achieve simplicity
but in general normal os
and application can run on
the nodes
mobility  Mostly stationary use, but movement for
certain applications possible e.g. tracking
applications
 Movement can be correlated e.g. sensors
carried by a river
 One of the main features
of MANETs-caused by
moving nodes
 Movement can be
correlated by moving
groups
Advantages of WSN:
1. Implementation cost is cheaper than wired network.
2. Ideal for temporary network setups.
3. Ideal for the non reachable such as across river or mountains or rural
areas.
Challenges of WSN:
1. Lower speed compared to wired network.
2. Less secure because hacker's laptop can act as access point.
3. More complex to configure than wired network.
4. Can be affected by surrounding's. For example, walls(blocking),
Microwave oven (interference), far distance.
5. Sensor node has low battery power, so as battery goes down, node
Goes down and so does the whole network.
6. Like any other wireless technology, it is easy for hackers to hack WSNs. For most
of the applications security & integrity of data is most important hence we have to
select networking technology as well as security algorithms accordingly.
7. Due to limited resources and dynamic topology, it is very difficult to design a
reliable routing scheme for WSNs.
8. Quite a few applications like solar energy monitoring, irrigation and air quality
monitoring are associated with harsh environments. Independent of enclosure
design, sensors will be exposed to the outdoor conditions and it is extremely

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19crucial to take environmental conditions into consideration while designing WSN
system.
9. Dynamic topologies and integration with internet affect factors like Quality-of-
service requirements, security, packet errors and variable-link capacity.
10. Energy conservation is a very critical part of WSN because of small battery
size. We need to look at traffic scheduling as well as remote wake-up features to
optimize power consumption.
Conclusion:
In this paper, I presented the state of the art of wireless sensor networks; their
architecture, routing protocols for WSNs, their applications. Also, in this paper, we
introduced Also, in this paper; a brief review of the application based on wireless sensor
networks is given. Also I introduced the difference between ad hoc networks and wsn.
Finally, our directions and recommendations for wireless sensor network management
are suggested.
References:
 Safari magazine
 Google.com
 Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal, Wireless sensor
network survey, Elsevier Computer Networks 52 (2008) 2292–2330
 Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam, and Erdal
Cayirci, A Survey on Sensor Networks, IEEE Communications Magazine,
August 2002
 Slideshare.com ->wireless sensor networks
 Wiki pedia
 Abrach, H., S. Bhatti, J. Carlson, H. Dai, J. Rose, A. Sheth, B. Shucker, J. Deng
and R. Han.MANTIS: System support for multimodal networks of in-situ sensors.
In: 2nd ACM International Workshop on Wireless Sensor
Networks and Applications, September, San Diego, USA, pp: 50-59. DOI:
10.1145/941350.941358.

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References download:
[1] AdiWirelessOS.pdf
[2] Summary of all os.pdf
[3] Challenges in sensor networks
[4] Disadvantages of wsn
[5] Wsn vs. adhoc network

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