Features of wsn and various routing techniques for wsn a survey

IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
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Volume: 01 Issue: 03 | Nov-2012, Available @ http://www.ijret.org 348
FEATURES OF WSN AND VARIOUS ROUTING TECHNIQUES FOR
WSN: A SURVEY
Parul Bakaraniya1
, Sheetal Mehta2
1
M.E. Computer Engineering, Parul Institute of Engineering and Technology, Gujarat, INDIA,parul9980@yahoo.com
2
Asst. Prof. (CSE), Parul Institute of Engineering and Technology, Gujarat, INDIA,prof.sheetal.mehta@gmail.com
Abstract
A Wireless Sensor Network is the collection of large number of sensor nodes, which are technically or economically feasible and
measure the ambient condition in the environment surrounding them. The difference between usual wireless networks and WSNs is
that sensors are sensitive to energy consumption. Most of the attention is given to routing protocols, for energy awareness, since they
might differ depending on the application and network architecture. Routing techniques for WSN are classified into three categories
based on network structure: Flat, hierarchical and location-based routing. Furthermore, these protocols can be classified into multi-
path based, query based, negotiation-based, QoS-based, and coherent–based, depending on the protocol operation. In this paper the
survey of routing techniques in WSNs is shown. It is also outlined the design challenges and performance metrics for routing
protocols in WSNs. Finally We also highlight the advantages and performance issues of different routing techniques by it’s
comparative analysis. Future-directions for routing in sensor network is also described.
Index Terms: Wireless sensor network, Routing techniques, Routing challenges and future directions.
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1. INTRODUCTION
A sensor network is defined as being composed of a large
number of nodes with sensing, processing and communication
facilities which are deployed either inside the phenomenon or
very close to it. Each of these nodes collects data and route
this information back to a sink. The network must possess
self-organizing capabilities since the positions of individual
nodes are not predetermined. Cooperation among nodes is the
dominant feature of this type of network, where groups of
nodes cooperate to disseminate the information gathered in
their vicinity to the user [1] as shown in fig 1. As it is shown
here there are several sensor nodes scattered randomly and the
data content of individual sensor nodes gets collected in the
sink. Then through internet the user can view the data
collected by the network. A sensor node is made up of four
basic components as shown in the figure a sensing unit,
including one or more sensors for data acquisition[12], a
processing unit, a transceiver unit and a power unit. They may
also have application dependent additional components such
as a location finding system, a power generator and a
mobilizer. Sensing units are usually composed of two
subunits: sensors and analog to digital converters (ADCs). The
analog signals produced by the sensors based on the observed
phenomenon are converted to digital signals by the ADC, and
then fed into the processing unit. The processing unit, which is
generally associated with a small storage unit, manages the
procedures. A transceiver unit connects the node to the
network. One of the most important components of a sensor
node is the power unit. Power units may be supported by a
power scavenging unit such as solar cells.
Fig-1: The components of a sensor node [1]
Sensor networks may consist of many different types of
sensors such as seismic, low sampling rate magnetic, thermal,
visual, infrared, acoustic and radar. Applications of the WSNs
include to monitor a wide variety of ambient conditions like
temperature, humidity, vehicular movement, lightning
condition, pressure, soil makeup, noise levels, In Military for
target field imaging, Earth Monitoring, Disaster management.
Fire alarm sensors, Sensors planted underground for precision
agriculture, intrusion detection and criminal hunting [1][5].

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2. ROUTING CHALLENGES AND DESIGN
ISSUES IN WSNs
Here is a list of the most common factors affecting the routing
protocols design [1][3][7]:
• Node Deployment: It is an application-dependent operation
affecting the routing protocol performance, and can be either
deterministic or randomized.
• Node/Link Heterogeneity: The existence of heterogeneous
set of sensors gives rise to many technical problems related to
data routing and they have to be overcome.
• Data Reporting Model: Data sensing, measurement and
reporting in WSNs depend on the application and the time
criticality of the data reporting. Data reporting can be
categorized as either time-driven (continuous), event driven,
query-driven, and hybrid.
• Energy Consumption Without Losing Accuracy: Sensor
nodes can use up their limited supply of energy to perform
computations and to transmit information. Sensor node
lifetime shows a strong dependence on battery lifetime [1].
The malfunctioning of some sensor nodes due to power failure
can cause significant topological changes.
• Scalability:. WSNs routing protocols should be scalable
enough to respond to events like huge increase of sensor
nodes, in the environment
• Network Dynamics: Mobility of sensor nodes is necessary in
many applications, like moving target monitoring.
• Transmission Media: In a multi-hop WSN, communicating
nodes are linked by a wireless medium. One approach of
MAC design for sensor networks is to use TDMA based
protocols that conserve more energy compared to contention-
based protocols like CSMA.
• Coverage: In WSNs, a given sensor’s view of the
environment is limited both in range and in accuracy; it can
only cover a limited physical area of the environment.
• Quality of Service: Data should be delivered within a certain
period of time. However, in a good number of applications,
conservation of energy, which is directly related to network
lifetime, is considered relatively more important than the
quality of data sent. Hence, energy aware routing protocols are
required to capture this requirement.
• Data Aggregation: Data aggregation is the combination of
data from different sources according to a certain aggregation
function, e.g. duplicate suppression.
2.1 Performance Metrics Of Routing In WSNs
The performance of the network is then measured based on
quantifiable parameters called performance metrics [2][3][13]
•Network Lifetime: Network lifetime is defined as the number
of data aggregation rounds till x % of sensors die where x is
specified by the system designer. For instance, in applications
where the time that all nodes operate together is vital, lifetime
is defined as the number of rounds until the first sensor is
drained of its energy.
•Data accuracy: The definition of data accuracy depends on
the specific application for which the sensor network is
designed. For instance, in a target localization problem, the
estimate of target location at the sink determines the data
accuracy.
• Latency: Latency is defined as the delay involved in data
transmission, routing and data aggregation. It can be measured
as the time delay between the data packets received at the sink
and the data generated at the source nodes.
•Average Energy Dissipated: This metric shows the average
dissipation of energy per node over time in the network.
•Total Number of Nodes Alive: This metric is also related to
the network lifetime. It gives an idea of the area coverage of
the network over time.
•Bandwidth, Capacity and Throughput: These indicate the
capacity of data which can be sent over a link within a given
time, however since the data size is very small bandwidth
rarely matters.
•Hop Count: No of hop in communication determine the cost
of path, and eventually the energy consumed in the process.
3. ROUTING PROTOCOLS BASED ON
NETWORK STRUCTURE
In this section we survey the routing protocols for WSNs. In
general, routing in WSNs can be divided into flat-based
routing (data-centric routing), hierarchical-based routing, and
location-based routing depending on the network
structure.(fig. 2) In flat-based routing, all nodes are typically
assigned equal roles or functionality. In hierarchical-based
routing, nodes will play different roles in the network. In
location-based routing, sensor nodes’ positions are exploited
to route data in the network. Furthermore, these protocols can
be classified into multipath-based, query-based, and
negotiation-based, QoS-based, or coherent-based routing
techniques depending on the protocol operation[2][14].
Routing protocols can be classified into three categories,
proactive, reactive, and hybrid, depending on how the source
finds a route to the destination. In proactive protocols, all
routes are computed before they are really needed, while in
reactive protocols, routes are computed on demand. Hybrid
protocols use a combination of these two ideas. When sensor
nodes are static, it is preferable to have table-driven routing
protocols rather than reactive protocols. A significant amount
of energy is used in route discovery and setup of reactive
protocols[1]. Another class of routing protocols is called
cooperative. In cooperative routing, nodes send data to a
central node where data can be aggregated and may be subject
to further processing, hence reducing route cost in terms of
energy use.

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Fig- 2: Routing protocols in WSN [1]
3.1 Data-Centric Protocols
In data-centric routing, the sink sends queries to certain
regions and waits for data from the sensors located in the
selected regions. Since data is being requested through
queries, attribute based naming is necessary to specify the
properties of data. SPIN is the first data-centric protocol,
which considers data negotiation between nodes in order to
eliminate redundant data and save energy [5]. Later, Directed
Diffusion has been developed . Then, many other protocols
have been proposed either based on Directed Diffusion or
following a similar concept [7]. This section describes these
protocols in details.
1)Sensor Protocols for Information via Negotiation (SPIN) :
The idea behind SPIN is to name the data using high level
descriptors or meta-data. Before transmission, meta-data are
exchanged among sensors via a data advertisement
mechanism, which is the key feature of SPIN. Each node upon
receiving new data, advertises it to its neighbors and interested
neighbors, means those who do not have the data, retrieve the
data by sending a request message. SPIN's meta-data
negotiation solves the classic problems of flooding such as
redundant information passing, overlapping of sensing areas
and resource blindness thus, achieving a lot of energy
efficiency. There is no standard meta-data format and it is
assumed to be application specific. There are three messages
defined in SPIN to exchange data between nodes. These are:
ADV message to allow a sensor to advertise a particular meta-
data, REQ message to request the specific data and DATA
message that carry the actual data. Details of it can be studied
from [5] .In SPIN, topological changes are localized since
each node needs to know only its single-hop neighbors. SPIN
is not used for applications such as intrusion detection, which
require reliable delivery of data packets over regular intervals.
2) Directed Diffusion(DD): DD is an important milestone in
the data-centric routing research of sensor networks. The idea
aims at diffusing data through sensor nodes by using a naming
scheme for the data. DD suggests the use of attribute-value
pairs for the data and queries the sensors in an on demand
basis by using those pairs. In order to create a query, an
interest is defined using a list of attribute-value pairs such as
name of objects, interval, duration, geographical area, etc. The
interest is broadcast by a sink through its neighbors. Each
node receiving the interest can do caching for later use. The
nodes also have the ability to do in-network data aggregation.
The interests in the caches are then used to compare the
received data with the values in the interests. The interest
entry also contains several gradient fields. A gradient is a
reply link to a neighbor from which the interest was received.
Hence, by utilizing interest and gradients, paths are
established between sink and sources. Several paths can be
established so that one of them is selected by reinforcement.
DD is highly energy efficient since it is on demand and there
is no need for maintaining global network topology. However,
DD can not be applied to all sensor network applications since
it is based on a query-driven data delivery model[1].Details of
DD can be studied from [5].
3) Rumor Routing (RR): RR is a compromise between
flooding queries and flooding event notifications. The main
idea of this protocol is to create paths that lead to each event ,
unlike event flooding which creates a network-wide gradient
field. Thus, in case that a query is generated it can be then sent
on a random walk until it finds the event path, instead of
flooding it throughout the network. As soon as the event path
is discovered it can be further routed directly to the event. On
the other hand, if the path cannot be found, the application can
try re-submitting the query or flooding it. The RR can be a
good method for delivering queries to events in large networks
[3].
3.2 Hierarchical Protocols
The main aim of hierarchical routing is to efficiently maintain
the energy consumption of sensor nodes by involving them in
multi-hop communication within a particular cluster. Here
data aggregation and fusion is performed in order to decrease
the number of transmitted messages to the sink. Here all nodes
get a chance to become cluster head for the cluster period[15].
Cluster formation is typically based on the residual energy of
sensors and sensor’s proximity to the cluster head . LEACH is
one of the widely used hierarchical routing protocol for
sensors networks. We explore hierarchical routing protocols in
this section.
1) Low-Energy Adaptive Clustering Hierarchy (LEACH) : It
is one of the most popular hierarchical routing algorithm. The
idea is to form clusters of the sensor nodes based on the
received signal strength and use local cluster heads(CHs) as
routers to the sink. This will save energy since the
transmissions will only be done by CHs rather than all sensor
nodes. Optimal number of CHs is estimated to be 5% of the
total number of nodes[1]. All the data processing such as data

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fusion and aggregation are local to the cluster. CHs change
randomly over time in order to balance the energy dissipation
of nodes. This decision is made by the node by choosing a
random number between 0 and 1. The node becomes a CH for
the current round if the number is less than the following
threshold:
Gn
p
rmodp
p
nT 
 )
1
)((1
=)(
otherwise0=)(nT
Where p is the desired percentage of CHs , r is = the current
round, and G is the set of nodes that have not been selected as
cluster heads in the last 1/p rounds[1]. LEACH achieves over
a factor of 7 reduction in energy dissipation compared to
direct communication and a factor of 4-8 compared to the
minimum transmission energy routing protocol[8]. The nodes
die randomly and dynamic clustering increases lifetime of the
system.
2) Power-Efficient GAthering in Sensor Information Systems
(PEGASIS):It is an improvement of the LEACH protocol.
Rather than forming multiple clusters, PEGASIS forms chains
from sensor nodes so that each node transmits and receives
from a neighbor and only one node is selected from that chain
to transmit to the base station (sink). Gathered data moves
from node to node, aggregated and eventually sent to the base
station. The chain construction is performed in a greedy way,
as shown in Fig. 3.
n0→n1→n2←n3←n4
BS
Fig. 3: chaining in PEGASIS
PEGASIS has been shown to outperform LEACH by about
100 to 300% for different network sizes and topologies[5].
However, PEGASIS introduces excessive delay for distant
node on the chain. Hierarchical-PEGASIS solves this problem
3)Threshold sensitive Energy Efficient sensor Network
protocol (TEEN): It is a hierarchical protocol designed to be
responsive to sudden changes in the sensed attributes such as
temperature. The sensor network architecture is based on a
hierarchical grouping where closer nodes form clusters and
this process goes on the second level until base station is
reached. The model is depicted in Fig. 4
Fig- 4: Hierarchical clustering in TEEN and APTEEN [5]
After the clusters are formed, the cluster head broadcasts two
thresholds to the nodes. These are hard and soft thresholds for
sensed attributes. Based on these threshold values , It gives
accurate data[15].However, TEEN is not good for applications
where periodic reports are needed since the user may not get
any data at all if the thresholds are not reached[5]. The
Adaptive Threshold sensitive Energy Efficient sensor Network
protocol (APTEEN) is an extension to TEEN and aims at both
capturing periodic data collections and reacting to time-critical
events [9] [15].
3.3 Location-Based Protocols
In this section, location-based protocols for WSNs, is
presented. They are based on two principal assumptions [3]:
• It is assumed that every node knows its own network
neighbors positions.
• The source of a message is assumed to be informed about the
position of the destination.
1)Distance Routing Effect Algorithm for Mobility (DREAM):
It is a proactive protocol and each Mobile Node (MN)
maintains a location table for all other nodes in the
network[3]. To maintain the table, each MN transmits location
packets to nearby MNs in the sensor network at a given
frequency and to far away MNs in the sensor network at
another lower frequency. Since far away MNs appear to move
more slowly than nearby MNs, it is not necessary for a MN to
maintain up-to-date location information for far away MNs.
Thus, by differentiating between nearby and far away MNs,
DREAM attempts to limit the overhead of location packets.
2) Geographic and Energy Aware Routing (GEAR): Unlike
previous geographic routing protocols, GEAR does not use
greedy algorithms to forward the packet to the destination
[10]. Thus, it differs in how they handle communication holes.
The GEAR uses energy aware and geographically informed
neighbor selection heuristics to route a packet towards the
target region. Two main characteristics of this protocol are :

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• When a closer neighbor to the destination exists GEAR picks
a next-hop node among all neighbors that are closer to the
destination.
• When all neighbors are further away, there is a hole. GEAR
picks a next-hop node that minimizes some cost value. The
main advantage of the GEAR is that each node knows its own
location and remaining energy level, and its neighbors
locations and remaining energy levels through a simple
neighbor hello protocol. Also it attempts to balance energy
consumption and thereby increase network lifetime.
3) Minimum Energy Relay Routing (MERR) - Location: It is
based on the idea that the distance between two nodes that
transmit data is very important [11]. This distance is closely
related to the energy consumed on the entire path, from the
source to the base station, Thus, in MERR each sensor seeks
locally for the downstream node within its maximum
transmission range whose distance is closest to the
characteristic distance. As soon as a sensor has decided to use
the next hop, it adjusts its transmission power to the lowest
possible level such that the radio signal can just be received by
the respective node. This can minimize the energy
consumption. If the distances between each pair of sensors are
all greater than the characteristic distance, each sensor will
select its direct downstream neighbor as the next hop node.
The MERR works well when the sensors are deployed over a
linear topology and sends data to a single control center.
Whereas, minimizing transmit energy means that it chooses
the nearest neighbor as router. So, a large amount of energy is
wasted in case that the nodes happen to be very close to each
other.
ROUTING PROTOCOLS BASED ON PROTOCOL
OPERATION
In this section we review routing protocols with different
routing functionality. It should be noted that some of these
protocols may fall under one or more of the above routing
categories [1].
1)Multipath Routing Protocols--- It includes the algorithms
that routes the data through a path whose nodes have the
largest residual energy. The path is changed whenever a better
path is discovered. DD is this kind of protocol [5].
2) Query-Based Routing — Here, the destination nodes
propagate a query for data from a node through the network,
and a node with this data sends the data that matches the query
back to the node that initiated the query. Usually queries are
described in natural language or high-level query languages.
DD and RR protocol are examples of this type of routing.
3) Negotiation-Based Routing Protocols — These protocols
use high-level data descriptors to eliminate redundant data
transmissions through negotiation. The SPIN protocols are
examples of negotiation-based routing protocols.
4) QoS-based Routing — Here, the network has to balance
between energy consumption and data quality. The network
has to satisfy certain QoS metrics (delay, energy, bandwidth,
etc.) when delivering data to the BS. Sequential Assignment
Routing (SAR) and SPEED are this type of protocols.
5) Coherent and Noncoherent Processing —These are data-
processing based routing. In noncoherent data processing
routing, nodes will locally process the raw data before it is
sent to other nodes for further processing. In coherent routing,
the data is forwarded to aggregators after minimum processing
like time stamping and duplicate suppression. To perform
energy-efficient routing, coherent processing is normally
selected. Single Winner Algorithm (SWE) and Multiple
Winner Algorithm are the examples of non-coherent and
coherent data processing, respectively.
5. FUTURE DIRECTIONS OF ROUTING IN WSN
Future trends in routing techniques in WSNs focus on
different directions, all share the common objective of
prolonging the network lifetime. We summarize some of these
directions as follows [4]:
A. Tiered architectures (mix of form/energy factors):
Hierarchical routing is an old technique to enhance scalability
and efficiency of the routing protocol. However, novel
techniques to network clustering which maximize the network
lifetime are also a hot area of research in WSNs [1].
B. Time and location synchronization
Energy-efficient techniques for associating time and spatial
coordinates with data to support collaborative processing are
also required.
C. Self-configuration and reconfiguration are essential to the
lifetime of unattended systems in a dynamic and energy
constrained environment. This is important for keeping the
network up and running.
D. Localization: Sensor nodes are randomly deployed into an
unplanned infrastructure. The problem of estimating spatial
coordinates of the node is referred to as localization. GPS
cannot be used in WSNs as GPS receivers are expensive.
Hence, there is a need to develop other means of establishing a
coordinate system.
E. Exploit spatial diversity and density of sensor/actuator
nodes: Nodes will span a network area that might be large
enough to provide spatial communication between sensor
nodes. Achieving energy-efficient communication in this
densely populated environment deserves further investigation.
F. Secure routing: protocols have not been designed with
security as a goal, it is important to analyze their security
properties. One aspect of sensor networks that complicates the
design of a secure routing protocol is in-network
aggregation[1][4].
6. COMPARATIVE ANALYSIS
Comparative analysis of certain techniques has been shown in
the following Table-I, II and III.

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Table-1: Comparison of Data-Centric Routing Schemes
Name of
the
Protocol
Route
Metric
Mobility Advantages Disadvanta
ge/Issues
SPIN Each node
sends data
to its
single hop
neighbors
Yes simplicity,
implosion
avoidance and
the minimal
start up cost
It does not
guaranty the
delivery of the
data and
consumes
unnecessary
power
DD The Best
Path
Limited It extends the
network
lifetime
It can’t be
used for
Continuous
Data delivery
or event
driven
applications
RR Shortest
Path
Low It is able to
handle node
failure
gracefully,
degrading its
delivery rate
linearly with
the number of
failed nodes
It may deliver
duplicated
messages to
the same
node
Table-2: Comparison of Hierarchical Routing Schemes
Name of
the
Protocol
Route
Metric
Mobility Advantages Disadvantag
e/Issues
LEACH Shortest
Path
Fixed BS (1) Low
energy,
distributed
dynamic
clustering
protocol so
increases
network
lifetime
(2) it achieves
over a factor
of 7and 4-8
reduction in
energy
dissipation
compared to
direct
communicatio
n and MTE
routing
protocol
(1) It is not
applicable to
networks
deployed in
large regions
and the
dynamic
clustering
brings extra
overhead
(2) The CHs are
randomly
selected and
CHs in the
network are not
uniformly
distributed
(3)All nodes
have same
initial energy
Including CH.
PEGASIS Greed
route
selection
Fixed BS The
transmitting
distance for
most of the
node is
reduced
Base station’s
location and the
energy of nodes
are not
considered
when one of the
nodes is
selected as the
head node
TEEN The best
route
Fixed BS (1)It works
well in the
conditions like
sudden
changes in the
sensed
attributes such
as temperature
(2) TEEN is
better than
LEACH and
APTEEN
because it
reduces
number of
transmissions.
(1) A lot of
energy
consumption
and overhead in
case of large
network
(2) overhead
with forming
clusters at
multiple levels
APTEEN The best
route
Fixed BS Low energy
consumption
(1)Long delay
(2) overhead
with forming
clusters at
multiple levels
Table-3: Comparison of Location-based Routing Schemes
Name
of the
Proto
col
Route
Metric
Mobil
ity
Advantages Disadvantage/Is
sues
DREA
M
The Path
that
minimize
total
power
consumpti
on
Good Efficient data
packet
transmission
The waste of
network bandwidth
due to
differentiating
between nearby and
far away MNs
GEAR The best
route
Limite
d
It attempts to
balance energy
consumption and
thereby increases
the network
lifetime
The periodic table
exchange
MERR The Path
that
minimize
total
power
consumpti
on
Low It distributes the
energy
consumption of
the sensors
uniformly to the
network sensors
It chooses the
nearest neighbor as
router. Thus, a large
amount of energy is
wasted in case that
the nodes happen to
be very close to
each other.

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CONCLUSIONS
Routing in sensor networks is an emerging area of research. In
this paper we present a comprehensive survey of routing
techniques in wireless sensor networks .Overall, the routing
techniques are classified based on the network structure into
three categories: flat, hierarchical, and location-based routing
protocols. Furthermore, these protocols are classified into
multipath-based, query-based, negotiation-based, and QoS-
based routing techniques depending on protocol operation.
Comparative analysis of different protocols is also shown here
and the design challenges and future directions for routing in
sensor network is also described.
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BIOGRAPHIES:
Parul Bakaraniya received her B.E.
(Computer Engineering) degree in 2002
from Maharaja Sayajirao University,
Baroda, India. Currently she is persuing
her M.E (Computer Engineering) from
P.I.E.T., Waghodia, India. Her Area of
research is Wireless Sensor Network.
E-mail: parul9980@yahoo.com
Sheetal Mehta received her
B.E.(Computer Engineering) degree in
2009 from Gujarat Technological
University, P.I.E.T., Waghodia, India. She
received her M.tech(Computer
Engineering) degree in 2011 from Institute
of Technology, Nirma
University,Ahmedabad, India. She is Asst.
Prof.(CSE) in P.I.E.T., Waghodia, India. Her area of research
are Wireless Sensor Network, Mobile Ad-hoc Networks. E-
mail: prof.sheetal.mehta@gmail.com

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