Routing Protocols in Wireless Sensor Networks1-A Survey.pdf

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Routing Protocols in Wireless Sensor Networks: A Survey

Deepak GoyalAssistant professorVaish college of Engineering, Rohtak, IndiaEmail id: [email protected]

Malay Ranjan TripathyProfessorAmity University, Noida, India

Abstract

Extensive usage of wireless sensor network (WSN) is the

reason of development of many routing protocols. Recent

advances in WSN now witness the increased interest in the

potential use in applications like Military, Environmental,

Health (Scanning), Space Exploration, Vehicular

Movement, Mechanical stress levels on attached objects,

disaster management, combat field reconnaissance etc.

Sensors are expected to be remotely deployed in

unattended environments. Routing as one key

technologies of wireless sensor network has now become

a hot research because the applications of WSN iseverywhere, it is impossible that there is a routing

protocol suitable for all applications. In this paper, the

various routing protocol are classified and described. The

growing interest in WSN and the continual emergence of

new architectural techniques inspired surveying the

characteristics, applications and communication protocols

for such a technical area.

1 Introduction

Large number of heterogeneous Sensor devices

spread over a large field. Wireless sensing and Data

Networking Group of sensors linked by wireless

media to perform distributed sensing tasks. A sensor

Network is the group of sensors attached to

transducers intends to monitor the conditions at

diverse locations. The Sensors are meant to measure

the physical or environmental changes. The sensor

commonly measure pressure, Chemical reactions,

sound intensity and temperature etc [1]. A Wireless

Sensor Network (WSN) consists of spatially

distributed autonomous sensors to monitor physical

or environmental conditions, such as temperature,

sound, vibration, pressure, motion or pollutants and

to cooperatively pass their data through the network

to a main location. The more modern networks are

bi-directional, enabling also to control the activity ofthe sensors. The development of wireless sensor

networks was motivated by military applications

such as battlefield surveillance; today such networks

are 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.

The WSN is built of nodes - from a few to several

hundreds or even thousands, where each node is

connected to one (or sometimes several) sensors.

Each such sensor network node has typically several

parts: a radio transceiver with an internal antenna or

connection to an external antenna, a

microcontroller, an electronic circuit for interfacing

with the sensors and an energy source, usually a

battery[2]. A sensor node might vary in size from

that of a shoebox down to the size of a grain of dust,

although functioning "motes" of genuinemicroscopic dimensions have yet to be created. The

cost of sensor nodes is similarly variable, ranging

from hundreds of dollars 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 bandwidth. The topology of the

WSNs can vary from a simple star network to an

advanced multi-hop wireless mesh network. The

propagation technique between the hops of the

network can be routing or flooding [3].

2 Sensor Network and Nodes

Network Channels: User nodes or gateways and

onward transmission to other network [4] [5].

Sensor channels: Communicates among sensor

nodes and targets.

Sensor Network has three types of Nodes

Sensor Nodes: Monitor immediate environment

Target Nodes: Generates various stimuli for

sensor nodes.

User Nodes: Client and Administration of Sensor

Networks.

3 Routing Protocols in WSN

Location-based Protocols:-MECN, SMECN, GAF,

GEAR, Span, TBF, BVGF, GeRaF

Data-centric Protocols: - SPIN, Directed Diffusion,

Rumor Routing, COUGAR, ACQUIRE, EAD

Hierarchical Protocols:-LEACH, PEGASIS, HEED,

TEEN, APTEEN

Multipath-based Protocols: -Disjoint Paths, Braided

paths, N-to-1 Multipath Discovery

2012 Second International Conference on Advanced Computing & Communication Technologies

978-0-7695-4640-7/12 $26.00 2012 IEEE

DOI 10.1109/ACCT.2012.98

478

2012 Second International Conference on Advanced Computing & Communication Technologies

978-0-7695-4640-7/12 $26.00 2012 IEEE

DOI 10.1109/ACCT.2012.98

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QoS-based protocols: - SAR, SPEED, Energy-aware

routing

3.1 Location-based Protocols

In location-based protocols as described in table 1,

sensor nodes are addressed by means of their

locations. Location information for sensor nodes is

required for sensor networks by most of the routing

protocols to calculate the distance between two

particular nodes so that energy consumption can be

estimated.

Protocol Description (Location-based Protocols) (table 1) Advantages Disadvantages

Geographic

Adaptive

Fidelity

(GAF)

This is an energy-aware routing protocol in WSNs because it favors

energy conservation. Based on an energy model that considers

energy consumption due to the reception and transmission of

packets [6].

Energy conservation Processing

overhead

Geographic

and Energy-

Aware

Routing

(GEAR):

Energy-efficient routing protocol proposed for routing queries to

target regions in a sensor field, sensors are aware of their residual

energy as well as the locations and residual energy of each of their

neighbors[7].

Recursive geographic

forwarding algorithm to

disseminate the packet

inside the target region

Lifetime

depletion

Span Its goal is to reduce energy consumption. Span helps sensors to join a

forwarding backbone topology as coordinators that will forward

packets on behalf of other sensors between any source and

destination

Interfacing or power

saving

Single point

of failure

Trajectory-

Based

Forwarding

(TBF):

Requires a sufficiently dense network and the presence of a

coordinate system [8]. For example, a GPS, so that the sensors can

position themselves and estimate distance to their neighbors.

indicate the path on a hop-by-hop basis

It can be used for

implementing

networking functions,

For example, flooding,

discovery, and network

management.

Costly to

implement

Bounded

Voronoi

Greedy

Forwarding

[BVGF]

Greedy geographic routing, a sensor will always forward a packet to

the neighbor that has the shortest distance to the destination. The

sensors eligible for acting as the next hops are the ones whose

Voronoi regions are traversed by the segment line joining the source

and the destination.

Shortest distance can

be calculated using

Euclidian distance

suffer from

battery

power

Depletion.

Geographic

Random

Forwarding

(GeRaF)

Geographic routing where a sensor acting as relay is not known a

priori by a sender. There is no guarantee that a sender will always be

able to forward the message toward its ultimate destination, that is,

the sink. Best-effort forwarding RTS/ a CTS message mechanism are

employed [9].

Backoff time increases

the reliability.

User

involvement

in each

stage is

required

Minimum

Energy

Communicat

ion Network

(MECN)

Achieving minimum energy for randomly deployed ad hoc networks,

computes an optimal spanning tree rooted at the sink, called

minimum power topology, which contains only the minimum power

paths from each sensor to the sink [10].

Self-configuring

Optimal spanning

Fault tolerant

Application

specific

Fault

tolerant

Small

Minimum-

Energy

Communicat

ion Network

(SMECN)

A routing protocol proposed to improve MECN, in which a minimal

graph is characterized with regard to the minimum energy property.

This property implies that of sensors.

A minimum energy-

efficient path between

nodes

No. of

broadcast

messages is

large

3.2 Data Centric Protocols

In data-centric protocols as described in table 2 ,

when the source sensors send their data to the sink,

intermediate sensors can perform some form of

aggregation on the data originating from multiple

source sensors and send the aggregated data toward

the sink. This process can result in energy savings

because of less transmission required to send the

data from the sources to the sink.

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protocol Description (Data Centric Protocols) (table 2) advantages disadvantages

SPIN: Sensor

Protocols for

Information

Negotiation

One of the most dominant forms of routing in the wireless sensor networks

[11].

Uses three types of messages:

ADV advertise data

REQ request for data

DATA data message, contains actual sensor data

SPIN1 and SPIN2

SPIN1: Three way handshaking protocol. ADV, REQ, DATA.

Each sensor node has resource manager, Keeps track of resource consumption

Applications probe the manager before any activity, Cut down activity to save

energy

SPIN2: Energy constraint. Adds energy-conservative heuristic to the SPIN1

protocol. Node initiates three stage protocols, only if it has enough energy to

complete it. If below energy threshold, node can still receive messages, cannot

send/recv DATA messages

Energy aware,

resource

aware and

resource

adaptive

Applies only to

lossless

networks

Not applicable

in mobile links

Directed

Diffusion

Meets the main requirements of WSNs such as energy efficiency, scalability,

and robustness. Directed diffusion has several key elements namely data

naming, interests and gradients, data propagation, and reinforcement [12]. A

sensing task can be described by a list of attribute-value pairs. At the beginning

of the directed diffusion process, the sink specifies a low data rate for incoming

events. After that, the sink can reinforce one particular sensor to send eventswith a higher data rate by resending the original interest message with a

smaller interval. Likewise, if a neighboring sensor receives this interest

message and finds that the sender's interest has a higher data rate than

before, and this data rate is higher than that of any existing gradient, it will

reinforce one or more of its neighbors.

Achieves

synchronizatio

n in networks

More event

handling

More user

interacting

Rumor

Routing

Logical compromise between query floods and event flooding app schemes is

based on the concept of agent, which is a long-lived packet that traverses a

network and informs each sensor it encounters about the events that it has

learned during its network traverse. An agent will travel the network for a

certain number of hops and then die [13].

Efficient

protocol if the

number of

queries is

between the

two

intersection

points of the

curve ofrumor routing

with those of

query flooding

and event

flooding.

Cougar A database approach to tasking sensor networks, provides a user and

application programs with declarative queries of the sensed data generated by

the source sensors [14].

query proxy

provides

higher level

services

through

queries that

can be issued

from a

gateway node

Cannot be

applied directly

to any

network, have

to be modified

ob base on the

application

Energy-

Aware Data-

Centric

Routing

(EAD):

Builds a virtual backbone composed of active sensors that are responsible for

in-network data processing and traffic relaying. In this protocol, a network is

represented by a broadcast tree spanning all sensors in the network and

rooted at the gateway, in which all leaf nodes radios are turned off while all

other nodes correspond to active sensors forming the backbone and thus their

radios are turned on. Specifically, EAD attempts to construct a broadcast tree

that approximates an optimal spanning tree with a minimum number of leaves,

thus reducing the size of the backbone formed by active sensors. EAD approach

is energy aware and helps extend the network lifetime.

Power saving,

Lifetime is

increased.

Gateway

handling

required

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3.3 Hierarchical Protocols

Many research projects in the last few years have

explored hierarchical clustering in WSN from

different perspectives as described in table 3.

Clustering is an energy-efficient communication

protocol that can be used by the sensors to report

their sensed data to the sink. In this section, we

describe a sample of layered protocols in which a

network is composed of several clumps (or clusters)

of sensors. 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 and by

performing data aggregation and fusion in order to

decrease the number of transmitted messages to the

sink. Cluster formation is typically based on theenergy reserve of sensors and sensors proximity to

the cluster head.

Protocol Description (Hierarchical Protocols) (table 3) Advantages Disadvanta

ges

Low-energy

adaptive

clustering

hierarchy

(LEACH)

First and most popular energy-efficient hierarchical clustering algorithm for

WSNs that was proposed for reducing power consumption [15]. In LEACH, the

clustering task is rotated among the nodes, based on duration. Direct

communication is used by each cluster head (CH) to forward the data to the

base station (BS). It uses clusters to prolong the life of the wireless sensor

network. LEACH is based on an aggregation (or fusion) technique that

combines or aggregates the original data into a smaller size of data that carry

only meaningful information to all individual sensors. LEACH divides the a

network into several cluster of sensors, which are constructed by usinglocalized coordination and control not only to reduce the amount of data that

are transmitted to the sink, but also to make routing and data dissemination

more scalable and robust.

Avoids battery

depletion

Does not

guarantee

good CH

distribution

, assumes

uniform

energy

distribution

.

PEGASIS Power-Efficient GAthering in Sensor Information Systems (PEGASIS) 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 [16].

Avoids so

much

clustering,

Increases

lifetime twice.

Requires

dynamical

topology

adjustment

TEEN Hierarchical protocol designed to be responsive to sudden changes in the

sensed attributes such as temperature. Responsiveness is important for time-

critical applications, in which the network operated in a reactive mode. TEEN

pursues a hierarchical approach along with the use of a data-centric

mechanism.

We can adjust

both hard and

soft threshold

values in order

to control thenumber of

packet

transmissions.

not good

for

applications

where

periodicreports are

needed

APTEEN Adaptive Threshold sensitive Energy Efficient sensor Network protocol

(APTEEN) aims at both capturing periodic data collections and reacting to time-

critical events [17]. The architecture is same as in TEEN. When the base station

forms the clusters, the cluster heads broadcast the attributes, the threshold

values, and the transmission schedule to all nodes. Cluster heads also perform

data aggregation in order to save energy. APTEEN supports three different

query types: historical, to analyze past data values; one-time, to take a

snapshot view of the network; and persistent to monitor an event for a period

of time.

APTEENs

performance is

between

LEACH and

TEEN in terms

of energy

dissipation and

network

lifetime.

HEED Hybrid, Energy-Efficient Distributed Clustering (HEED operates in multi-hop

networks, using an adaptive transmission power in the inter-clusteringcommunication. HEED was proposed with four primary goals namely (i)

prolonging network lifetime by distributing energy consumption, (ii)

terminating the clustering process within a constant number of iterations, (iii)

minimizing control overhead, and (iv) producing well-distributed CHs and

compact clusters.

using residual

energy andnode degree or

density as a

metric for

cluster

selection to

achieve power

balancing

Not

suitable forentire

needs of

WSN

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3.4 Multipath-based Protocols

Considering data transmission between source

sensors and the sink, there are two routing

paradigms: single-path routing and multipath

routing. In single-path routing, each source sensor

sends its data to the sink via the shortest path. In

multipath routing, each source sensor finds the first

k shortest paths to the sink and divides its load

evenly among these paths. The protocols are as

described in table 4

Protocol Description (Multipath-based Protocols) (Table 4) Advantages Disadvantages

Disjoint

Paths

Protocol that helps finds a small number of

alternate paths that have no sensor in common with

each other and with the primary path. In sensor-

disjoint path routing, the primary path is best

available whereas the alternate paths are less

desirable as they have longer latency. The disjoint

makes those alternate paths independent of the

primary path [18].

If a failure occurs on the

primary path, it remains local

and does not affect any of

those alternate paths. The

sink can determine which of

its neighbors can provide it

with the highest quality data

characterized by the lowest

loss or lowest delay after the

network has been flooded

with some low-rate samples

more

resilient to

sensor

failures, they

can be

potentially

longer than

the primary

path and

thus less

energy

efficientBraided

Paths

Partially disjoint path from primary one after

relaxing the disjointedness constraint. To construct

the braided multipath, first primary path is

computed. Then, for each node (or sensor) on the

primary path, the best path from a source sensor to

the sink that does not include that node is

computed. Those best alternate paths are not

necessarily disjoint from the primary path and are

called idealized braided multipath

Links of each of the alternate

paths lie either on or

geographically close to the

primary path. Therefore, the

energy consumption on the

primary and alternate paths

seems to be comparable as

opposed to the scenario of

mutually ternate and primary

paths

N-to-1

Multipath

Discovery

N-to-1 Multipath Discovery is based on the simple

flooding originated from the sink and is composed

of two phases, namely, branch aware flooding (or

phase1) and multipath extension of flooding [19].

An active per-hop packet

salvaging strategy can be

adopted to handle sensor

failures and enhance network

reliability

3.5 Network flow and QoS-aware protocols

Although most of the routing protocols proposed for

sensor networks fit our classification, some pursue

somewhat different approach such as network flow

and QoS. In some approaches, route setup is

modeled and solved as a network flow problem.

QoS-aware protocols consider end to end delay

requirements while setting up the paths in the

sensor network.

Maximum lifetime energy routing presents an

interesting solution to the problem of routing in

sensor networks based on a network flow approach.

The main objective of the approach is to maximize

the network lifetime by carefully defining link cost as

a function of node remaining energy and the

required transmission energy using that link. Finding

traffic distribution is a possible solution to the

routing problem in sensor networks and based on

that, comes the name maximum lifetime energy

routing. The solution to this problem maximizes the

feasible time the network lasts. In order to find out

the best link metric for the stated maximization

problem, two maximum residual energy path

algorithms are presented and simulated. The twoalgorithms differ in their definition of link costs and

the incorporation of nodes residual energy.

Minimum cost forwarding protocol aims at finding

the minimum cost path in a large sensor network,

which will also be simple and scalable. The protocol

is not really flow-based, however since data flows

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over the minimum cost path and the resources on

the nodes are updated after each flow, we have

included it in this section. The cost function for the

protocol captures the effect of delay, throughput

and energy consumption from any node to the sink.

There are two phases in the protocol. First phase is a

setup phase for setting the cost value in all nodes. It

starts from the sink and diffuses through the

network. Every node adjusts its cost value by adding

the cost of the node it received the message from

and the cost of the link. Such cost adjustment is not

done through flooding. Instead, a back-off based

algorithm is used in order to limit the number of

messages exchanged. The forwarding of message is

deferred for a preset duration to allow the message

with a minimum cost to arrive. Hence, the algorithm

finds optimal cost of all nodes to the sink by using

only one message at each node. Once these cost

fields are set, there will be no need to keep next hop

states for the nodes. This will ensure scalability. Inthe second phase, the source broadcasts the data to

its neighbors. The nodes receiving the broadcast

message, adds its transmission cost (to sink) to the

cost of the packet. Then the node checks the

remaining cost in the packet. If the remaining cost of

the packet is not sufficient to reach the sink, the

packet is dropped. Otherwise the node forwards the

packet to its neighbors. The protocol does not

require any addresses and forwarding paths.

Simulation results show that the cost values for each

node obtained by the proposed protocol is same as

flooding. As a consequence, optimal forwarding is

achieved with minimum number of advertisementmessages. The average number of advertisement

messages in flooding could be reduced by a factor of

50 using the back off based algorithm with a proper

setting of the back off timer.

SAR: Sequential Assignment Routing (SAR) [20] is the

first protocol for sensor networks that includes the

notion of QoS in its routing decisions. It is a table-

driven multi-path approach striving to achieve

energy efficiency and fault tolerance. The SAR

protocol creates trees rooted at one-hop neighbors

of the sink by taking QoS metric, energy resource on

each path and priority level of each packet into

consideration. By using created trees, multiple paths

from sink to sensors are formed. One of these paths

is selected according to the energy resources and

QoS on the path. Failure recovery is done by

enforcing routing table consistency between

upstream and downstream nodes on each path. Any

local failure causes an automatic path restoration

procedure locally. Simulation results show that SAR

offers less power consumption than the minimum-

energy metric algorithm, which focuses only the

energy consumption of each packet without

considering its priority. SAR maintains multiple paths

from nodes to sink. Although, this ensures fault-

tolerance and easy recovery, the protocol suffers

from the overhead of maintaining the tables andstates at each sensor node especially when the

number of nodes is huge.

SPEED: A QoS routing protocol for sensor networks

that provides soft real-time end-to-end guarantees.

The protocol requires each node to maintain

information about its neighbors and uses geographic

forwarding to find the paths. In addition, SPEED [21]

strive to ensure a certain speed for each packet in

the network so that each application can estimate

the end-to-end delay for the packets by dividing the

distance to the sink by the speed of the packet

before making the admission decision. Moreover,SPEED can provide congestion avoidance when the

network is congested. The routing module in SPEED

is called Stateless Geographic Non-Deterministic

forwarding (SNFG) and works with four other

modules at the network layer, redrawn from The

Beacon exchange mechanism collects information

about the nodes and their location. Delay estimation

at each node is basically made by calculating the

elapsed time when an ACK is received from a

neighbor as a response to a transmitted data packet.

By looking at the delay values, SNGF selects the

node, which meets the speed requirement. If such a

node cannot be found, the relay ratio of the node ischecked. The Neighborhood Feedback Loop module

is responsible for providing the relay ratio which is

calculated by looking at the miss ratios of the

neighbors of a node (the nodes which could not

provide the desired speed) and is fed to the SNGF

module. If the relay ratio is less than a randomly

generated number between 0 and 1, the packet is

dropped. And finally, the backpressure-rerouting

module is used to prevent voids, when a node fails

to find a next hop node, and to eliminate congestion

by sending messages back to the source nodes so

that they will pursue new routes. When compared to

Dynamic Source Routing (DSR) and Ad-hoc on-

demand vector routing (AODV), SPEED performs

better in terms of end-to-end delay and miss ratio.

Moreover, the total transmission energy is less due

to the simplicity of the routing algorithm, i.e. control

packet overhead is less, and to the even traffic

distribution. Such load balancing is achieved through

the SNGF mechanism of dispersing packets into a

large relay area. As explained earlier, similar energy

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Routing Protocols in Wireless Sensor Networks1-A Survey.pdf