ROUTING PROTOCOLS FOR

WSN

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UNIT V

Created by : Neha Birla

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Data Dissemination and Gathering

Dissemination = The act of spreading something,

spreading, distribution.

Gathering = Assemble or collect

1. Data Dissemination

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Process of Distribution of data.

Information flow from one sensor node to another.

The originator of data is known as Source Node and

Receiver of the data is called Sink node or Gateway.

The Sink registers its interest to receive the data from

source. The Source reports the data information to the

Sink. The information thus reported is called event.

Process of Data Dissemination

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The node that is interested in some events, like temperature

or air humidity, broadcasts its interests to its neighbors

periodically. Interests are then propagated through the

whole sensor network.

Nodes that have requested data, send back data after

receiving the request.

Intermediate nodes in the sensor network also keep a cache

of received interests and data.

Data Dissemination Methods

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Flooding

Gossiping

SPIN

1.1 Flooding

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Each node which receives a packet (queries/data) broadcasts it if

the maximum hop-count of the packet is not reached and the node

itself is not the destination of the packet.

Advantage

No costly topology maintenance or route discovery

Disadvantages

Implosion

Overlapping

Resource Blindness

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Implosion : This is the situation When duplicate messages are

send to the same node. This occurs when a node receives copies

of the same messages from many of its neighbors

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Overlap : Overlap is another problem which occurs when using

flooding. If two nodes share the same observation region both nodes

will witness an event at the same time and transmit details of this

event.

Resource blindness : the flooding protocol does not consider the

available energy at the nodes and results in many redundant

transmissions. Hence, it reduces the network lifetime.

1.2 Gossiping

Modified version of flooding

The nodes do not broadcast a packet, but

send it to a randomly selected neighbor.

Avoid the problem of implosion by making

one copy of each message at any node

It takes a long time for message to propagate

throughout the network.

The hop count can become quite large due to

the protocols random nature9

1.3 Sensor Protocols for Information via

Negotiation

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SPIN use negotiation and resource adaptation to address the

disadvantage of flooding and Use meta-data instead of raw data.

Reduce overlap and implosion, and prolong network lifetime.

SPIN-1 has three types of messages: ADV, REQ, and DATA.

SPIN-2 using an energy threshold to reduce participation. A node

may join in the ADV-REQ-DATA handshake only if it has

sufficient resource above a threshold.

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2. Data Gathering

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The objective of the data gathering problem is to transmit the

sensed data from each sensor node to a BS.

The goal of algorithm which implement data gathering is

maximize the lifetime of network

Minimum energy should be consumed

The transmission occur with minimum delay

Difference between Data Dissemination

and Gathering

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Data Dissemination Data Gathering

1 Any node can request the

data along with base station.

All data is transmitted to the

base station

2 Data is always transmitted

on demand

Data can be transmitted

periodically

Data Gathering Approaches

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Direct Transmission

Power-Efficient Gathering for Sensor Information Systems

Binary Scheme

2.1 Direct Transmission

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All sensor nodes transmit their data directly to the BS.

It cost expensive when the sensor nodes are very far from the BS.

Nodes must take turns while transmitting to the BS to avoid

collision, so the media access delay is also large. Hence, this

scheme performs poorly with respect to the energy x delay metric.

2.2 Power-Efficient Gathering for Sensor

Information Systems

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PEGASIS based on the assumption that all sensor nodes know the

location of every other node.

Any node has the required transmission range to reach the BS in

one hop, when it is selected as a leader.

The goal of PEGASIS are as following

Minimize the distance over which each node transmit

Minimize the broadcasting overhead

Minimize the number of messages that need to besent to the BS

Distribute the energy consumption equally across all nodes

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To construct a chain of sensor nodes, starting from the node

farthest from the BS. At each step, the nearest neighbor which has

not been visited is added to the chain.

This algorithm uses greedy algorithm for chain construction.

Before first round of communication chain formation is done

During formation of chain care must be taken so that nodes

already in chain should not revisited

It is reconstructed when nodes die out.

At every node, data fusion or aggregation is carried out.

A node which is designated as the leader finally transmits one

message to the BS.

Leadership is transferred in sequential order.

The delay involved in messages reaching the BS is O(N)

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Figure 5 : Data gathering with PEGASIS

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2.3 Binary Scheme

This is a chain-based scheme like PEGASIS, which classifies

nodes into different levels.

This scheme is possible when nodes communicate using CDMA,

so that transmissions of each level can take place simultaneously.

The delay is O(log2N)

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Advantages

Low delay of only O(log2N), where the N is the amount of

nodes.

Disadvantages

Non equal distribution of energy consumption, nodes that are

active on several levels consume more energy than nodes that

are only active at the first level. This might lead to the

situation where some of sensor nodes die earlier than others.

Transmission distances may become long in high levels,

which leads to a high power consumption

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Routing Challenges and Design

Issues in WSN

The design of routing protocols in WSNs is influenced by

many challenging factors. These factors must be overcome

before efficient communication can be achieved in WSNs.

– Node deployment

– Energy considerations

– Data delivery model

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– Node/link heterogeneity

– Fault tolerance

– Scalability

– Network dynamics

– Transmission media

– Connectivity

– Coverage

– Data aggregation/converge cast

– Quality of service

Node Deployment

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Node deployment in WSNs is application dependent and affects

the performance of the routing protocol.

The deployment can be either deterministic or randomized.

In deterministic deployment, the sensors are manually placed and

data is routed through pre-determined paths.

In random node deployment, the sensor nodes are scattered

randomly creating an infrastructure in an ad hoc manner.

Energy Considerations

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Sensor nodes can use up their limited supply of energy performing

computations and transmitting information in a wireless

environment. Energy conserving forms of communication and

computation are essential.

In a multi-hop WSN, each node plays a dual role as data sender

and data router. The malfunctioning of some sensor nodes due to

power failure can cause significant topological changes and might

require rerouting of packets and reorganization of the network.

Data Delivery Model

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Time-driven (continuous)

Suitable for applications that require periodic data monitoring

Event-driven

React immediately to sudden and drastic changes

Query-driven

Respond to a query generated by the BS or another node in the

network

Hybrid

The routing protocol is highly influenced by the data reporting method

Node/Link Heterogeneity

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Depending on the application, a sensor node can have a

different role or capability.

The existence of a heterogeneous set of sensors raises many

technical issues related to data routing.

Even data reading and reporting can be generated from these

sensors at different rates, subject to diverse QoS constraints,

and can follow multiple data reporting models.

Fault Tolerance

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Some sensor nodes may fail or be blocked due to lack of power,

physical damage, or environmental interferences

It may require actively adjusting transmission powers and

signaling rates on the existing links to reduce energy

consumption, or rerouting packets through regions of the

network where more energy is available

Scalability

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The number of sensor nodes deployed in the sensing area may

be on the order of hundreds or thousands, or more.

Any routing scheme must be able to work with this huge

number of sensor nodes.

In addition, sensor network routing protocols should be

scalable enough to respond to events in the environment.

Network Dynamics

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Routing messages from or to moving nodes is more

challenging since route and topology stability become

important issues

Moreover, the phenomenon can be mobile (e.g., a

target detection/ tracking application).

Transmission Media

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In general, the required bandwidth of sensor data will be low,

on the order of 1-100 kb/s. Related to the transmission media is

the design of MAC.

TDMA (time-division multiple access)

CSMA (carrier sense multiple access)

Connectivity

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High node density in sensor networks precludes them from

being completely isolated from each other.

However, may not prevent the network topology from being

variable and the network size from shrinking due to sensor

node failures.

In addition, connectivity depends on the possibly random

distribution of nodes.

Coverage

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In WSNs, each sensor node obtains a certain view of the

environment.

A given sensor’s view of the environment is limited in both

range and accuracy.

It can only cover a limited physical area of the environment.

Data Aggregation/Convergecast

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Since sensor nodes may generate significant redundant data,

similar packets from multiple nodes can be aggregated to

reduce the number of transmissions.

Data aggregation is the combination of data from different

sources according to a certain aggregation function.

Converge casting is collecting information “upwards” from the

spanning tree after a broadcast.

Quality of Service

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In many applications, conservation of energy, which is directly

related to network lifetime.

As energy is depleted, the network may be required to reduce

the quality of results in order to reduce energy dissipation in

the nodes and hence lengthen the total network lifetime.

Routing Protocols in WSNs: A taxonomy

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Network Structure Protocol Operation

Flat routing• SPIN

• Directed Diffusion (DD)

Hierarchical routing• LEACH

• PEGASIS

• TTDD

Location based routing• GEAR

• GPSR

Negotiation based routing• SPIN

Multi-path network routing• DD

Query based routing• DD, Data centric routing

QoS based routing• TBP, SPEED

Coherent based routing• DD

Aggregation• Data Mules, CTCCAP

Routing protocols in WSNs

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Routing Strategies in WSN

Routing Strategies

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Aim to make communication more efficient

Trade-off between routing overhead and data transmission cost

Strategies incur differing levels of communication and storage overhead

Hybrid approaches are possible

Proactive and Reactive Routing

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Proactive routing

Routes created and maintained in advance

E.g : LEACH protocol

Does not scale to large networks

Reactive routing

Routes created and cached as required

E.g : TEEN protocol

Dynamic delays

Geographic and Energy Aware Routing

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Motivation: Reduce overhead of interest and low rate data flooding in directed

diffusion

Basic ideas: Leverage geographical information to restrict flooding, and

recursively disseminate data inside the target region.

Extend overall network lifetime using local techniques to balance energy usage

Reuse routing information across multiple user queries.

Geographic and Energy Aware Routing

Forward the packets towards the target region: Greedy mode: minimizing cost

function (f=mix function of distance and energy)

Route around “communication holes” with energy aware neighbor estimation

Disseminate the packet within the target region: Geographic Recursive Forwarding

recursively re-send packets to sub-regions of the original geographic region

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Geographic and Energy Aware Routing

Each node has a learned cost(historical cost) and an estimated cost (present state cost) to decide the next forwarding node

Learned cost

Estimated cost

min min( , ) ( , ) ( , )h N R h N R C N N

( , ) ( , ) (1 ) ( )i i ic N R d N R e N

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G P S R : G R E E D Y P E R I M E T E R S T A T E L E S S R O U T I N G F O R W I R E L E S S N E T W O R K S

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Geographic Routing

Motivation

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A sensor net consists of hundreds or thousands of nodes

Scalability is the issue

Existing ad hoc net protocols, e.g., DSR, AODV, ZRP, require nodes to cache e2e route information

Dynamic topology changes

Mobility

Reduce caching overhead

Hierarchical routing is usually based on well defined, rarely changing administrative boundaries

Geographic routing

Use location for routing

Scalability metrics

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Routing protocol msg cost

How many control packets sent?

Per node state

How much storage per node is required?

E2E packet delivery success rate

Assumptions

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Every node knows its location

Positioning devices like GPS

Localization

A source can get the location of the destination

802.11 MAC

Link bidirectionality

Geographic Routing: Greedy Routing

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S D

Closest to D

A

- Find neighbors who are the closer to the destination- Forward the packet to the neighbor closest to the destination

Benefits of GF

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A node only needs to remember the location info of one-hop neighbors

Routing decisions can be dynamically made

Greedy Forwarding does NOT always work

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If the network is dense enough that each interior node has a neighbor in every 2/3 angular sector, GF will always succeed

GF fails

Energy-Aware Routing

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• Maximise network lifetime (no accepted definition)• Communication is the most expensive activity• Possible goals include:

– Shortest-hop (fewest nodes involved)– Lowest energy route– Route via highest available energy– Distribute energy burden evenly– Lowest routing overhead

• Distributed algorithms cost energy• Changing component state costs energy

NOTE: Read Routing Strategies PPT’s after this

Energy-Aware Routing

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A destination-initiated reactive protocol

It maintains a set of paths

Choosing paths by means of certain probabilitydepending on how low the energy consumption is

Energy-Aware Routing

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Setup Phase

Controller

Sensor

Directional flooding

10 nJ

30 nJ

p1 = 0.75

p2 = 0.25

Local Rule

Energy-Aware Routing

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Data Communication Phase

1.01.0

0.6

0.4

Controller

Sensor0.3

0.7

Each node makes

a local decision

Attribute-based routing

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Data-centric approach: Not interested in routing to a particular node or a particular location

Nodes desiring some information need to find nodes that have that information

Attribute-value event record, and associated query

type animal

instance horse

location 35,57

time 1:07:13

type animal

instance horse

location 0,100,100,200

Directed diffusion

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Sinks: nodes requesting information

Sources: nodes generating information

Interests: records indicating A desire for certain types of information

Frequency with which information desired

Key assumption: Persistence of interests

Approach:

Learn good paths between sources and sinks

Amortize the cost of finding the paths over period of use

[IGE00]

Diffusion of interests and gradients

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Interests diffuse from the sinks through the sensor network

Nodes track unexpired interests

Each node maintains an interest cache

Each cache entry has a gradient

Derived from the frequency with which a sink requests repeated data about an interest

Sink can modify gradients (increase or decrease) depending on response from neighbors

Attribute based Routing

Directed Diffusion

Rumor Routing

Geographic hash table

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