ROUTING PROTOCOLS FOR WSN · Network Structure Protocol Operation Flat routing • SPIN • Directed Diffusion (DD) Hierarchical routing • LEACH • PEGASIS • TTDD Location based
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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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