This seminar presentation summarizes the Stable Election Protocol (SEP) for wireless sensor networks. SEP aims to increase network stability and reduce energy consumption through clustering. It uses a genetic algorithm to dynamically select cluster members, heads, and the next cluster. The genetic algorithm evaluates chromosomes based on their ability to minimize energy use and maximize network lifetime. It selects high-fitness chromosomes to mate and produce new chromosomes, applying crossover and mutation. The goal of SEP is to yield longer stability periods for networks with heterogeneous nodes having different energy levels.

1. Seminar presentation
on
SEP: Stable Election Protocol
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Submitted To:
Deepak Agarwal
Abhishek Jain
Guided By:
Nidhi Gupta(Asst. Prof)
CSE
Presented By:
Apurva Pareek

2. Content
 Overview: Wireless Sensor Network
 Application
 Need of SEP
 SEP Method
 Algorithm
 References
 Conclusion
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3. Sensor
 Sensor are used to sense the information from
the environment and compute, store and
transmit ,interested data from the
environment in which they deployed.
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4. Wireless Sensor Network
 A Wireless Sensor Network (WSN) consists
of base stations and a number of wireless
sensors (nodes).
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5. Application
 Military and national security application
 Environment monitoring
 Medical application
 Nearly anything you can imagine
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6. Problem
 Due to small size a big size battery source can
not be embedded into them therefore sensor
need an effective mechanism for maximum
energy utilization. some amount of energy is
consumed during sensing as well as
transmission of data. practically this is not
possible to replace or recharge batteries of
nodes once node are deployed in a field or
zone.
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7. Application…
Great Duck Island
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8. Method
DTE: Direct Transfer Energy
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5
4
2
1
sink
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9. MTE: Minimal Transfer Energy
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sink

10. 10
Clustering Hierarchy
In wsn nodes are not always homogeneous they might be
heterogeneous which increase network complexity. To
increase stability and reduce the energy consumption
clustering is key technique in WSN.

11. Genetic Algorithm
Genetic Algorithm is used to create cluster
member, cluster head and next cluster
dynamically, which is used to calculate
average fitness and increase life time of the
network
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12. Process….
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13. Population
A population is collection of several
chromosomes and the best chromosome is
used to generate the next population. Initially
the GA starts with a population of predefined
number of chromosomes and randomly
selected cluster heads. each chromosome
is evaluated by GA by calculating its
fitness. After evaluating the fitness GA
selects best suitable chromosome and then
applies crossover and mutation.
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14. Fitness
 The fitness of a chromosome is its ability
to pass on its genetic material & also its
quality to survive. The fitness of the
chromosome is designed to minimize the
energy consumption and to increase the network
lifetime.
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15. Selection
 Selection is the process of determining
which two chromosomes will mate to
form a new chromosome.
 The chromosomes with higher fitness values
have more chances to of matting.
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16. Crossover
 Crossover is a binary genetic operation
applied on two chromosomes. Crossover
recombines the genetic materials of two parent
chromosomes to produce a child chromosome. The
results of the crossover depend on the selection
procedure.
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17. Mutation
 In mutation the genetic material of
individual changes of its own. The mutation
adds variations in the next generation.
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18. Conclusion
It conclude that SEP is most suitable when
deal with network lifetime and stability. It
found that SEP yields longer stability region
for higher values of extra energy brought by
more powerful nodes.
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19. References
 G. Smaragdakis and I. Matta, “SEP: A
Stable Election protocol for clustered
heterogeneous Wireless sensor Networks”,
Boston University Computer Science Department,
2004.
 Akkaya, K., & Younis, M. (2005). "A survey on
routing protocol for wireless sensor networks". Ad
hoc Networks 3 , 325-349.
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20. 20
Thank you

21. Any Queries???
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