1. POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS
Presented by - S.ATCHUTHAN
Supervised by – Prof Klaus Moissner

2. Major Achievements
Investigated energy conservation algorithms for WSN and identify clustering is promising technique for energy saving
Selected typical clustering algorithms for detailed investigation and comparison based on simulation
Weaknesses of these algorithms were identified and a NEW algorithm was proposed, the improvement of which was proved through simulation and comparison to the selected algorithms

3. CONTENTS Introduction Energy efficiency Existing protocols Clustering
LEACH
DEEC
HEED
Proposed Algorithm
Improvement
Conclusion

4. INTRODUCTION What is a wireless sensor network ?
- Data Acquisition network
-Data Distribution network
Applications of wireless sensor network
- Environmental monitoring
- Battle field surveillance
- Transportation traffic monitoring

5. Architecture of a wireless sensor network

6. What happens in a monitoring sensor network

7. ENERGY EFFICIENCY
What are the common problems in a wireless networking ?
What is network lifetime ?
Common problems- medium access control, routing, bandwidth allocation, power efficiency, security, life time
network lifetime – Time taken until the first node or last node in the network dies
Prolong the network lifetime – Minimize the power consumption from nodes
How to prolong the network lifetime ?

8. ENERGY EFFICIENCY........ How energy is consumed in a sensor node ?
Energy consumption – Transmitting or receiving data, processing query requests, forwarding data or queries to neighbour nodes, idle listening to the media, retransmission when packet collision and generating control packets
Energy conservation – Major challenge
How to conserve energy in a wireless sensor network ?

9. EXISTING PROTOCOLS LEACH LEACH-E SEP PEGASIS DEEC HEED TEEN APTEEN EAD
GEAR
GAF
MECN

10. EXISTING PROTOCOLS......

11. CLUSTERING What is Clustering ?
Promising technique for lifetime extension

12. CLUSTERING...... Choosing LEACH, DEEC and HEED for investigation
LEACH – Basic clustering mechanism
DEEC - Energy consideration for threshold
HEED - Competitive method

13. LEACH Low Energy Adaptive Clustering Hierarchy
Can apply for Single hop networks.
Cluster head threshold
T(n) = p/(1-p*(r mod(1/p))) if n ε G
T(n) = Otherwise
G is the set consisting of nodes that have not been cluster heads during last (1/p) rounds
n takes a value between 0 and 1
If n is less than threshold T(n), then that particular node would get the chance to become a cluster head at that particular round
Node which becomes cluster head during round 0, would again get the chance to be a cluster head during next (1/p) rounds

14. LEACH......

15. LEACH...... Merits Global knowledge of the network is not necessary.
Only two hops are needed to reach sink.
Demerits
Failure of the cluster head is a problem.
Difficult to optimize the cluster head selection.

16. DEEC Distributed Energy – Efficient Clustering Algorithm
Can apply for Single hop networks
Cluster head threshold
T(Si) = Pi /(1-Pi (r mod (1/Pi))) if Si ε G
T( Si ) = Otherwise
Pi = Popt (1+a) Ei (r) / (1+a*m) Ē (r) if normal node
Pi = Popt Ei (r) / (1+a*m) Ē (r) if advanced node
Probability threshold based on the ration between residual energy of each node and the average energy of the network

17. DEEC....... Residual Energy Calculation
ETx (l, d) = l*Eelec +l*єfs *d^ if d < d ETx (l, d) = l*Eelec +l*єmp*d^ if d >= d0
Average Energy Calculation
Ē (r) = (1/N) * Etotal (1- r/R)

18. DEEC........ Merits Life time is prolonged than LEACH Demerits
Global knowledge of the network is necessary

19. HEED Hybrid Energy Efficient Distributed Algorithm
Multi hop routing protocol
Clustering – Competitive mechanism

20. HEED....... Clustering parameters - Node residual energy - Node degree
Probability to be a cluster head
CHprob = Cprob *(Eresidual /Emax )

21. HEED...... Status of nodes - Tentative cluster head
- Final cluster head
- Uncovered
Merits
Large scalability
Lifetime is prolonged than DEEC
Demerits
Clustering consumes much energy

22. PROPOSED ALGORITHM Clustering Energy: HEED >> DEEC
DEEC Clustering for multi hop networks

23. PROPOSED ALGORITHM
Pseudo code (DEEC Clustering for multi hop networks)
For i = 1:1: n
For j = 1:1: n
If ( d( i, j) =< Tr )
join ( node j joins with cluster head i );
End
K = rand ();
If (DEEC clustering threshold probability < k)
S ( i ). Cluster = TRUE;

24. PROPOSED ALGORITHM....... Long distance cause Energy loss
Shortest path routing
Obtaining maximum single hop distance (100 m)

25. PROPOSED ALGORITHM....... Pseudo code (Shortest path routing)
While ((i =< n) & ((d.sink – d.cluster (i, sink)) >= 100))
While (j =< n)
If (d.cluster (i, j) =< 100)
Cluster (i) = cluster (j);
Else If
hop = hop +1; End End
End

26. PROPOSED ALGORITHM
Output

27. IMPROVEMENT
Lifetime is prolonged

28. CONCLUSION Improvement - DEEC Clustering for multi hop networks
- Shortest path routing
(Based on Single hop maximum distance)
Better combined of DEEC Clustering and Multi hop
Twelve percent improvement of lifetime

29. THANK YOU