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POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS

POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS. Presented by - S.ATCHUTHAN. Supervised by – Prof Klaus Moissner. Major Achievements. Investigated energy conservation algorithms for WSN and identify clustering is promising technique for energy saving

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POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS

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  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 ? How to prolong the network lifetime ?

  8. ENERGY EFFICIENCY........ How energy is consumed in a sensor node ? 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) = 0 Otherwise

  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 ) = 0 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

  17. DEEC....... Residual Energy Calculation ETx (l, d) = l*Eelec +l*єfs *d^2 if d < d0 ETx (l, d) = l*Eelec +l*єmp*d^4 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 End K = rand (); If (DEEC clustering threshold probability < k) S ( i ). Cluster = TRUE; End End

  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

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