1. MCEEC: MULTI-HOP CENTRALIZED ENERGY EFFICIENT CLUSTERING ROUTING PROTOCOL FOR WSNS N. Javaid, M. Aslam, K. Djouani, Z. A. Khan, T. A. Alghamdi

2. Outline  Abstract  Introduction  Related Work  Problem Statement  Proposed Network Model  Proposed Model  Results  Conclusion

3. Abstract  Proposed a Multi-hop Centralized Energy Efficient Clustering (MCEEC)  Execution of MCEEC clustering is performed by advanced central control algorithm  Each node is capable of sensing two types of environmental dynamics  Temperature  Humidity

4. Continue…  CH selection criteria  Multi-hop inter-cluster communication for MCEEC.  Network deployment for MCEEC operation  MCEEC provides  Long network lifetime  Long stability period

5. Introduction (1/2)  Modern progression in Micro Electro Mechanical System (MEMS)  Individual Sensor Capability  WSN Architecture  Applications  Energy constrain  Energy efficient routing techniques

6. Introduction (2/2)  Types of WSNs  Types of Energy efficient routing protocols  Main objective of routing protocols  Intra cluster communication and Inter cluster communication  Multi-hoping advantages  We proposed MCEEC

7. Related Work  Types of clustering routing protocols  Homogeneous and Heterogeneous Networks  Single-hop inter-cluster communication and multi-hop inter- cluster communication.  LEACH  MLEACH  SEP  DEEC  LEACH-C

8. Problem Statement  Low network lifetime and stability of WSNs  Limited battery capacity  Un guaranteed CHs selection of distributed algorithms  Lack of network deployment planning  Large network area  High network density  Single-hop intra and inter-cluster communication

9. Proposed Network Model

10. Proposed Network Model Clustering Mechanism

11. Proposed Model of MCEEC  MCEEC’s advanced centrally controlled algorithm  Parameters for the selection of CHs  Heterogeneity awareness of MCEEC  Multi-hoping Inter-cluster Communications  Clustering and Multi-hoping restrictions for MCEEC  Network Settling Phase (NSP) and Network Transmission Phase (NTP)

12. Network Settling Phase (NSP) of MCEEC (1/2)  CHs selection  Types of nodes and regions of networks  Total Energy network  CHs selection restrictions  Average energy of each type node

13. Network Settling Phase (NSP) of MCEEC (2/2)  For normal nodes  For Advance nodes  For Super nodes   Required number of CHs  Distance to BS  Comparison and CHs selection  Association Phase.

14. Network Transmission Phase (NTP)  Transmission of sensed data  CHs aggregate received data  CHs compress aggregated data  Only transmit Meaning full information  Single-hop intra cluster-communication  Multi-hop inter cluster-communication

15. Radio Model Used in MCEEC  Radio Model  Energy consumption

16. Results  Simulation Parameters

17. Alive Nodes for first scenario  Stability period increased  Due to the uniform random deployment of nodes  Centralized cluster formation  Multihoping in inter-cluster

18. Dead Nodes for first scenario  Late start of instability period as compared to the other routing protocols  Transmission responsibilities of nodes according to their remaining energies

19. Cluster-Heads Generation for first scenario  Guaranteed number of CHs per round  Centralized controlled selection of CHs  LEACH, SEP, E-SEP and DEEC do not provide guaranteed number of CHs

20. Alive Nodes for second scenario  Guaranteed number of CHs provide high throughput  Throughput enhancement is due to multi-hop communication approach  CHs transmit data in short range

21. Dead Nodes for second scenario  Number of dead node slowly increase as compared to LEACH, DEEC, SEP and ESEP

22. Cluster-Heads Generation for second scenario  Fluctuations in CHs selection per round increased

23. Packets send to BS for second scenario  Better throughput of MCEEC as compared to selected routing protocols

24. Conclusion  We propose MCEEC routing protocol for three level heterogeneous WSNs  MCEEC bases on the concept of heterogeneous-aware clustering like SEP, E-SEP and DEEC.  Major improvement is centralized clustering algorithm  MCEEC provides scalability  MCEEC outperform  LEACH  SEP  E-SEP  DEEC