1. Padmalaya Nayak, and Bhavani Vathasava
Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic
2017 IEEE Sensors Journal
Padmalaya Nayak, and Bhavani Vathasava
ADVISOR: DR. HO-TING WU
Speaker: Jin-wei Lin

2. Outline Introduction Related Work System Model Simulation & Result
Conclusions

3. Introduction
An important design issue in WSNs is to reduce the energy consumption by the use of energy conserving hardware, operating system and communication protocols.
Transmission energy that dominates overall energy consumption.

4. Introduction To design a suitable protocol, few of parameters
discussed here.
Self-Organizing Capability
Network Lifetime
Load balancing
Scalability
Latency
Clustering

5. Introduction LEACH & LEACH-C (centralized LEACH)
Randomized probabilistic model
Local information for data transfer
Low energy media access control
Application specific data processing

6. Fuzzy Logic is considered
Simple and flexible to take real time decisions
under uncertain environment.
T2FL is more accurately.

7. Related Work Hierarchical Routing Protocols Based on Clustering
FL Based Clustering Protocol

8. Hierarchical Routing Protocols Based on Clustering
LEACH
Random number of CHs
CHs are too closed
CPU cycles are consumed
CH is located near to boundary
LEACH-C
Better clusters are formed by base station(BS)

9. FL Based Clustering Protocol
CHEF
proximity distance
energy
Better than LEACH 22.7%
Another method
concentration
centrality

10. Fuzzy Logic

11. System Model System Assumption All the sensor nodes are static
All the sensor nodes have initial equal energy
Distance between the BS and the sensor node is computed based on RSSI
A stand by CH (SB-CH) is elected in the last level of
the chain (nearer to the BS)

12. System Model
Algorithm

13. System Model Fuzzy Logic Model 3 parameters Remaining Battery Power
Distance to BS
Concentration
These two functions can be represented (each one) by a Type-1fuzzy set membership function

14. System Model

15. System Model FOU : footprint of uncertainty FOU -> 0, T1FL
Type2FL = Type1FL + FOU FOU -> 0~1, T2FL

16. Simulation and Result

17. Simulation and Result

19. T1FL

20. Conclusions
LEACH provides an opportunity to improve in various parts of the protocol.
T2FL Model handles the uncertainties more accurately than T1FL model.
T2FL model provides better scalability, better lifetime compared to T1FL, LEACH single and LEACH multi-hop protocol.

21. REFERENCES
Padmalaya Nayak, Bhavani Vathasavai ,” Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic” , IEEE SENSORS JOURNAL, VOL. 17, NO. 14, JULY 15, 2017
Padmalaya Nayak, Anurag Devulapalli ,” A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime” , IEEE SENSORS JOURNAL, VOL. 16, NO. 1, JANUARY 1, 2016