Energy Efcient Clustering Algorithm for MultiHop Wireless Sensor

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Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic 2017

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

Outline • Introduction • Related Work • System Model • Simulation & Result •

Outline • Introduction • Related Work • System Model • Simulation & Result • Conclusions

Introduction • An important design issue in WSNs is to reduce the energy consumption

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.

Introduction • To design a suitable protocol, few of parameters • • discussed here.

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

Introduction • LEACH & LEACH-C (centralized LEACH) • • Randomized probabilistic model Local information

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

• Fuzzy Logic is considered • Simple and flexible to take real time

• Fuzzy Logic is considered • Simple and flexible to take real time decisions • under uncertain environment. • T 2 FL is more accurately.

Related Work • Hierarchical Routing Protocols Based on Clustering • FL Based Clustering Protocol

Related Work • Hierarchical Routing Protocols Based on Clustering • FL Based Clustering Protocol

• Hierarchical Routing Protocols Based on Clustering • LEACH • • Random number

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

• FL Based Clustering Protocol • CHEF • proximity distance • energy •

• FL Based Clustering Protocol • CHEF • proximity distance • energy • Better than LEACH 22. 7% • Another method • concentration • centrality

• Fuzzy Logic

• Fuzzy Logic

System Model • System Assumption • • • All the sensor nodes are static

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)

System Model • Algorithm

System Model • Algorithm

System Model • Fuzzy Logic Model • • 3 parameters Remaining Battery Power Distance

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-1 fuzzy set membership function

System Model

System Model

System Model • FOU : footprint of uncertainty • Type 2 FL = Type

System Model • FOU : footprint of uncertainty • Type 2 FL = Type 1 FL + FOU -> 0, T 1 FL FOU -> 0~1, T 2 FL

Simulation and Result

Simulation and Result

Simulation and Result

Simulation and Result

T 1 FL

T 1 FL

Conclusions • LEACH provides an opportunity to improve in various parts of the protocol.

Conclusions • LEACH provides an opportunity to improve in various parts of the protocol. • T 2 FL Model handles the uncertainties more accurately than T 1 FL model. • T 2 FL model provides better scalability, better lifetime compared to T 1 FL, LEACH single and LEACH multi-hop protocol.

REFERENCES • Padmalaya Nayak, Bhavani Vathasavai , ” Energy Efficient Clustering Algorithm for Multi-Hop

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

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