**Acknowledgements**

We are grateful to INHA University Global Education Project Group, Incheon, South Korea for all the support and funding provided for the publication of this research work.

compared to SIBER-DELTA and SIBER-VLP. SIBER-VLP performs very poorly in

*(a) Effect of malicious nodes on PDR-50 nodes. (b) Effect of malicious nodes on TP-50 nodes. (c) Effect of*

In this chapter, swarm intelligence and social insects based approaches are presented to deal with bio-inspired networking framework. The proposed approaches are designed to tackle the challenges and issues in the WSN field such as large scale networking, dynamic nature, resource constraints and the need for infrastructureless and autonomous operation having the capabilities of self-organization and survivability. This research work presents the necessity to consider a combination of evaluation parameters for efficient routing of packets from source to destination with the development of SIBER-XLP with TECB, SIBER-DELTA and SIBER-DELTAKE models, each one emerging as an improved extension over the other. NS2 simulation environment was used to develop the entire work. The outcomes achieved in terms of results can serve as a contribution to the research community in the area of WSN with further levels of security to be integrated in future due to the voluminous data generation in modern world with the development of IOT applications. Also, in this work, a set of parameters like packet delivery ratio, latency, throughput, energy

the existence of larger malicious or faulty nodes in the network.

*malicious nodes on LT– 50 nodes. (d) Effect of malicious nodes on EC-50 nodes.*

*Wireless Sensor Networks - Design, Deployment and Applications*

**6. Conclusion and future work**

**Figure 9.**

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