Titlebook: Design Frameworks for Wireless Networks; Santosh Kumar Das,Sourav Samanta,Rajesh Kumar Book 2020 Springer Nature Singapore Pte Ltd. 2020 A

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Nata?a Rogelja,Alenka Janko Spreizer for the pixel bits of the image. Every neuron of the neural network uses the equation of chaotic maps as its transfer function. The system performs comparatively better as the two hyperchaotic maps have been used in the process with their nonlinearity property. Security analyses prove the fact with more evidence.

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An Analysis and Comparison of Security Protocols on Wireless Sensor Networks (WSN)rotocols for secure transmission of data and comparing them on the basis of performance. This work has provided a detailed description of the WSN-related information to extremely understand the concept of the network.

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Study and Design of Route Repairing Mechanism in MANETtipath scenario. Based on the widespread simulation of the proposed mechanism, done by adopting NS2 and by relative study of the same with existing protocol AODV, it was found that the projected routing mechanism helps in enhancing the performance and brings about improvement in ratio of packet delivery, packet loss as well as end-to-end delay.

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Image Encryption in IoT Devices Using DNA and Hyperchaotic Neural Network for the pixel bits of the image. Every neuron of the neural network uses the equation of chaotic maps as its transfer function. The system performs comparatively better as the two hyperchaotic maps have been used in the process with their nonlinearity property. Security analyses prove the fact with more evidence.

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Book 2020lligence and soft computing techniques to provide design frameworks for wireless networks. These techniques play a vital role in developing a more robust algorithm suitable for the dynamic and heterogeneous environment, making the network self-managed, self-operational, and self-configurational, and

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Distributed Online Fault Diagnosis in Wireless Sensor Networksy sensor in WSNs is addressed in this chapter. Further, how the performance of the fault diagnosis algorithm has been improved by employing robust statistical methods presented. The issue of intermittent fault diagnosis in WSNs is discussed using statistical methods which is the main focus of this chapter.