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This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential attribute of wireless sensor networks, heterogeneity and its impacts on random key predistribution protocols are first discussed. Using supernetworks theory, the optimal node deployment model is proposed and illustrated. In order to find the equilibrium performance of our model, all optimal performance functions are changed into variational inequalities so that this optimization problem can be solved. A small-scale example is presented to illustrate the applicability of our model.


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Optimization of Key Predistribution Protocol Based on Supernetworks Theory in Heterogeneous WSN

Show Author's information Qi YuanChunguang Ma( )Xiaorui ZhongGang DuJiansheng Yao
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China.
College of Communication and Electronic Engineering, Qiqihar University, Qiqihar 161006, China.
Key Lab of Network Security and Cryptography of Fujian Province.
China Academy of Electronics and Information Technology, Beijing 100041, China.

Abstract

This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential attribute of wireless sensor networks, heterogeneity and its impacts on random key predistribution protocols are first discussed. Using supernetworks theory, the optimal node deployment model is proposed and illustrated. In order to find the equilibrium performance of our model, all optimal performance functions are changed into variational inequalities so that this optimization problem can be solved. A small-scale example is presented to illustrate the applicability of our model.

Keywords: optimization, wireless sensor networks, key predistribution protocol, supernetworks, variational inequality

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Publication history

Received: 02 February 2016
Accepted: 10 March 2016
Published: 13 June 2016
Issue date: June 2016

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© The author(s) 2016

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Nos. 61170241 and 61472097), the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20132304110017), and the Open Fund of the Key Lab of Network Security and Cryptography of Fujian Province (No. 150003).

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