Multi-objective optimization for security and QoS adaptation in Wireless Sensor Networks

In this paper we address the impact of the security cost in terms of energy consumption, processing time, and traffic load on quality of services (QoS) in Wireless Sensor Networks (WSNs). Offering security services (authentication, confidentiality, and integrity) and QoS (throughput, delay, and reliability) guarantee in WSNs is still challenging issue. The security and QoS are opposite parameters, and then security services must be dynamically and optimally adapted to QoS and network constraints (e.g. energy efficiency). Therefore, designing such solution that optimizes multiple conflicting objectives is computationally intractable. We propose a new solution based on multi-objective optimization using genetic algorithm (NSGA-II) for security, QoS, and energy efficiency in WSNs. Resource constraints as well as QoS requirements are respected through use of optimal security level based on evolutionary strategy. The obtained simulation results illustrate that the energy efficiency and the security level optimization is reached with different set of optimal security settings adapted to the QoS and the energy requirements.

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