Performance Modeling of Cognitive Wireless Sensor Networks Applied to Environmental Protection

This paper presents a methodology, a theoretical framework, and some novel ideas on performance modeling and evaluation of application-specific cognitive wireless sensor networks applied to environmental protection. Cross-layer optimizations integrating the use of adaptive sleep, adaptive modulation and energy-aware higher layer processing and protocols are assumed. Routing and application layer processing are assumed to be dependent on lower-layer protocols, requirements, and constraints. Applications relevant to this study are forest monitoring, where the probability of network failure is the main parameter to be minimized, and endangered-species monitoring, where the probability of node failure is reduced by increasing the expected node life. Results are shown comparing expected node life of a cross-layered design to that of a traditional adaptive modulation system.