关键词：光机电；传感器；生物激励；自我属性
摘 要：Wireless sensor networks (WSNs) possess inherent tradeoffs among conflicting performance objectives such as data yield, data fidelity and power consumption. In order to address this challenge, this paper proposes a biologically-inspired application framework for WSNs. The proposed framework, called El Nifio, models an application as a decentralized group of software agents. This is analogous to a bee colony (application) consisting of bees (agents). Agents collect sensor data on individual nodes and carry the data to base stations. They perform this data collection functionality by autonomously sensing their local network conditions and adaptively invoking biological behaviors such as pheromone emission, swarming, reproduction and migration. Each agent carries its own operational parameters, as genes, which govern its behavior invocation and configure its underlying sensor nodes. El Nino allows agents to evolve and adapt their operational parameters to network dynamics and disruptions by seeking the optimal tradeoffs among conflicting performance objectives. This evolution process is augmented by a notion of accelerated evolution. It allows agents to evolve their operational parameters by learning dynamic network conditions in the network and approximating their performance under the conditions. This is intended to expedite agent evolution to adapt to network dynamics and disruptions.