Sensor networks for situation management: a biomimetic model

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications in support of situation management. Recent sensor network research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to situation management as it allows single points of failure and does not scale to massive size networks. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in our model fully distributed data aggregation and integration can be performed in a scalable fashion where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. This exemplifies the robust, fault-tolerant infrastructure required for successful situation management systems

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