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Promises of ubiquitous control of the physical environment by sensor networks open avenues that will redefine the way we live and work. Due to the small size and low cost of sensors, visionaries promise smart systems enabled by deployment of huge numbers of sensors working in concert. At the moment, sensor network research is concentrating on developing techniques for performing simple tasks with minimal energy expense, assuming some form of centralized control. Centralized control does not scale to large networks and simple tasks in small-scale networks will not lead to the sophisticated applications predicted. Recently, the authors have proposed a new way of looking at sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Here we demonstrate that in such a model, fully distributed data aggregation can be performed efficiently, without synchronization, in a scalable fashion, where individual motes operate autonomously based on local information, cooperating with neighbors to make local decisions that are aggregated across the network achieving globally-meaningful effects. [ABSTRACT FROM AUTHOR]

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. [ABSTRACT FROM AUTHOR]