Networked and Embedded Systems Laboratory

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Large-scale coordination and control problems in sensor/actuator networks are often expressed within the networked optimization model. While significant advances have taken place in both first- and higher-order optimization techniques, their widespread adoption in practical implementations has been hindered by a lack of adequate programming and evaluation support. This motivates the two major contributions of this paper. First, we outline the design of an Application Programming Framework, implement different versions of the subgradient technique and perform extensive evaluation with varying deployment and algorithmic parameters. Second, the insights obtained by observing the variability in practical metrics such as response time and incurred message cost, lead us to exploit the spatial locality inherent in these large-scale actuator control applications, and propose a novel consensus algorithm applied to the subgradient method. We show using simulations that there is at least 99% improvement in response time and the message cost is reduced by more than 90% over prior consensus based algorithms.

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