Macro Programming a Spatial Computer with Bayesian Networks
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Core operational semantics of Proto
Proceedings of the 2011 ACM Symposium on Applied Computing
Automatic discovery of algorithms for multi-agent systems
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Linda in space-time: an adaptive coordination model for mobile ad-hoc environments
COORDINATION'12 Proceedings of the 14th international conference on Coordination Models and Languages
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A spatial computer is a collection of devices filling space whose ability to interact is strongly dependent on their proximity. Previously, we have showed that programming such a computer as a continuous space can allow selfscaling across computers with different device distributions and can increase robustness against device failure. We have extended these ideas to time, allowing self-scaling across computers with different communication and execution rates. We have used a network of 24 Mica2 Motes to demonstrate that a program exploiting these ideas shows minimal difference in behavior as the time between program steps ranges from 100 ms to 300 ms and on a configuration with mixed rates.