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The Quake-Catcher Network (QCN) represents a paradigm shift in seismic networks by involving the general public in the collection, detection, and recognition of seismic events. The QCN uses low-cost sensors connected to volunteer computers across the world to monitor seismic events. The location and density of these sensors can impact the accuracy of event detection. Testing different arrangements of new sensors could disrupt the currently active project; thus such an experiment is best accomplished in a simulated environment.

This paper presents an accurate and efficient framework for simulating low-cost QCN sensors and identifying their most effective locations and densities. To build the framework, we extend EmBOINC, an emulator of Berkeley Open Infrastructure for Network Computing (BOINC) projects, to handle the trickle messages generated by sensors connected to volunteer hosts and sent to the …