Component-Average Based Distributed Seismic Tomography in Sensor Networks

Existing volcano instrumentation and monitoring system use centralized approach for data collection and image reconstruction and they lack the capability of obtaining real time information. A new distributed method is required which can obtain a high resolution seismic tomography in real time. In this paper, we present a component-average distributed multiresolution evolving tomography algorithm for processing data and inverting volcano tomography in the network, while avoiding centralized computation and costly data collection. The new algorithm distributes the computational burden to sensor nodes and performs real time tomographic inversion under constraints of network resources. We implemented and evaluated the algorithm in a customized simulator using synthetic data. The experiment results validate that our proposed algorithm not only balances the computation load but also achieves high data loss tolerance.