Goutham Kamath

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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(More)
Many real-world wireless sensor network applications such as environmental monitoring, structural health monitoring, and smart grid can be formulated as a least-squares problem. In distributed Cyber-Physical System (CPS), each sensor node observes partial phenomena due to spatial and temporal restriction and is able to form only partial rows of(More)
Current geophysical techniques for visualizing seismic activity employ image reconstruction methods that rely on a centralized approach for processing the raw data captured by seismic sensors. The data is either gathered manually, or relayed by expensive broadband stations, and then processed at a base station. This approach is time-consuming (weeks to(More)
Seismic tomographic imaging is a complex process for imaging the subsurface geological structures. It involves massive data acquisition, signal processing and computing. Traditionally, the voluminous data is logged in each station then manually gathered to a centralized location for post processing. It may take months to see the subsurface image. To see(More)
Abstract—Edge or Fog computing is emerging as a new computing paradigm where the data processing, networking, storage and analytics are performed closer to the devices (IoT) and applications. The edge of a network plays an important role in the IoT system. It is an optimal site for off-loading bandwidth hungry IoT data. In order to generate business value(More)
Existing seismic instrumentation systems do not yet have the capability to recover the physical dynamics with sufficient resolution in real time. Currently, seismologists use centralized tomography inversion algorithm for which the data is gathered either manually from each station or by using limited number of expensive broadband stations. This scheme can(More)
Network diagnosis is a vital aspect in ensuring an efficient and robust functioning of any kind of mesh network. In this paper we present a network diagnosis method which determines the delay map of a mesh network using only end-to-end delay measurements without having the knowledge of the path taken. We model the problem of network diagnosis as an inverse(More)
Many science and engineering applications involve solving a linear least-squares system formed from some field measurements. In the distributed cyber-physical systems (CPS), often each sensor node used for measurement only knows partial independent rows of the least-squares system. To compute the least-squares solution they need to gather all these(More)
In both industry and academia, the seismic exploration does not yet have the capability of illuminating the physical dynamics with high resolution and in real-time. The major bottleneck in real-time monitoring today is to transfer large volume of raw data for post processing. Although computation capacity and sampling rate of sensors have increased(More)
Many real-world applications arising in domains such as large-scale machine learning, wired and wireless networks can be formulated as distributed linear least-squares over a large network. These problems often have their data naturally distributed. For instance applications such as seismic imaging, smart grid have the sensors geographically distributed and(More)