Decentralized Multigrid for In-situ Big Data Computing

作     者：Goutham Kamath Lei Shi Edmond Chow Wenzhan Song Junjie Yang 

作者机构：Department of Computer ScienceGeorgia State University College of ComputingGeorgia Institute of Technology School of Electric and Information EngineeringShanghai University of Electric Power 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2015年第20卷第6期

页      面：545-559页

核心收录：

学科分类：070801[理学-固体地球物理学] 07[理学] 0708[理学-地球物理学] 

主　　题：distributed multigrid cyber physical system big da 

摘      要：Modern seismic sensors are capable of recording high precision vibration data continuously for several months. Seismic raw data consists of information regarding earthquake’s origin time, location, wave velocity, ***, these high volume data are gathered manually from each station for analysis. This process restricts us from obtaining high-resolution images in real-time. A new in-network distributed method is required that can obtain a high-resolution seismic tomography in real time. In this paper, we present a distributed multigrid solution to reconstruct seismic image over large dense networks. The algorithm performs in-network computation on large seismic samples and avoids expensive data collection and centralized computation. Our evaluation using synthetic data shows that the proposed method accelerates the convergence and reduces the number of messages exchanged. The distributed scheme balances the computation load and is also tolerant to severe packet loss.