Cost-efficient parallel processing of irregularly structured problems in cloud computing environments

Haussmann, Jens; Blochinger, Wolfgang; Kuechlin, Wolfgang

doi:10.1007/s10586-018-2879-3

Cited by 9 publications

(2 citation statements)

References 38 publications

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“…When using satellite remote sensing data for earthquake prediction, it is of great significance to inversely perform the abrupt change of physical parameters such as temperature, so as to identify the abrupt change of bright temperature value during earthquake and then extract the infrared heating anomalies practice, Lipschitz index [32] often used to express the local singularity of the signal.…”

Section: Seismic Satellite Remote Sensing Data Analysis Based On Wmentioning

confidence: 99%

Analysis of Earthquake Emergency Command System According to Cloud Computing Methods

Chen¹,

Chen²,

Li³

et al. 2021

IEEE Access

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To solve the problems of slow information acquisition, low processing efficiency, weak information storage and communication ability in earthquake rescue, an earthquake emergency command system on the basis of cloud computing and Internet of Things (IoT) is designed. First, the cloud computing technology is introduced, and the traditional earthquake emergency command system built by cloud computing and the Internet of things is analyzed. Then, based on the satellite remote sensing data, the characteristics of the middle-wave infrared remote sensing data before and after the recent earthquakes in China are explored. Subsequently, a new earthquake emergency command system is built based on cloud computing and Internet of things technology along with the data from the satellite middle-wave infrared remote sensing. Finally, the feasibility of the system is evaluated. The results show that the surface radiation changes significantly before the earthquake, the infrared brightness temperature difference value also fluctuates violently, and the abnormal area will gradually get closer to the epicenter as time goes by. The peak value of the relative power spectrum in the earthquake is more than 9 times of the average value in the normal time. In conclusion, the evaluation result of the emergency command system based on satellite remote sensing data, cloud computing, and Internet of things is good, suggesting satellite infrared remote sensing data can be applied to earthquake prediction, and the earthquake emergency command system constructed combining cloud computing and Internet of things technology has a good feasibility.

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Section: Seismic Satellite Remote Sensing Data Analysis Based On Wmentioning

confidence: 99%

Analysis of Earthquake Emergency Command System According to Cloud Computing Methods

Chen¹,

Chen²,

Li³

et al. 2021

IEEE Access

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“…The first approach to distributed workload management systems is structural classification [21]. Its main concern is the architecture behind hardware implementation of the computing pool.…”

Section: Structural Classificationmentioning

confidence: 99%

Tree-Like Distributed Computation Environment with Shapp Library

Gałecki

Daszczuk

2020

Information

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Despite the rapidly growing computing power of computers, it is often insufficient to perform mass calculations in a short time, for example, simulation of systems for various sets of parameters, the searching of huge state spaces, optimization using ant or genetic algorithms, machine learning, etc. One can solve the problem of a lack of computing power through workload management systems used in local networks in order to use the free computing power of servers and workstations. This article proposes raising such a system to a higher level of abstraction: The use in the .NET environment of a new Shapp library that allows remote task execution using fork-like operations from Portable Operating System Interface for UNIX (POSIX) systems. The library distributes the task code, sending static data on which task force is working, and individualizing tasks. In addition, a convenient way of communicating distributed tasks running hierarchically in the Shapp library was proposed to better manage the execution of these tasks. Many different task group architectures are possible; we focus on tree-like calculations that are suitable for many problems where the range of possible parallelism increases as the calculations progress.

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