scholarly journals Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1525
Author(s):  
Abdullah Ayub Khan ◽  
Zaffar Ahmed Shaikh ◽  
Asif Ali Laghari ◽  
Sami Bourouis ◽  
Asif Ali Wagan ◽  
...  
Keyword(s):  
Land Surface ◽  
P2p Network ◽  
Dynamic Monitoring ◽  
Distributed Data ◽  
Distributed Monitoring ◽  
Distributed Data Management ◽  
Smart Contract ◽  
Simulation Results ◽  
Stored Information ◽  
Surface Changes

In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based data are captured through drones and transmitted to the fog nodes. The main objective here is to enable process and schedule, to investigate individual captured entity (records) and to analyze changes in the blockchain storage with a secure hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. The proposed blockchain mechanism is also investigated for analyzing the fog-cloud-based stored information, which is referred to as smart contracts. These contracts are designed and deployed to automate the overall distributed monitoring system. They include the registration of UAVs (drones), the day-to-day dynamic captured drone-based images, and the update transactions in the immutable storage for future investigations. The simulation results show the merit of our framework. Indeed, through extensive experiments, the developed system provides good performances regarding monitoring and management tasks.

scholarly journals Function-Level Dynamic Monitoring and Analysis System for Smart Contract

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 229161-229172
Author(s):  
Yi Ding ◽  
Chenshuo Wang ◽  
Qionghui Zhong ◽  
Haisheng Li ◽  
Jinjing Tan ◽  
...  
Keyword(s):  
Dynamic Monitoring ◽  
Smart Contract ◽  
Analysis System

Role of Land-Surface Changes in Arctic Summer Warming

Science ◽  
2005 ◽  
Vol 310 (5748) ◽  
pp. 657-660 ◽  
Author(s):  
F. S. Chapin
Keyword(s):  
Land Surface ◽  
Summer Warming ◽  
Arctic Summer ◽  
Surface Changes

Two parameters are required for a Budyko function to describe the land-atmosphere interaction

2021 ◽  
Author(s):  
Daeha Kim ◽  
Jong Ahn Chun
Keyword(s):  
Land Surface ◽  
River Basins ◽  
Control Surface ◽  
Primary Control ◽  
Evaporative Demand ◽  
Atmosphere Interaction ◽  
The Mean ◽  
Two Parameters ◽  
Two Parameter ◽  
Surface Changes

<p>While the Budyko framework has been a simple and convenient tool to assess runoff (Q) responses to climatic and surface changes, it has been unclear how parameters of a Budyko function represent the vertical land-atmosphere interactions. Here, we explicitly derived a two-parameter equation by correcting a boundary condition of the Budyko hypothesis. The correction enabled for the Budyko function to reflect the evaporative demand (E<sub>p</sub>) that actively responds to soil moisture deficiency. The derived two-parameter function suggests that four physical variables control surface runoff; namely, precipitation (P), potential evaporation (E<sub>p</sub>), wet-environment evaporation (E<sub>w</sub>), and the catchment properties (n). We linked the derived Budyko function to a definitive complementary evaporation principle, and assessed the relative elasticities of Q to climatic and land surface changes. Results showed that P is the primary control of runoff changes in most of river basins across the world, but its importance declined with climatological aridity. In arid river basins, the catchment properties play a major role in changing runoff, while changes in E<sub>p</sub> and E<sub>w</sub> seem to exert minor influences on Q changes. It was also found that the two-parameter Budyko function can capture unusual negative correlation between the mean annual Q and E<sub>p</sub>. This work suggests that at least two parameters are required for a Budyko function to properly describe the vertical interactions between the land and the atmosphere.</p>

scholarly journals Experience of a low-maintenance distributed data management system

2014 ◽  
Vol 513 (3) ◽  
pp. 032095 ◽  
Author(s):  
Wataru Takase ◽  
Yoshimi Matsumoto ◽  
Adil Hasan ◽  
Francesca Di Lodovico ◽  
Yoshiyuki Watase ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Distributed Data ◽  
Distributed Data Management

scholarly journals Integration of Rucio in Belle II

2021 ◽  
Vol 251 ◽  
pp. 02057
Author(s):  
Cédric Serfon ◽  
Ruslan Mashinistov ◽  
John Steven De Stefano ◽  
Michel Hernández Villanueva ◽  
Hironori Ito ◽  
...  
Keyword(s):  
Data Management ◽  
Smooth Transition ◽  
Distributed Data ◽  
Simulation Data ◽  
Migration Strategy ◽  
Distributed Data Management ◽  
Order Of Magnitude ◽  
Belle Ii ◽  
Work Done ◽  
Data Management Software

The Belle II experiment, which started taking physics data in April 2019, will multiply the volume of data currently stored on its nearly 30 storage elements worldwide by one order of magnitude to reach about 340 PB of data (raw and Monte Carlo simulation data) by the end of operations. To tackle this massive increase and to manage the data even after the end of the data taking, it was decided to move the Distributed Data Management software from a homegrown piece of software to a widely used Data Management solution in HEP and beyond : Rucio. This contribution describes the work done to integrate Rucio with Belle II distributed computing infrastructure as well as the migration strategy that was successfully performed to ensure a smooth transition.

scholarly journals Land-surface modelling in hydrological perspective

2005 ◽  
Vol 2 (6) ◽  
pp. 1815-1848 ◽  
Author(s):  
J. Overgaard ◽  
D. Rosbjerg ◽  
M. B. Butts
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Potential Evapotranspiration ◽  
Distributed Data ◽  
Atmospheric Models ◽  
Dynamic Coupling ◽  
Surface Modelling ◽  
Evaluation Procedures ◽  
Surface Models ◽  
Land Surface Modelling

Abstract. A comprehensive review of energy-based land-surface modelling, as seen from a hydrological perspective, is provided. We choose to focus on energy-based approaches, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail, and the difficulties inherent in various evaluation procedures are presented. Remote sensing is the only source of distributed data at scales that correspond to hydrological modelling scales. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the future perspectives of such efforts are discussed.

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