scholarly journals A Satellite Observation Data Transmission Scheduling Algorithm Oriented to Data Topics

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Hao Chen ◽  
Baorong Zhai ◽  
Jiangjiang Wu ◽  
Chun Du ◽  
Jun Li
Keyword(s):  
Data Transmission ◽  
Domain Knowledge ◽  
Scheduling Algorithm ◽  
Satellite Observation ◽  
Observation Data ◽  
Transmission Scheduling ◽  
Expected Time ◽  
Knowledge Based ◽  
Sensing Applications ◽  
Speed Up

The scheduling of Earth Observation Satellite (EOS) data transmission is a complex combinatorial optimization problem. With the development of remote sensing applications, a new special requirement named data transmission oriented to topics has appeared. It supposes that the data obtained from each observation activity by satellites belong to certain observation data topics, and every observation data topic has completeness and timeliness requirements. Unless all of the observation data belonging to one topic has been transmitted to the ground before the expected time, the value of the observation data will be decayed sharply and only a part of the rewards (or even no reward) for the data transmission will be obtained. Current researches do not meet the new data topic transmission requirements well. Based on the characteristics of the problem, a mathematic scheduling model is established, and a novel hybrid scheduling algorithm based on evolutionary computation is proposed. In order to further enhance the performance and speed up the convergence process of our algorithm, a domain-knowledge-based mutation operator is designed. Quantitative experimental results show that the proposed algorithm is more effective to solve the satellite observation data topic transmission scheduling problem than that of the state-of-the-art approaches.

A large-scale multiobjective satellite data transmission scheduling algorithm based on SVM+NSGA-II

2019 ◽  
Vol 50 ◽  
pp. 100560 ◽  
Author(s):  
Jiawei Zhang ◽  
Lining Xing ◽  
Guansheng Peng ◽  
Feng Yao ◽  
Cheng Chen
Keyword(s):  
Satellite Data ◽  
Data Transmission ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Transmission Scheduling ◽  
Nsga Ii

scholarly journals An Adaptive Multi-Channel Cooperative Data Transmission Scheduling in VANETs

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5612
Author(s):  
Benhong Zhang ◽  
Baorui Yuan ◽  
Xiang Bi ◽  
Zhenchun Wei ◽  
Mingyue Zhang
Keyword(s):  
Data Transmission ◽  
Model Simulation ◽  
Scheduling Algorithm ◽  
Transmission Scheduling ◽  
Service Capacity ◽  
Transmission Delays ◽  
The Road ◽  
High Data ◽  
Service Delay ◽  
Cooperative Scheduling

The Internet of Vehicle (IoV) technology is one of the most important technologies of modern intelligent transportation. The data transmission scheduling method is a research hotspot in the technology of IoV. It is a challenge to ensure the stability of data transmission due to fast network topology changes, high data transmission delays, and some other reasons. Aiming at the above problems, a multi-channel data transmission cooperative scheduling algorithm is proposed. First, construct a feasible interference map based on the data items sent and received by vehicles in the road scene. Second, assign channels to the nodes in the interference map based on the Signal-to-Interference-Noise-Ratio (SINR). Finally, the optimal multi-channel data transmission cooperative scheduling scheme is achieved through the ISing model. Simulation results show that compared with the traditional algorithm, the network service capacity is increased by about 31% and the service delay is reduced by about 20%. It ensures that emergency data is preferentially transmitted to the target vehicle and the maximum weighted service capacity of the network.

scholarly journals Comparison of ISS–CATS and CALIPSO–CALIOP Characterization of High Clouds in the Tropics

2020 ◽  
Vol 12 (23) ◽  
pp. 3946
Author(s):  
Pasquale Sellitto ◽  
Silvia Bucci ◽  
Bernard Legras
Keyword(s):  
Optical Properties ◽  
Space Station ◽  
Satellite Observation ◽  
Observation Data ◽  
Upper Troposphere ◽  
Cloud Properties ◽  
Synchronous Orbit ◽  
The Tropics ◽  
High Clouds

Clouds in the tropics have an important role in the energy budget, atmospheric circulation, humidity, and composition of the tropical-to-global upper-troposphere–lower-stratosphere. Due to its non-sun-synchronous orbit, the Cloud–Aerosol Transport System (CATS) onboard the International Space Station (ISS) provided novel information on clouds from space in terms of overpass time in the period of 2015–2017. In this paper, we provide a seasonally resolved comparison of CATS characterization of high clouds (between 13 and 18 km altitude) in the tropics with well-established CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation) data, both in terms of clouds’ occurrence and cloud optical properties (optical depth). Despite the fact that cloud statistics for CATS and CALIOP are generated using intrinsically different local overpass times, the characterization of high clouds occurrence and optical properties in the tropics with the two instruments is very similar. Observations from CATS underestimate clouds occurrence (up to 80%, at 18 km) and overestimate the occurrence of very thick clouds (up to 100% for optically very thick clouds, at 18 km) at higher altitudes. Thus, the description of stratospheric overshoots with CATS and CALIOP might be different. While this study hints at the consistency of CATS and CALIOP clouds characterizaton, the small differences highlighted in this work should be taken into account when using CATS for estimating cloud properties and their variability in the tropics.

scholarly journals Semantics-Driven Remote Sensing Scene Understanding Framework for Grounded Spatio-Contextual Scene Descriptions

2021 ◽  
Vol 10 (1) ◽  
pp. 32
Author(s):  
Abhishek V. Potnis ◽  
Surya S. Durbha ◽  
Rajat C. Shinde
Keyword(s):  
Remote Sensing ◽  
Domain Knowledge ◽  
Situational Awareness ◽  
Scene Understanding ◽  
Graph Representation ◽  
Observation Data ◽  
Test Scenario ◽  
Semantic Web Technologies ◽  
Earth Observation Data ◽  
Contextual Domain

Earth Observation data possess tremendous potential in understanding the dynamics of our planet. We propose the Semantics-driven Remote Sensing Scene Understanding (Sem-RSSU) framework for rendering comprehensive grounded spatio-contextual scene descriptions for enhanced situational awareness. To minimize the semantic gap for remote-sensing-scene understanding, the framework puts forward the transformation of scenes by using semantic-web technologies to Remote Sensing Scene Knowledge Graphs (RSS-KGs). The knowledge-graph representation of scenes has been formalized through the development of a Remote Sensing Scene Ontology (RSSO)—a core ontology for an inclusive remote-sensing-scene data product. The RSS-KGs are enriched both spatially and contextually, using a deductive reasoner, by mining for implicit spatio-contextual relationships between land-cover classes in the scenes. The Sem-RSSU, at its core, constitutes novel Ontology-driven Spatio-Contextual Triple Aggregation and realization algorithms to transform KGs to render grounded natural language scene descriptions. Considering the significance of scene understanding for informed decision-making from remote sensing scenes during a flood, we selected it as a test scenario, to demonstrate the utility of this framework. In that regard, a contextual domain knowledge encompassing Flood Scene Ontology (FSO) has been developed. Extensive experimental evaluations show promising results, further validating the efficacy of this framework.

Simulation of runoff for the Black Volta Basin using satellite observation data

2012 ◽  
Vol 10 (3) ◽  
pp. 245-254 ◽  
Author(s):  
Salamatu Shaibu ◽  
Samuel Nii Odai ◽  
Kwaku Amaning Adjei ◽  
Edward Matthew Osei ◽  
Frank Ohene Annor
Keyword(s):  
Satellite Observation ◽  
Observation Data ◽  
Volta Basin

Variational assimilation of observation data in the mathematical model of the Baltic Sea dynamics

2015 ◽  
Vol 30 (4) ◽  
Author(s):  
Valeriy I. Agoshkov ◽  
Eugene I. Parmuzin ◽  
Vladimir B. Zalesny ◽  
Victor P. Shutyaev ◽  
Natalia B. Zakharova ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Heat Flux ◽  
Baltic Sea ◽  
Satellite Observation ◽  
Sea Surface ◽  
Observation Data ◽  
The Baltic Sea ◽  
Variational Assimilation ◽  
The Baltic ◽  
The Mathematical Model

AbstractA mathematical model of the dynamics of the Baltic Sea is considered. A problem of variational assimilation of sea surface temperature (SST) data is formulated and studied. Based on variational assimilation of satellite observation data, an algorithm solving the inverse problem of heat flux restoration on the interface of two media is proposed. The results of numerical experiments reconstructing the heat flux functions in the problem of variational assimilation of SST observation data are presented. The influence of SST assimilation on other hydrodynamic parameters of the model is considered.

Configuration Tree Solver: A Technology for Automated Design and Configuration

1990 ◽  
Author(s):  
Alexander Kott ◽  
Gerald Agin ◽  
Dave Fawcett
Keyword(s):  
Problem Solving ◽  
General Model ◽  
General Class ◽  
Domain Knowledge ◽  
Automated Design ◽  
Automotive Component ◽  
Business Operation ◽  
Knowledge Based ◽  
Specific Configuration

Abstract Configuration is a process of generating a definitive description of a product or an order that satisfies a set of specified requirements and known constraints. Knowledge-based technology is an enabling factor in automation of configuration tasks found in the business operation. In this paper, we describe a configuration technique that is well suited for configuring “decomposable” artifacts with reasonably well defined structure and constraints. This technique may be classified as a member of a general class of decompositional approaches to configuration. The domain knowledge is structured as a general model of the artifact, an and-or hierarchy of the artifact’s elements, features, and characteristics. The model includes constraints and local specialists which are attached to the elements of the and-or-tree. Given the specific configuration requirements, the problem solving engine searches for a solution, a subtree, that satisfies the requirements and the applicable constraints. We describe an application of this approach that performs configuration and design of an automotive component.

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