Reducing Replica Update Cost in Replicated DRTDBS

2021 ◽  
Vol 11 (3) ◽  
pp. 15-28
Author(s):  
Pratik Shrivastava ◽  
Shailly Jain ◽  
Simran Gupta
Keyword(s):  
Data Access ◽  
Database System ◽  
Experimental Result ◽  
Data Mining Algorithm ◽  
Bandwidth Utilization ◽  
Communication Costs ◽  
Related Data ◽  
System Resource ◽  
Real Time Database ◽  
Existing Data

Replication techniques have drawn a great deal of appeal in the real-time database system (RTDBS). In this technique, the replication protocol (RPCL) has been studied as one of the primary technologies. Existing RPCL causes improper resource utilization and suffers from large communication costs. Hence, the objective is to propose a solution that effectively utilizes the system resource and decreases the large communication cost. The proposed data mining algorithm identifies the frequently accessed data items, their related data access sequence, and replicate those data items on the demanded replica sites. Additionally, mutual consistency among newly created data replica and existing data replica gets satisfied with the proposed RPCL. The experimental result shows that the proposed solutions improve the performance of the system by reducing the issue of unnecessary replica updation, unnecessary storage utilization, and unnecessary bandwidth utilization.

Special Database System Design Using Sector Organization and Server Clustering Techniques

2014 ◽  
Vol 915-916 ◽  
pp. 1377-1381
Author(s):  
Qiu Dong Sun ◽  
Jian Cun Zuo ◽  
Yu Feng Shao ◽  
Lin Gui
Keyword(s):  
Scheduling Algorithm ◽  
Data Access ◽  
Database System ◽  
Security Level ◽  
Good Efficiency ◽  
Clustering Techniques ◽  
Control Information ◽  
File Access ◽  
Information Server ◽  
Segmentation Methods

In order to reform the shortcomings of common database with a slower access speed and lower security level, this paper applied sector operating directly instead of general file access, and used the distributed computing and clustering techniques to form an information server cluster as the special database system. Firstly, the layout and sector segmentation methods were provided for data access in sector based database. And then some management methods were given to control information servers in the cluster. Finally, to more efficiently schedule the tasks for storing data and querying information, a dynamic and self-adaptive scheduling algorithm was introduced into the application server of cluster. The practice shows that the system developed by this design strategy has good efficiency and security, and the access speed of the special database system is almost 25 times than that of common database.

Abstract 12: Feasibility of Monitoring Covid-19 Related Stroke Patients Across a 14 Hospital Stroke System of Care

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Howard J Rho ◽  
Navdeep S Sangha
Keyword(s):  
Stroke Care ◽  
Stroke Patients ◽  
Specific Data ◽  
Related Data ◽  
Disease States ◽  
Hospital Systems ◽  
Pandemic Response ◽  
Relationship Of ◽  
The Relationship ◽  
Existing Data

Background: Identifying and tracking COVID-19 related data has been crucial to the pandemic response. Most hospital systems have created internal tracking databases specific to COVID-19 but separated from other disease specific data pools. Traditional methods for tracking and trending novel and specific data such as COVID-19 related strokes may require personnel with highly technical skills to abstract the data. We aimed to create a COVID-19 stroke dashboard which would easily auto-abstract and update data. Methods: A simple monitoring system was designed using PowerBI™ and Microsoft Suite™ products that model existing data sources without using other IT resources. Existing data queries from various sources were modeled into one report and the resulting data model was used to track and trend incidence of COVID-19 and its relationship to stroke care throughout a 14- hospital stroke system. Results: The report allowed region-wide identification and evaluation of several metrics, including: volume of code strokes, the volume of patients who had a stroke within two weeks before or after testing positive for COVID-19, the initial NIHSS, if alteplase was administered, reason for no alteplase administration, delay in alteplase administration and if related to COVID-19 and the relationship of COVID-19 cases to the volume of code strokes. It was found that the volume of code strokes significantly decreased during the time of the pandemic and was inversely related to the volume of COVID-19 positive cases being reported in a county. The tool also found that COVID-19 positive stroke patients increased as the overall COVID-19 hospital volume increased. Conclusion: Assessing the relationships between a novel disease and other disease states may lead to changes in hospital workflows and practices resulting into improved patient outcomes.

scholarly journals Adaptive Broadcasting Mechanism for Bandwidth Allocation in Mobile Services

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Gwo-Jiun Horng ◽  
Chi-Hsuan Wang ◽  
Chih-Lun Chou
Keyword(s):  
Analytical Model ◽  
Bandwidth Allocation ◽  
Data Dissemination ◽  
Data Access ◽  
Experimental Results ◽  
Bandwidth Utilization ◽  
Access Latency ◽  
The Mean ◽  
Access Efficiency ◽  
Broadcast Program

This paper proposes a tree-based adaptive broadcasting (TAB) algorithm for data dissemination to improve data access efficiency. The proposed TAB algorithm first constructs a broadcast tree to determine the broadcast frequency of each data and splits the broadcast tree into some broadcast wood to generate the broadcast program. In addition, this paper develops an analytical model to derive the mean access latency of the generated broadcast program. In light of the derived results, both the index channel’s bandwidth and the data channel’s bandwidth can be optimally allocated to maximize bandwidth utilization. This paper presents experiments to help evaluate the effectiveness of the proposed strategy. From the experimental results, it can be seen that the proposed mechanism is feasible in practice.

Transaction Processing in the Rodain Real-Time Database System

1997 ◽  
pp. 355-377 ◽  
Author(s):  
Jukka Kiviniemi ◽  
Tiina Niklander ◽  
Pasi Porkka ◽  
Kimmo Raatikainen
Keyword(s):  
Real Time ◽  
Transaction Processing ◽  
Database System ◽  
Real Time Database

scholarly journals Extending TCGA queries to automatically identify analogous genomic data from dbGaP

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 319
Author(s):  
Erin K. Wagner ◽  
Satyajeet Raje ◽  
Liz Amos ◽  
Jessica Kurata ◽  
Abhijit S. Badve ◽  
...  
Keyword(s):  
Genomic Data ◽  
The Cancer Genome Atlas ◽  
Genomic Research ◽  
Reproducible Research ◽  
Software Pipeline ◽  
Individual Level ◽  
Related Data ◽  
Cancer Genome Atlas ◽  
Existing Data ◽  
Genome Atlas

Data sharing is critical to advance genomic research by reducing the demand to collect new data by reusing and combining existing data and by promoting reproducible research. The Cancer Genome Atlas (TCGA) is a popular resource for individual-level genotype-phenotype cancer related data. The Database of Genotypes and Phenotypes (dbGaP) contains many datasets similar to those in TCGA. We have created a software pipeline that will allow researchers to discover relevant genomic data from dbGaP, based on matching TCGA metadata. The resulting research provides an easy to use tool to connect these two data sources.

scholarly journals The use of biodiversity data in spatial planning and impact assessment in Europe

2018 ◽  
Vol 4 ◽  
pp. e28045 ◽  
Author(s):  
Evelyn Underwood ◽  
Katie Taylor ◽  
Graham Tucker
Keyword(s):  
Data Collection ◽  
Impact Assessment ◽  
Local Governments ◽  
Spatial Planning ◽  
Data Access ◽  
Individual Development ◽  
Federal State ◽  
Biodiversity Data ◽  
Existing Data ◽  
The Eu

This review identifies successful approaches to collating and using biodiversity data in spatial planning and impact assessment, the barriers to obtaining and using existing data sources, and the key data gaps that hinder effective implementation. The analysis is a contribution to the EU BON project funded by the European Commission FP7 research programme, which aimed to identify and pilot new approaches to overcome gaps in biodiversity data in conservation policy at European and national levels. The consideration of biodiversity in impact assessments and spatial planning requires spatially explicit biodiversity data of various types. Where spatial plans take account of biodiversity, there are opportunities through Strategic Environmental Assessment (SEA) of development plans and Environmental Impact Assessment (EIA) of individual development proposals to ensure that consented activities are consistent with no net loss of biodiversity or even a net gain, and help to maintain or develop coherent ecological networks. However, biodiversity components of SEAs and EIAs have often been found to be of insufficient quality due to the lack of data or the inadequate use of existing data. Key obstacles to providing access to biodiversity data include the need for data standardisation and data quality governance and systems, licensing approaches to increase data access, and lack of resources to target gaps in data coverage and to develop and advertise policy-relevant data products. Existing data platforms differ in the degree to which they successfully provide a service to spatial planners and impact assessment practitioners. Some local governments, for example Somerset County Council in the UK and the Bremen federal state in Germany, have invested in integrated data collection and management systems that now provide intensively used tools for spatial planning and impact assessment informed by local data collection and monitoring. The EU BON biodiversity data portal aims to provide a platform that is an access point to datasets relevant to essential biodiversity variables on species, habitats and ecosystems. The EU BON taxonomic backbone provides an integrated search function for species and taxa according to different classifications, and also provides a range of tools for data analysis and decision-support. This will increase the accessibility of the vast range of biodiversity data available in different sources and allow the targeting of future data collection to address current gaps.

scholarly journals An Efficient Row Key Encoding Method with ASCII Code for Storing Geospatial Big Data in HBase

2020 ◽  
Vol 9 (11) ◽  
pp. 625
Author(s):  
Quan Xiong ◽  
Xiaodong Zhang ◽  
Wei Liu ◽  
Sijing Ye ◽  
Zhenbo Du ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Distributed Storage ◽  
Meteorological Data ◽  
Data Access ◽  
Henan Province ◽  
Geospatial Data ◽  
Experimental Result ◽  
Raster Data ◽  
Encoding Method ◽  
Original Grid

Recently, increasing amounts of multi-source geospatial data (raster data of satellites and textual data of meteorological stations) have been generated, which can play a cooperative and important role in many research works. Efficiently storing, organizing and managing these data is essential for their subsequent application. HBase, as a distributed storage database, is increasingly popular for the storage of unstructured data. The design of the row key of HBase is crucial to improving its efficiency, but large numbers of researchers in the geospatial area do not conduct much research on this topic. According the HBase Official Reference Guide, row keys should be kept as short as is reasonable while remaining useful for the required data access. In this paper, we propose a new row key encoding method instead of conventional stereotypes. We adopted an existing hierarchical spatio-temporal grid framework as the row key of the HBase to manage these geospatial data, with the difference that we utilized the obscure but short American Standard Code for Information Interchange (ASCII) to achieve the structure of the grid rather than the original grid code, which can be easily understood by humans but is very long. In order to demonstrate the advantage of the proposed method, we stored the daily meteorological data of 831 meteorological stations in China from 1985 to 2019 in HBase; the experimental result showed that the proposed method can not only maintain an equivalent query speed but can shorten the row key and save storage resources by 20.69% compared with the original grid codes. Meanwhile, we also utilized GF-1 imagery to test whether these improved row keys could support the storage and querying of raster data. We downloaded and stored a part of the GF-1 imagery in Henan province, China from 2017 to 2018; the total data volume reached about 500 GB. Then, we succeeded in calculating the daily normalized difference vegetation index (NDVI) value in Henan province from 2017 to 2018 within 54 min. Therefore, the experiment demonstrated that the improved row keys can also be applied to store raster data when using HBase.

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