A Cognitive Research Tendency in Data Management of Sensor Network

2021 ◽  
pp. 26-36
Author(s):  
Subhra Prosun Paul ◽  
◽  
Dr. Shruti Aggarwal ◽  
Keyword(s):  
Sensor Networks ◽  
Data Management ◽  
Sensor Network ◽  
High Speed ◽  
Web Of Science ◽  
Data Access ◽  
Global Perspective ◽  
Data Movement ◽  
Network Database ◽  
Cognitive Research

In today’s World sensor networks offer various opportunities for data management applications because of their low cost, reliability, scalability, high-speed data processing, and other versatile advantageous purposes. It is a great challenge to organize data effectively and to retrieve the appropriate data from the large volume of various data sets in ad-hoc network databases, mobile databases, etc. The sensor network is necessary for routing of data, performance analysis of data management activities, and data incorporation for the right application. Data management involves intranet and extranet query handling, data access mechanism, modeling of data, different data movement algorithm, data warehousing, and data mining of network database. Additionally, connectivity, design, and lifetime are important issues for sensor networks to perform all data management activities smoothly. In this paper, we are trying to give a cognitive research tendency of Sensor network data management in the last two decades considering all the challenges and issues of both sensor network database and data management functions using Scopus and Web of Science database. To analyze data, different assessments are done considering various parameters like the author, time, publication and citation number, place, source, document separately for Web of Science and Scopus database in global perspective. It is noticed that there is a significant growth of research in data management for sensor networks because of the popularity of this topic.

TinyCubus: An Adaptive Cross-Layer Framework for Sensor Networks (TinyCubus: Ein Adaptives Cross-Layer Framework für Sensornetze)

2005 ◽  
Vol 47 (2) ◽  
Author(s):  
Pedro José Marrón ◽  
Daniel Minder ◽  
Andreas Lachenmann ◽  
Kurt Rothermel
Keyword(s):  
Sensor Networks ◽  
Data Management ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Cross Layer ◽  
Relevant Research ◽  
Management Framework ◽  
Network Applications ◽  
Application Requirements ◽  
Over Time

SummuryWith the proliferation of sensor networks and sensor network applications, the overall complexity of such systems is continuously increasing. Sensor networks are now heterogeneous in terms of their hardware characteristics and application requirements even within a single network. In addition, the requirements of currently supported applications are expected to change over time. All of this makes developing, deploying, and optimizing sensor network applications an extremely difficult task. In this paper, we present the architecture of TinyCubus, a flexible and adaptive cross-layer framework for TinyOS-based sensor networks that aims at providing the necessary infrastructure to cope with the complexity of such systems. TinyCubus consists of a cross-layer framework that enables optimizations through cross-layer interactions, a configuration engine that distributes components efficiently by considering the roles of the sensor nodes and provides support to install components dynamically, and a data management framework that selects and adapts both system and data management components. Finally, relevant research challenges associated with the development of each framework are identified and discussed in the paper.

Research on Database Design Based on Wireless Sensor Network

2014 ◽  
Vol 539 ◽  
pp. 239-242
Author(s):  
Wei Jiang Geng
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Programming Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Embedded Operating System ◽  
Network Nodes ◽  
Network Database ◽  
Component Models

This paper analyzes the composition of architecture and sensor nodes in wireless sensor networks, component models running on the nodes embedded operating system and programming model based on nesC. Then, we analyze network databases based on wireless sensor, design and implement wireless sensor network database TaraxDB, focused on design and implement the receiving client inquiries, analysis and presentation, send queries and receive results between the database client and sensor networks, database client Receive query and submit the results between the client and the user, The main feature on the database, including front-end and network nodes, as well as the completion of key technical queries collaboration between nodes.

scholarly journals Ten simple rules for managing high-throughput nucleotide sequencing data

2016 ◽  
Author(s):  
Rutger A. Vos
Keyword(s):  
Data Management ◽  
High Throughput ◽  
Large Data ◽  
Data Access ◽  
Nucleotide Sequencing ◽  
Data Generation ◽  
Sequencing Data ◽  
Data Movement ◽  
Simple Rules ◽  
Bandwidth Consumption

AbstractThe challenges posed by large data volumes produced by high-throughput nucleotide sequencing technologies are well known. This document establishes ten simple rules for coping with these challenges. At the level of master data management, (1) data triage reduces data volumes; (2) some lossless data representations are much more compact than others; (3) careful management of data replication reduces wasted storage space. At the level of data analysis, (4) automated analysis pipelines obviate the need for storing work files; (5) virtualization reduces the need for data movement and bandwidth consumption; (6) tracking of data and analysis provenance will generate a paper trail to better understand how results were produced. At the level of data access and sharing, (7) careful modeling of data movement patterns reduces bandwidth consumption and haphazard copying; (8) persistent, resolvable identifiers for data reduce ambiguity caused by data movement; (9) sufficient metadata enables more effective collaboration. Finally, because of rapid developments in HTS technologies, (10) agile practices that combine loosely coupled modules operating on standards-compliant data are the best approach for avoiding lock-in. A generalized scenario is presented for data management from initial raw data generation to publication of result data.

scholarly journals Structured peer-to-peer-based publication and sharing of ontologies to automatically process SPARQL query on a semantic sensor network

2018 ◽  
Vol 14 (10) ◽  
pp. 155014771879758 ◽  
Author(s):  
Huayou Si ◽  
Yajie Qi ◽  
Meilian Zheng ◽  
Yongjian Ren ◽  
Lifeng Yu
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Data Access ◽  
Peer To Peer ◽  
Sparql Query ◽  
Conceptual Level ◽  
Semantic Query

In recent years, semantic sensor networks are proposed, which apply ontologies to provide query capabilities and data access and allow users to express their needs at a conceptual level. In such sensor networks, a large amount of web ontologies are separately created by sensors to represent their own knowledge. These ontologies are distributed in different sensors and provide knowledge for semantic queries. It has become a very pressing issue to locate the desired ontologies for a given semantic query. To address this issue, we propose an approach based on structured peer-to-peer protocol to publish shareable ontologies on different sensors and automatically discover the ontologies useful for a given SPARQL query. Therefore, if a SPARQL query is given, our approach can locate ontologies desired and further send the query to them to find out solutions for the query. In addition, if solutions can be found out from a web ontology published, our approach makes sure to discover the ontology and get the solutions from it for the query. We conduct three experiments to evaluate the approach, the results of which demonstrate that our approach is effective and efficient.

scholarly journals Information Processing and Data Management Technology in Wireless Sensor Networks

2018 ◽  
Vol 14 (09) ◽  
pp. 66
Author(s):  
Yong Liu ◽  
Baohua Liang ◽  
Jiabao Jiang
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Data Management ◽  
Sensor Network ◽  
Distributed Database ◽  
Wireless Sensor ◽  
Head Node ◽  
Continuous Stream

<p>The wireless sensor network is essentially a data-centric network that processes the continuous stream of data, which is collected by different sensors. Therefore, the existing data management technologies regard the wireless sensor network, which is named WSN as a distributed database, and it is composed of continuous data streams from the physical world. Wireless sensor networks are emerging next-generation sensor networks, but their transmission of information is highly dependent. The wireless sensor network processes the continuous stream of data collected by the sensor. Based on the features of wireless sensor networks, this paper presents a topology-dependent model of cluster evolution with fault tolerance. Through the limited data management, resources have reasonably configured, while also saving energy. The model is based on the energy-aware routing protocol in its network layer protocols. The key point is the energy routing principle. According to its own local view, the cluster head node builds the inter-cluster topology to achieve fault-tolerant and energy-saving goals. Simulation results show that the model has good fault tolerance and energy efficiency.</p>

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