Service-Driven Data Management Framework for Electric Power Sensor Networks

Author(s):  
Ziqi Wang ◽  
Ying Liu ◽  
Yudong Wang ◽  
Kexuan Song
2005 ◽  
Vol 47 (2) ◽  
Author(s):  
Pedro José Marrón ◽  
Daniel Minder ◽  
Andreas Lachenmann ◽  
Kurt Rothermel

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.


2012 ◽  
Vol 6 (3) ◽  
pp. 137-160 ◽  
Author(s):  
Gianni Giorgetti ◽  
Richard Farley ◽  
Kiran Chikkappa ◽  
Judy Ellis ◽  
Telis Kaleas

1989 ◽  
Vol 25 (5) ◽  
pp. 3821-3823
Author(s):  
H. Yoda ◽  
S. Kurashima ◽  
M. Endoh ◽  
N. Wakatsuki

Author(s):  
Subhra Prosun Paul ◽  
◽  
Dr. Shruti Aggarwal ◽  

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.


2012 ◽  
Vol 12 (11) ◽  
pp. 1237-1242 ◽  
Author(s):  
Walter Cedeno ◽  
Simson Alex ◽  
Edward P. Jaeger ◽  
Dimitris K. Agrafiotis ◽  
Victor S. Lobanov

2017 ◽  
Author(s):  
Andrei Tsaregorodstsev ◽  

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