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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  4/2013 - 1
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Rich: Region-based Intelligent Cluster-Head Selection and Node Deployment Strategy in Concentric-based WSNs

FAN, C.-S. See more information about FAN, C.-S. on SCOPUS See more information about FAN, C.-S. on IEEExplore See more information about FAN, C.-S. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (765 KB) | Citation | Downloads: 1,014 | Views: 2,095

Author keywords
clustering methods, energy consumption, wireless sensor networks, energy efficiency, routing protocols

References keywords
sensor(25), networks(23), deployment(8), lifetime(4), information(4), energy(4), communications(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-11-30
Volume 13, Issue 4, Year 2013, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.04001
Web of Science Accession Number: 000331461300001
SCOPUS ID: 84890143555

Abstract
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Full text preview
In a random deployment, sensor nodes are scattered randomly in the sensing field. Hence, the coverage can not be guaranteed. In contrast, the coverage of uniformly deployment is in general larger than the random deployment. However, uniformly deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs). In this situation, larger load may be imposed to CHs (cluster heads) around the sink. Therefore, CHs close to the sink use up their energy earlier than those farther away from the sink. To overcome this problem, we propose a novel node deployment strategy in the concentric model, namely, Region-based Intelligent Cluster-Head selection and node deployment strategy (called Rich). The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed Rich scheme. The simulation results show that the proposed Rich alleviates the unbalanced traffic pattern significantly, prolongs network lifetime and achieves satisfactory coverage ratio.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 42]


[2] W. Fang, S. Li, X. Liang and Z. Li, "Cluster-based Data Gathering in Long-Strip Wireless Sensor Networks," Advances in Electrical and Computer Engineering, vol. 12, no. 1, pp. 3-8, Feb. 2012.
[CrossRef] [Full Text] [Web of Science Times Cited 4] [SCOPUS Times Cited 7]


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[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 16]


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[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 3]


[6] N. Essaddi, M. Hamdi, S. Habib and N. Boudriga, "Evolutionary strategies for non-uniform deployment in wireless sensor networks," Int. J. of Communication Networks and Distrib. Systems, vol. 7, no. 3/4, pp. 331-354, May 2011.
[CrossRef] [SCOPUS Times Cited 2]


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[CrossRef] [SCOPUS Times Cited 44]


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[CrossRef] [Web of Science Times Cited 21] [SCOPUS Times Cited 38]


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[CrossRef] [SCOPUS Times Cited 22]


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[CrossRef] [SCOPUS Times Cited 30]


[11] Y. Xin, T. Guven and M. Shayman, "Relay Deployment and Power Control for Lifetime Elongation in Sensor Networks," Proceedings of the IEEE Int. Conf. on Communications (ICC), pp. 3461-3466, June 2006.
[CrossRef] [SCOPUS Times Cited 21]


[12] N. Kulkarni, R. Prasad, H. Cornean and N. Gupta, "Performance Evaluation of AODV, DSDV and DSR for Quasi Random Deployment of Sensor Nodes in Wireless Sensor Networks," Int. Conf. on Devices and Communications (ICDeCom), pp. 1-5, Feb. 2011.
[CrossRef] [SCOPUS Times Cited 11]


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[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 59]


[14] P. Balister and S. Kumar, "Random vs. Deterministic Deployment of Sensors in the Presence of Failures and Placement Errors," IEEE Int. Conf. on Computer Communications (INFOCOM), pp. 2896-2900, Apr. 2009.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 33]


[15] G. Chen, S.K. Das and X. Wu, "Avoiding energy holes in wireless sensor networks with nonuniform node distribution," IEEE Trans. on Parallel and Distrib. Systems, vol.19, no.5, pp.710-720, May 2008.
[CrossRef] [Web of Science Times Cited 193] [SCOPUS Times Cited 312]


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[CrossRef] [SCOPUS Times Cited 16]


[18] D. Ganesan, R. Cristescu and B.B. Lozano, "Power Efficient Sensor Placement and Transmission Structure for Data Gathering under Distortion Constraints," ACM Trans. on Sensor Networks, vol. 2, no. 2, pp. 155-181, May 2006.
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[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 56]


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[CrossRef] [SCOPUS Times Cited 13]


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[CrossRef] [Web of Science Times Cited 3324] [SCOPUS Times Cited 5658]




References Weight

Web of Science® Citations for all references: 3,770 TCR
SCOPUS® Citations for all references: 6,567 TCR

Web of Science® Average Citations per reference: 171 ACR
SCOPUS® Average Citations per reference: 299 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-06-26 13:36 in 161 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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