A Hierarchical of Security Situation Element Acquisition Mechanism in Wireless Sensor Network Article Swipe
Fangwei Li
,
Yan Wang
,
Jiang Zhu
,
Xinyue Zhang
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.4108/icst.mobimedia.2015.259030
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.4108/icst.mobimedia.2015.259030
In wireless sensor network, the processing ability of the sensor nodes is poor. And the security situational element acquisition is also a serious problem. Thus, this paper proposes a hierarchical framework of security situational elements acquisition mechanism. In this framework, support vector machine hyper sphere multi class algorithm is introduced as basic classifier. The method of attribute reduction uses non negative matrix factorization algorithm. The fuzzy classification algorithm used to initialize non negative matrix factorization, in order to avoid the local optimal which is caused by non negative matrix factorization random initialization. In the sink node classification rules and attribute reduction rules are formed by learning. The classification analyses respectively focus on the cluster head and sink node, which can reduce the requirement of the sensor node properties. Attribute reduction before the data transmission, which reduces communication consumption data transmission, improves the performance of classifiers. By simulation analysis, the scheme has preferably accuracy in the situation elements acquisiton, and smaller communication overhead in the process of information transmission.
Related Topics
Concepts
Wireless sensor network
Computer science
Mechanism (biology)
Key distribution in wireless sensor networks
Situation awareness
Computer network
Element (criminal law)
Wireless
Situation analysis
Wireless network
Computer security
Distributed computing
Telecommunications
Engineering
Business
Epistemology
Aerospace engineering
Philosophy
Law
Marketing
Political science
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.4108/icst.mobimedia.2015.259030
- http://eudl.eu/pdf/10.4108/icst.mobimedia.2015.259030
- OA Status
- gold
- References
- 5
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2296588934
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2296588934Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.4108/icst.mobimedia.2015.259030Digital Object Identifier
- Title
-
A Hierarchical of Security Situation Element Acquisition Mechanism in Wireless Sensor NetworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-01-01Full publication date if available
- Authors
-
Fangwei Li, Yan Wang, Jiang Zhu, Xinyue ZhangList of authors in order
- Landing page
-
https://doi.org/10.4108/icst.mobimedia.2015.259030Publisher landing page
- PDF URL
-
https://eudl.eu/pdf/10.4108/icst.mobimedia.2015.259030Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://eudl.eu/pdf/10.4108/icst.mobimedia.2015.259030Direct OA link when available
- Concepts
-
Wireless sensor network, Computer science, Mechanism (biology), Key distribution in wireless sensor networks, Situation awareness, Computer network, Element (criminal law), Wireless, Situation analysis, Wireless network, Computer security, Distributed computing, Telecommunications, Engineering, Business, Epistemology, Aerospace engineering, Philosophy, Law, Marketing, Political scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
5Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.hyper | 43 |
| abstract_inverted_index.local | 80 |
| abstract_inverted_index.multi | 45 |
| abstract_inverted_index.node, | 117 |
| abstract_inverted_index.nodes | 10 |
| abstract_inverted_index.order | 76 |
| abstract_inverted_index.paper | 26 |
| abstract_inverted_index.poor. | 12 |
| abstract_inverted_index.rules | 97, 101 |
| abstract_inverted_index.which | 82, 118, 134 |
| abstract_inverted_index.before | 130 |
| abstract_inverted_index.caused | 84 |
| abstract_inverted_index.formed | 103 |
| abstract_inverted_index.matrix | 61, 73, 88 |
| abstract_inverted_index.method | 54 |
| abstract_inverted_index.random | 90 |
| abstract_inverted_index.reduce | 120 |
| abstract_inverted_index.scheme | 149 |
| abstract_inverted_index.sensor | 2, 9, 125 |
| abstract_inverted_index.sphere | 44 |
| abstract_inverted_index.vector | 41 |
| abstract_inverted_index.ability | 6 |
| abstract_inverted_index.cluster | 113 |
| abstract_inverted_index.element | 17 |
| abstract_inverted_index.machine | 42 |
| abstract_inverted_index.optimal | 81 |
| abstract_inverted_index.process | 164 |
| abstract_inverted_index.reduces | 135 |
| abstract_inverted_index.serious | 22 |
| abstract_inverted_index.smaller | 159 |
| abstract_inverted_index.support | 40 |
| abstract_inverted_index.accuracy | 152 |
| abstract_inverted_index.analyses | 108 |
| abstract_inverted_index.elements | 34, 156 |
| abstract_inverted_index.improves | 140 |
| abstract_inverted_index.negative | 60, 72, 87 |
| abstract_inverted_index.network, | 3 |
| abstract_inverted_index.overhead | 161 |
| abstract_inverted_index.problem. | 23 |
| abstract_inverted_index.proposes | 27 |
| abstract_inverted_index.security | 15, 32 |
| abstract_inverted_index.wireless | 1 |
| abstract_inverted_index.Attribute | 128 |
| abstract_inverted_index.algorithm | 47, 67 |
| abstract_inverted_index.analysis, | 147 |
| abstract_inverted_index.attribute | 56, 99 |
| abstract_inverted_index.framework | 30 |
| abstract_inverted_index.learning. | 105 |
| abstract_inverted_index.reduction | 57, 100, 129 |
| abstract_inverted_index.situation | 155 |
| abstract_inverted_index.algorithm. | 63 |
| abstract_inverted_index.framework, | 39 |
| abstract_inverted_index.initialize | 70 |
| abstract_inverted_index.introduced | 49 |
| abstract_inverted_index.mechanism. | 36 |
| abstract_inverted_index.preferably | 151 |
| abstract_inverted_index.processing | 5 |
| abstract_inverted_index.simulation | 146 |
| abstract_inverted_index.acquisition | 18, 35 |
| abstract_inverted_index.acquisiton, | 157 |
| abstract_inverted_index.classifier. | 52 |
| abstract_inverted_index.consumption | 137 |
| abstract_inverted_index.information | 166 |
| abstract_inverted_index.performance | 142 |
| abstract_inverted_index.properties. | 127 |
| abstract_inverted_index.requirement | 122 |
| abstract_inverted_index.situational | 16, 33 |
| abstract_inverted_index.classifiers. | 144 |
| abstract_inverted_index.hierarchical | 29 |
| abstract_inverted_index.respectively | 109 |
| abstract_inverted_index.communication | 136, 160 |
| abstract_inverted_index.factorization | 62, 89 |
| abstract_inverted_index.transmission, | 133, 139 |
| abstract_inverted_index.transmission. | 167 |
| abstract_inverted_index.classification | 66, 96, 107 |
| abstract_inverted_index.factorization, | 74 |
| abstract_inverted_index.initialization. | 91 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/1 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | No poverty |
| citation_normalized_percentile.value | 0.16948906 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |