Different InterCriteria Analysis of Variants of ACO algorithm for Wireless Sensor Network Positioning View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019-06-22

AUTHORS

Olympia Roeva , Stefka Fidanova

ABSTRACT

Wireless sensor networks Roeva, Olympia formed by spatially distributed sensors, which communicate in a wireless way. This network can monitor various kinds of environment and physical conditions like movement, noise, light, humidity, images, Fidanova, Stefka substances etc. A given area needs to be fully covered with minimal number of sensors and the energy consumption of the network needs to be minimal too. We propose several algorithms, based on Ant Colony Optimization, to solve the problem. We study the algorithms behavior when the number of ants varies from 1 to 10. We apply InterCriteria analysis to study relations between proposed algorithms and number of ants and analyse correlation between them. Four different algorithms of ICrA—\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu $$\end{document}-biased, Balanced, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nu $$\end{document}-biased and Unbiased—are applied. The obtained results are discussed in order to find the stronger correlations between considered hybrid ACO algorithms. More... »

PAGES

83-103

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_6

DOI

http://dx.doi.org/10.1007/978-3-030-22723-4_6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1117402914


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1005", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Communications Technologies", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 105, 1113, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.493309.4", 
          "name": [
            "Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 105, 1113, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Roeva", 
        "givenName": "Olympia", 
        "id": "sg:person.015745057111.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015745057111.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 25A, 1113, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.424988.b", 
          "name": [
            "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 25A, 1113, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "id": "sg:person.011173106320.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2019-06-22", 
    "datePublishedReg": "2019-06-22", 
    "description": "Wireless sensor networks Roeva, Olympia\u00a0formed by spatially distributed sensors, which communicate in a wireless way. This network can monitor various kinds of environment and physical conditions like movement, noise, light, humidity, images, Fidanova, Stefka\u00a0substances etc. A given area needs to be fully covered with minimal number of sensors and the energy consumption of the network needs to be minimal too. We propose several algorithms, based on Ant Colony Optimization, to solve the problem. We study the algorithms behavior when the number of ants varies from 1 to 10. We apply InterCriteria analysis to study relations between proposed algorithms and number of ants and analyse correlation between them. Four different algorithms of ICrA\u2014\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym}\n\t\t\t\t\\usepackage{amsfonts}\n\t\t\t\t\\usepackage{amssymb}\n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\mu $$\\end{document}-biased, Balanced, \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym}\n\t\t\t\t\\usepackage{amsfonts}\n\t\t\t\t\\usepackage{amssymb}\n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\nu $$\\end{document}-biased and Unbiased\u2014are applied. The obtained results are discussed in order to find the stronger correlations between considered hybrid ACO algorithms.", 
    "editor": [
      {
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-030-22723-4_6", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-030-22722-7", 
        "978-3-030-22723-4"
      ], 
      "name": "Recent Advances in Computational Optimization", 
      "type": "Book"
    }, 
    "keywords": [
      "ACO algorithm", 
      "Ant Colony Optimization", 
      "kind of environment", 
      "InterCriteria Analysis", 
      "wireless way", 
      "different algorithms", 
      "colony optimization", 
      "wireless sensor network positioning", 
      "algorithm behavior", 
      "algorithm", 
      "number of ants", 
      "energy consumption", 
      "network", 
      "network positioning", 
      "hybrid ACO algorithm", 
      "minimal number", 
      "sensors", 
      "images", 
      "ICrA", 
      "optimization", 
      "environment", 
      "number", 
      "Balanced", 
      "noise", 
      "analyse correlation", 
      "ants", 
      "kind", 
      "way", 
      "order", 
      "consumption", 
      "positioning", 
      "analysis", 
      "results", 
      "variants", 
      "movement", 
      "area", 
      "behavior", 
      "physical conditions", 
      "correlation", 
      "relation", 
      "strong correlation", 
      "conditions", 
      "Olympia", 
      "humidity", 
      "light", 
      "problem", 
      "substances"
    ], 
    "name": "Different InterCriteria Analysis of Variants of ACO algorithm for Wireless Sensor Network Positioning", 
    "pagination": "83-103", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1117402914"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-030-22723-4_6"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-030-22723-4_6", 
      "https://app.dimensions.ai/details/publication/pub.1117402914"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-05-10T10:52", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/chapter/chapter_416.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-030-22723-4_6"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_6'


 

This table displays all metadata directly associated to this object as RDF triples.

117 TRIPLES      23 PREDICATES      72 URIs      65 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-030-22723-4_6 schema:about anzsrc-for:10
2 anzsrc-for:1005
3 schema:author N4eabff4dd6e245a384b2abf5bb8968c1
4 schema:datePublished 2019-06-22
5 schema:datePublishedReg 2019-06-22
6 schema:description Wireless sensor networks Roeva, Olympia formed by spatially distributed sensors, which communicate in a wireless way. This network can monitor various kinds of environment and physical conditions like movement, noise, light, humidity, images, Fidanova, Stefka substances etc. A given area needs to be fully covered with minimal number of sensors and the energy consumption of the network needs to be minimal too. We propose several algorithms, based on Ant Colony Optimization, to solve the problem. We study the algorithms behavior when the number of ants varies from 1 to 10. We apply InterCriteria analysis to study relations between proposed algorithms and number of ants and analyse correlation between them. Four different algorithms of ICrA—\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu $$\end{document}-biased, Balanced, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nu $$\end{document}-biased and Unbiased—are applied. The obtained results are discussed in order to find the stronger correlations between considered hybrid ACO algorithms.
7 schema:editor Ncad00373c5714361b824e6b127442710
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N1f6b397df5014ad781335bce05e66de9
12 schema:keywords ACO algorithm
13 Ant Colony Optimization
14 Balanced
15 ICrA
16 InterCriteria Analysis
17 Olympia
18 algorithm
19 algorithm behavior
20 analyse correlation
21 analysis
22 ants
23 area
24 behavior
25 colony optimization
26 conditions
27 consumption
28 correlation
29 different algorithms
30 energy consumption
31 environment
32 humidity
33 hybrid ACO algorithm
34 images
35 kind
36 kind of environment
37 light
38 minimal number
39 movement
40 network
41 network positioning
42 noise
43 number
44 number of ants
45 optimization
46 order
47 physical conditions
48 positioning
49 problem
50 relation
51 results
52 sensors
53 strong correlation
54 substances
55 variants
56 way
57 wireless sensor network positioning
58 wireless way
59 schema:name Different InterCriteria Analysis of Variants of ACO algorithm for Wireless Sensor Network Positioning
60 schema:pagination 83-103
61 schema:productId N17f433b445784c6bb51ee39484eb5ed2
62 N8262ab78c18d4fc4bc2f628182414bba
63 schema:publisher Nf9e6c573e9294ed2947c9019af1b8244
64 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117402914
65 https://doi.org/10.1007/978-3-030-22723-4_6
66 schema:sdDatePublished 2022-05-10T10:52
67 schema:sdLicense https://scigraph.springernature.com/explorer/license/
68 schema:sdPublisher N6ad6fc8c5ab64a32b456525a72e31e07
69 schema:url https://doi.org/10.1007/978-3-030-22723-4_6
70 sgo:license sg:explorer/license/
71 sgo:sdDataset chapters
72 rdf:type schema:Chapter
73 N03cde283104147059941ccdd9b409807 schema:familyName Fidanova
74 schema:givenName Stefka
75 rdf:type schema:Person
76 N17f433b445784c6bb51ee39484eb5ed2 schema:name doi
77 schema:value 10.1007/978-3-030-22723-4_6
78 rdf:type schema:PropertyValue
79 N1f6b397df5014ad781335bce05e66de9 schema:isbn 978-3-030-22722-7
80 978-3-030-22723-4
81 schema:name Recent Advances in Computational Optimization
82 rdf:type schema:Book
83 N4eabff4dd6e245a384b2abf5bb8968c1 rdf:first sg:person.015745057111.08
84 rdf:rest Ncedbd757131d4d00ba278a3b60bf1b98
85 N6ad6fc8c5ab64a32b456525a72e31e07 schema:name Springer Nature - SN SciGraph project
86 rdf:type schema:Organization
87 N8262ab78c18d4fc4bc2f628182414bba schema:name dimensions_id
88 schema:value pub.1117402914
89 rdf:type schema:PropertyValue
90 Ncad00373c5714361b824e6b127442710 rdf:first N03cde283104147059941ccdd9b409807
91 rdf:rest rdf:nil
92 Ncedbd757131d4d00ba278a3b60bf1b98 rdf:first sg:person.011173106320.18
93 rdf:rest rdf:nil
94 Nf9e6c573e9294ed2947c9019af1b8244 schema:name Springer Nature
95 rdf:type schema:Organisation
96 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
97 schema:name Technology
98 rdf:type schema:DefinedTerm
99 anzsrc-for:1005 schema:inDefinedTermSet anzsrc-for:
100 schema:name Communications Technologies
101 rdf:type schema:DefinedTerm
102 sg:person.011173106320.18 schema:affiliation grid-institutes:grid.424988.b
103 schema:familyName Fidanova
104 schema:givenName Stefka
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18
106 rdf:type schema:Person
107 sg:person.015745057111.08 schema:affiliation grid-institutes:grid.493309.4
108 schema:familyName Roeva
109 schema:givenName Olympia
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015745057111.08
111 rdf:type schema:Person
112 grid-institutes:grid.424988.b schema:alternateName Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 25A, 1113, Sofia, Bulgaria
113 schema:name Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 25A, 1113, Sofia, Bulgaria
114 rdf:type schema:Organization
115 grid-institutes:grid.493309.4 schema:alternateName Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 105, 1113, Sofia, Bulgaria
116 schema:name Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 105, 1113, Sofia, Bulgaria
117 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...