Effect of Neighborhood on In-Network Processing in Sensor Networks View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2008

AUTHORS

Muhammad Jafar Sadeq , Matt Duckham

ABSTRACT

Wireless sensor networks are growing from a few hand-placed devices to more large-scale networks in terms of coverage and node density. For various concerns, such as scalability, larger network sizes require some management of the large volume of data that a sensor network delivers. One way to manage this data is processing information in the network. This paper investigates how a sensor network’s network architecture (specifically, the neighborhood structure) can influence the conclusions that a sensor network makes from its measurements. The results demonstrate that non-planar structures are infeasible for routing and some in-network processing applications. Structures with low average edge lengths give better quantitative results, while those with high edge densities give better qualitative results. More... »

PAGES

133-150

References to SciGraph publications

Book

TITLE

Geographic Information Science

ISBN

978-3-540-87472-0
978-3-540-87473-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-87473-7_9

DOI

http://dx.doi.org/10.1007/978-3-540-87473-7_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1032872715


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/2008/1005", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Communications Technologies", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Melbourne", 
          "id": "https://www.grid.ac/institutes/grid.1008.9", 
          "name": [
            "Department of Geomatics, The University of Melbourne, 3010, Victoria, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sadeq", 
        "givenName": "Muhammad Jafar", 
        "id": "sg:person.016666655321.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016666655321.65"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Melbourne", 
          "id": "https://www.grid.ac/institutes/grid.1008.9", 
          "name": [
            "Department of Geomatics, The University of Melbourne, 3010, Victoria, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Duckham", 
        "givenName": "Matt", 
        "id": "sg:person.01060220132.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01060220132.66"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1145/1097064.1097073", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005862561"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1080810.1080818", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017972423"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/570738.570751", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018579220"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1021021236", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1098-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021021236", 
          "https://doi.org/10.1007/978-1-4612-1098-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1098-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021021236", 
          "https://doi.org/10.1007/978-1-4612-1098-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/345910.345953", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025201758"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.earscirev.2006.05.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029286457"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1570-8705(03)00007-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035741076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1570-8705(03)00007-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035741076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11502593_27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050943474", 
          "https://doi.org/10.1007/11502593_27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11502593_27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050943474", 
          "https://doi.org/10.1007/11502593_27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/ees.2006.0045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059253767"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpds.2003.1239871", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061752719"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/mdm.2006.110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093601323"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2008", 
    "datePublishedReg": "2008-01-01", 
    "description": "Wireless sensor networks are growing from a few hand-placed devices to more large-scale networks in terms of coverage and node density. For various concerns, such as scalability, larger network sizes require some management of the large volume of data that a sensor network delivers. One way to manage this data is processing information in the network. This paper investigates how a sensor network\u2019s network architecture (specifically, the neighborhood structure) can influence the conclusions that a sensor network makes from its measurements. The results demonstrate that non-planar structures are infeasible for routing and some in-network processing applications. Structures with low average edge lengths give better quantitative results, while those with high edge densities give better qualitative results.", 
    "editor": [
      {
        "familyName": "Cova", 
        "givenName": "Thomas J.", 
        "type": "Person"
      }, 
      {
        "familyName": "Miller", 
        "givenName": "Harvey J.", 
        "type": "Person"
      }, 
      {
        "familyName": "Beard", 
        "givenName": "Kate", 
        "type": "Person"
      }, 
      {
        "familyName": "Frank", 
        "givenName": "Andrew U.", 
        "type": "Person"
      }, 
      {
        "familyName": "Goodchild", 
        "givenName": "Michael F.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-540-87473-7_9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-3-540-87472-0", 
        "978-3-540-87473-7"
      ], 
      "name": "Geographic Information Science", 
      "type": "Book"
    }, 
    "name": "Effect of Neighborhood on In-Network Processing in Sensor Networks", 
    "pagination": "133-150", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-540-87473-7_9"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "9c9a1c64ebaea4cbfaf01263fa90f0fbdd82487296f830cc2b597b75c7e7a680"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1032872715"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-540-87473-7_9", 
      "https://app.dimensions.ai/details/publication/pub.1032872715"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T06:09", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000350_0000000350/records_77554_00000000.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-540-87473-7_9"
  }
]
 

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.10.1007/978-3-540-87473-7_9'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-87473-7_9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-87473-7_9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-87473-7_9'


 

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

129 TRIPLES      23 PREDICATES      39 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-540-87473-7_9 schema:about anzsrc-for:10
2 anzsrc-for:1005
3 schema:author Nfd26f7c94f17453d932bf6c66ecb9de8
4 schema:citation sg:pub.10.1007/11502593_27
5 sg:pub.10.1007/978-1-4612-1098-6
6 https://app.dimensions.ai/details/publication/pub.1021021236
7 https://doi.org/10.1016/j.earscirev.2006.05.001
8 https://doi.org/10.1016/s1570-8705(03)00007-6
9 https://doi.org/10.1089/ees.2006.0045
10 https://doi.org/10.1109/mdm.2006.110
11 https://doi.org/10.1109/tpds.2003.1239871
12 https://doi.org/10.1145/1080810.1080818
13 https://doi.org/10.1145/1097064.1097073
14 https://doi.org/10.1145/345910.345953
15 https://doi.org/10.1145/570738.570751
16 schema:datePublished 2008
17 schema:datePublishedReg 2008-01-01
18 schema:description Wireless sensor networks are growing from a few hand-placed devices to more large-scale networks in terms of coverage and node density. For various concerns, such as scalability, larger network sizes require some management of the large volume of data that a sensor network delivers. One way to manage this data is processing information in the network. This paper investigates how a sensor network’s network architecture (specifically, the neighborhood structure) can influence the conclusions that a sensor network makes from its measurements. The results demonstrate that non-planar structures are infeasible for routing and some in-network processing applications. Structures with low average edge lengths give better quantitative results, while those with high edge densities give better qualitative results.
19 schema:editor N4b8e30100b0948a788798f2a1ab1876b
20 schema:genre chapter
21 schema:inLanguage en
22 schema:isAccessibleForFree true
23 schema:isPartOf Nceba64c7eb46471cb45f32a99db9cd1d
24 schema:name Effect of Neighborhood on In-Network Processing in Sensor Networks
25 schema:pagination 133-150
26 schema:productId N81ca836849b24802ae410ad596a45171
27 Ned785f492c434ba78272a94b444794a7
28 Nefef25490bd0450d86551dbba47de5eb
29 schema:publisher Nad197fbd2b5a465b9208ab6f63cefa93
30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032872715
31 https://doi.org/10.1007/978-3-540-87473-7_9
32 schema:sdDatePublished 2019-04-16T06:09
33 schema:sdLicense https://scigraph.springernature.com/explorer/license/
34 schema:sdPublisher N5a722cf571994ca98c214a65d7c66b72
35 schema:url https://link.springer.com/10.1007%2F978-3-540-87473-7_9
36 sgo:license sg:explorer/license/
37 sgo:sdDataset chapters
38 rdf:type schema:Chapter
39 N305dabb7e3634a61892ff1f84272d324 schema:familyName Beard
40 schema:givenName Kate
41 rdf:type schema:Person
42 N4b8e30100b0948a788798f2a1ab1876b rdf:first Nb27a6c1da6584ce9ae5dfde23af8a395
43 rdf:rest N9057b07fb59e49318474a51a99413649
44 N5a722cf571994ca98c214a65d7c66b72 schema:name Springer Nature - SN SciGraph project
45 rdf:type schema:Organization
46 N81ca836849b24802ae410ad596a45171 schema:name dimensions_id
47 schema:value pub.1032872715
48 rdf:type schema:PropertyValue
49 N9057b07fb59e49318474a51a99413649 rdf:first Nb4edaf18598946f99dd035e120b4c5f9
50 rdf:rest N94348558382d4f6cbcf85c99f58c55f5
51 N94348558382d4f6cbcf85c99f58c55f5 rdf:first N305dabb7e3634a61892ff1f84272d324
52 rdf:rest Nbd9ffcc4936241d788514b707259dd18
53 Na1a90299824948388522e2342a876eaa rdf:first Na9ea0527fa334022a2ec77d1e9baa98f
54 rdf:rest rdf:nil
55 Na9ea0527fa334022a2ec77d1e9baa98f schema:familyName Goodchild
56 schema:givenName Michael F.
57 rdf:type schema:Person
58 Nad197fbd2b5a465b9208ab6f63cefa93 schema:location Berlin, Heidelberg
59 schema:name Springer Berlin Heidelberg
60 rdf:type schema:Organisation
61 Nb27a6c1da6584ce9ae5dfde23af8a395 schema:familyName Cova
62 schema:givenName Thomas J.
63 rdf:type schema:Person
64 Nb4edaf18598946f99dd035e120b4c5f9 schema:familyName Miller
65 schema:givenName Harvey J.
66 rdf:type schema:Person
67 Nbd9ffcc4936241d788514b707259dd18 rdf:first Ndb498fd1e0994cfbb5975de05868c3bf
68 rdf:rest Na1a90299824948388522e2342a876eaa
69 Nceba64c7eb46471cb45f32a99db9cd1d schema:isbn 978-3-540-87472-0
70 978-3-540-87473-7
71 schema:name Geographic Information Science
72 rdf:type schema:Book
73 Ndb498fd1e0994cfbb5975de05868c3bf schema:familyName Frank
74 schema:givenName Andrew U.
75 rdf:type schema:Person
76 Ned785f492c434ba78272a94b444794a7 schema:name doi
77 schema:value 10.1007/978-3-540-87473-7_9
78 rdf:type schema:PropertyValue
79 Nefef25490bd0450d86551dbba47de5eb schema:name readcube_id
80 schema:value 9c9a1c64ebaea4cbfaf01263fa90f0fbdd82487296f830cc2b597b75c7e7a680
81 rdf:type schema:PropertyValue
82 Nf339732d71614313a771a4a9a731a0ac rdf:first sg:person.01060220132.66
83 rdf:rest rdf:nil
84 Nfd26f7c94f17453d932bf6c66ecb9de8 rdf:first sg:person.016666655321.65
85 rdf:rest Nf339732d71614313a771a4a9a731a0ac
86 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
87 schema:name Technology
88 rdf:type schema:DefinedTerm
89 anzsrc-for:1005 schema:inDefinedTermSet anzsrc-for:
90 schema:name Communications Technologies
91 rdf:type schema:DefinedTerm
92 sg:person.01060220132.66 schema:affiliation https://www.grid.ac/institutes/grid.1008.9
93 schema:familyName Duckham
94 schema:givenName Matt
95 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01060220132.66
96 rdf:type schema:Person
97 sg:person.016666655321.65 schema:affiliation https://www.grid.ac/institutes/grid.1008.9
98 schema:familyName Sadeq
99 schema:givenName Muhammad Jafar
100 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016666655321.65
101 rdf:type schema:Person
102 sg:pub.10.1007/11502593_27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050943474
103 https://doi.org/10.1007/11502593_27
104 rdf:type schema:CreativeWork
105 sg:pub.10.1007/978-1-4612-1098-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021021236
106 https://doi.org/10.1007/978-1-4612-1098-6
107 rdf:type schema:CreativeWork
108 https://app.dimensions.ai/details/publication/pub.1021021236 schema:CreativeWork
109 https://doi.org/10.1016/j.earscirev.2006.05.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029286457
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/s1570-8705(03)00007-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035741076
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1089/ees.2006.0045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059253767
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1109/mdm.2006.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093601323
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1109/tpds.2003.1239871 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061752719
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1145/1080810.1080818 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017972423
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1145/1097064.1097073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005862561
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1145/345910.345953 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025201758
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1145/570738.570751 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018579220
126 rdf:type schema:CreativeWork
127 https://www.grid.ac/institutes/grid.1008.9 schema:alternateName University of Melbourne
128 schema:name Department of Geomatics, The University of Melbourne, 3010, Victoria, Australia
129 rdf:type schema:Organization
 




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


...