Highly Scalable Multiprocessing Algorithms for Preference-Based Database Retrieval View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Joachim Selke , Christoph Lofi , Wolf-Tilo Balke

ABSTRACT

Until recently algorithms continuously gained free performance improvements due to ever increasing processor speeds. Unfortunately, this development has reached its limit. Nowadays, new generations of CPUs focus on increasing the number of processing cores instead of simply increasing the performance of a single core. Thus, sequential algorithms will be excluded from future technological advances. Instead, highly scalable parallel algorithms are needed to fully tap new hardware potentials. In this paper we establish a design space for parallel algorithms in the domain of personalized database retrieval, taking skyline algorithms as a representative example. We will investigate the spectrum of base operations of different retrieval algorithms and various parallelization techniques to develop a set of highly scalable and high-performing skyline algorithms for different retrieval scenarios. Finally, we extensively evaluate these algorithms to showcase their superior characteristics. More... »

PAGES

246-260

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-12098-5_19

DOI

http://dx.doi.org/10.1007/978-3-642-12098-5_19

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026088860


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institut f\u00fcr Informationssysteme, Technische Universit\u00e4t Braunschweig, M\u00fchlenpfordtstra\u00dfe 23, Braunschweig, Germany", 
          "id": "http://www.grid.ac/institutes/grid.6738.a", 
          "name": [
            "Institut f\u00fcr Informationssysteme, Technische Universit\u00e4t Braunschweig, M\u00fchlenpfordtstra\u00dfe 23, Braunschweig, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Selke", 
        "givenName": "Joachim", 
        "id": "sg:person.012152554345.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012152554345.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut f\u00fcr Informationssysteme, Technische Universit\u00e4t Braunschweig, M\u00fchlenpfordtstra\u00dfe 23, Braunschweig, Germany", 
          "id": "http://www.grid.ac/institutes/grid.6738.a", 
          "name": [
            "Institut f\u00fcr Informationssysteme, Technische Universit\u00e4t Braunschweig, M\u00fchlenpfordtstra\u00dfe 23, Braunschweig, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lofi", 
        "givenName": "Christoph", 
        "id": "sg:person.011355173745.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011355173745.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut f\u00fcr Informationssysteme, Technische Universit\u00e4t Braunschweig, M\u00fchlenpfordtstra\u00dfe 23, Braunschweig, Germany", 
          "id": "http://www.grid.ac/institutes/grid.6738.a", 
          "name": [
            "Institut f\u00fcr Informationssysteme, Technische Universit\u00e4t Braunschweig, M\u00fchlenpfordtstra\u00dfe 23, Braunschweig, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Balke", 
        "givenName": "Wolf-Tilo", 
        "id": "sg:person.014313642615.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014313642615.12"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2010", 
    "datePublishedReg": "2010-01-01", 
    "description": "Until recently algorithms continuously gained free performance improvements due to ever increasing processor speeds. Unfortunately, this development has reached its limit. Nowadays, new generations of CPUs focus on increasing the number of processing cores instead of simply increasing the performance of a single core. Thus, sequential algorithms will be excluded from future technological advances. Instead, highly scalable parallel algorithms are needed to fully tap new hardware potentials. In this paper we establish a design space for parallel algorithms in the domain of personalized database retrieval, taking skyline algorithms as a representative example. We will investigate the spectrum of base operations of different retrieval algorithms and various parallelization techniques to develop a set of highly scalable and high-performing skyline algorithms for different retrieval scenarios. Finally, we extensively evaluate these algorithms to showcase their superior characteristics.", 
    "editor": [
      {
        "familyName": "Kitagawa", 
        "givenName": "Hiroyuki", 
        "type": "Person"
      }, 
      {
        "familyName": "Ishikawa", 
        "givenName": "Yoshiharu", 
        "type": "Person"
      }, 
      {
        "familyName": "Li", 
        "givenName": "Qing", 
        "type": "Person"
      }, 
      {
        "familyName": "Watanabe", 
        "givenName": "Chiemi", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-12098-5_19", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-3-642-12097-8", 
        "978-3-642-12098-5"
      ], 
      "name": "Database Systems for Advanced Applications", 
      "type": "Book"
    }, 
    "keywords": [
      "skyline algorithms", 
      "database retrieval", 
      "parallel algorithm", 
      "different retrieval scenarios", 
      "scalable parallel algorithm", 
      "retrieval scenarios", 
      "hardware potential", 
      "parallelization techniques", 
      "processing cores", 
      "processor speed", 
      "sequential algorithm", 
      "different retrieval algorithms", 
      "algorithm", 
      "base operations", 
      "single core", 
      "design space", 
      "performance improvement", 
      "retrieval algorithm", 
      "retrieval", 
      "CPU", 
      "new generation", 
      "technological advances", 
      "future technological advances", 
      "representative examples", 
      "scenarios", 
      "set", 
      "performance", 
      "operation", 
      "domain", 
      "speed", 
      "space", 
      "technique", 
      "example", 
      "core", 
      "advances", 
      "generation", 
      "improvement", 
      "superior characteristics", 
      "number", 
      "preferences", 
      "development", 
      "characteristics", 
      "potential", 
      "limit", 
      "spectra", 
      "paper"
    ], 
    "name": "Highly Scalable Multiprocessing Algorithms for Preference-Based Database Retrieval", 
    "pagination": "246-260", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1026088860"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-12098-5_19"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-12098-5_19", 
      "https://app.dimensions.ai/details/publication/pub.1026088860"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-06-01T22:33", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/chapter/chapter_362.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-642-12098-5_19"
  }
]
 

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.10.1007/978-3-642-12098-5_19'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-12098-5_19'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-12098-5_19'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-12098-5_19'


 

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

135 TRIPLES      23 PREDICATES      72 URIs      65 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-12098-5_19 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N5d6fcf29885b4f888b499de786c6e129
4 schema:datePublished 2010
5 schema:datePublishedReg 2010-01-01
6 schema:description Until recently algorithms continuously gained free performance improvements due to ever increasing processor speeds. Unfortunately, this development has reached its limit. Nowadays, new generations of CPUs focus on increasing the number of processing cores instead of simply increasing the performance of a single core. Thus, sequential algorithms will be excluded from future technological advances. Instead, highly scalable parallel algorithms are needed to fully tap new hardware potentials. In this paper we establish a design space for parallel algorithms in the domain of personalized database retrieval, taking skyline algorithms as a representative example. We will investigate the spectrum of base operations of different retrieval algorithms and various parallelization techniques to develop a set of highly scalable and high-performing skyline algorithms for different retrieval scenarios. Finally, we extensively evaluate these algorithms to showcase their superior characteristics.
7 schema:editor Nf1a3ec1bc2044e67bf00e2138826e8fb
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree true
11 schema:isPartOf Nd6816784d2a04e7993eac6ffed0f77dc
12 schema:keywords CPU
13 advances
14 algorithm
15 base operations
16 characteristics
17 core
18 database retrieval
19 design space
20 development
21 different retrieval algorithms
22 different retrieval scenarios
23 domain
24 example
25 future technological advances
26 generation
27 hardware potential
28 improvement
29 limit
30 new generation
31 number
32 operation
33 paper
34 parallel algorithm
35 parallelization techniques
36 performance
37 performance improvement
38 potential
39 preferences
40 processing cores
41 processor speed
42 representative examples
43 retrieval
44 retrieval algorithm
45 retrieval scenarios
46 scalable parallel algorithm
47 scenarios
48 sequential algorithm
49 set
50 single core
51 skyline algorithms
52 space
53 spectra
54 speed
55 superior characteristics
56 technique
57 technological advances
58 schema:name Highly Scalable Multiprocessing Algorithms for Preference-Based Database Retrieval
59 schema:pagination 246-260
60 schema:productId N4e4818783da745429c9f7c7293998dc9
61 Nc16395224e034134863e400a16582304
62 schema:publisher N4e708178041e4ccea22cba987ef0bf53
63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026088860
64 https://doi.org/10.1007/978-3-642-12098-5_19
65 schema:sdDatePublished 2022-06-01T22:33
66 schema:sdLicense https://scigraph.springernature.com/explorer/license/
67 schema:sdPublisher N0d5726ba0f1e47da83d8cf9ac5960023
68 schema:url https://doi.org/10.1007/978-3-642-12098-5_19
69 sgo:license sg:explorer/license/
70 sgo:sdDataset chapters
71 rdf:type schema:Chapter
72 N0ceb4282d71d4804a4d269de9cb01083 rdf:first Nb65d6214c483487ea458b56586a9c18b
73 rdf:rest rdf:nil
74 N0d5726ba0f1e47da83d8cf9ac5960023 schema:name Springer Nature - SN SciGraph project
75 rdf:type schema:Organization
76 N35542a0df408420bb7572e027879f0e1 schema:familyName Ishikawa
77 schema:givenName Yoshiharu
78 rdf:type schema:Person
79 N4e4818783da745429c9f7c7293998dc9 schema:name doi
80 schema:value 10.1007/978-3-642-12098-5_19
81 rdf:type schema:PropertyValue
82 N4e708178041e4ccea22cba987ef0bf53 schema:name Springer Nature
83 rdf:type schema:Organisation
84 N5d6fcf29885b4f888b499de786c6e129 rdf:first sg:person.012152554345.21
85 rdf:rest N685298e953cc49c78950ab5bc5d697cd
86 N685298e953cc49c78950ab5bc5d697cd rdf:first sg:person.011355173745.44
87 rdf:rest Nd6917179c9914af7bbf22776c786a709
88 N71ee74eb21114496b05c8a50476e07b5 rdf:first N35542a0df408420bb7572e027879f0e1
89 rdf:rest N98061d717cb54dc89eb65885c484da05
90 N7e5d3b11eaf44512914435fc94ce6f5b schema:familyName Li
91 schema:givenName Qing
92 rdf:type schema:Person
93 N98061d717cb54dc89eb65885c484da05 rdf:first N7e5d3b11eaf44512914435fc94ce6f5b
94 rdf:rest N0ceb4282d71d4804a4d269de9cb01083
95 Nb65d6214c483487ea458b56586a9c18b schema:familyName Watanabe
96 schema:givenName Chiemi
97 rdf:type schema:Person
98 Nc16395224e034134863e400a16582304 schema:name dimensions_id
99 schema:value pub.1026088860
100 rdf:type schema:PropertyValue
101 Nd6816784d2a04e7993eac6ffed0f77dc schema:isbn 978-3-642-12097-8
102 978-3-642-12098-5
103 schema:name Database Systems for Advanced Applications
104 rdf:type schema:Book
105 Nd6917179c9914af7bbf22776c786a709 rdf:first sg:person.014313642615.12
106 rdf:rest rdf:nil
107 Nf1a3ec1bc2044e67bf00e2138826e8fb rdf:first Nf3b2c611562e415f9317f3e450f1755a
108 rdf:rest N71ee74eb21114496b05c8a50476e07b5
109 Nf3b2c611562e415f9317f3e450f1755a schema:familyName Kitagawa
110 schema:givenName Hiroyuki
111 rdf:type schema:Person
112 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
113 schema:name Information and Computing Sciences
114 rdf:type schema:DefinedTerm
115 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
116 schema:name Artificial Intelligence and Image Processing
117 rdf:type schema:DefinedTerm
118 sg:person.011355173745.44 schema:affiliation grid-institutes:grid.6738.a
119 schema:familyName Lofi
120 schema:givenName Christoph
121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011355173745.44
122 rdf:type schema:Person
123 sg:person.012152554345.21 schema:affiliation grid-institutes:grid.6738.a
124 schema:familyName Selke
125 schema:givenName Joachim
126 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012152554345.21
127 rdf:type schema:Person
128 sg:person.014313642615.12 schema:affiliation grid-institutes:grid.6738.a
129 schema:familyName Balke
130 schema:givenName Wolf-Tilo
131 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014313642615.12
132 rdf:type schema:Person
133 grid-institutes:grid.6738.a schema:alternateName Institut für Informationssysteme, Technische Universität Braunschweig, Mühlenpfordtstraße 23, Braunschweig, Germany
134 schema:name Institut für Informationssysteme, Technische Universität Braunschweig, Mühlenpfordtstraße 23, Braunschweig, Germany
135 rdf:type schema:Organization
 




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


...