How much memory is needed for leader election View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-10

AUTHORS

Emanuele G. Fusco, Andrzej Pelc

ABSTRACT

We study the minimum memory size with which nodes of a network have to be equipped, in order to solve deterministically the leader election problem. Nodes are unlabeled, but ports at each node have arbitrary fixed labelings which, together with the topology of the network, can create asymmetries to be exploited in leader election. We consider two versions of the leader election problem: strong LE in which exactly one leader has to be elected, if this is possible, while all nodes must terminate in a state “infeasible” when the election of a unique leader fails, and weak LE, which differs from strong LE in that no requirement on the behavior of nodes is imposed, if leader election is impossible. Nodes are modeled as identical automata and we ask what is the minimum amount of memory of such an automaton to enable leader election. We show that logarithmic memory is optimal for both strong and weak leader election in the class of arbitrary connected graphs. By contrast we show that strong LE can be accomplished in the class of trees of maximum degree Δ using only O(log log Δ) bits of memory, thus proving an exponential gap in memory requirements for leader election between the class of trees and the class of arbitrary graphs. More... »

PAGES

65

References to SciGraph publications

  • 2008. Deterministic Rendezvous in Trees with Little Memory in DISTRIBUTED COMPUTING
  • 2004. Digraphs Exploration with Little Memory in STACS 2004
  • 2002-02-21. A Space Lower Bound for Routing in Trees in STACS 2002
  • 2005. Local Computations on Closed Unlabelled Edges: The Election Problem and the Naming Problem in SOFSEM 2005: THEORY AND PRACTICE OF COMPUTER SCIENCE
  • 2009. Leader Election in Ad Hoc Radio Networks: A Keen Ear Helps in AUTOMATA, LANGUAGES AND PROGRAMMING
  • 2008. Randomized Rendez-Vous with Limited Memory in LATIN 2008: THEORETICAL INFORMATICS
  • 2008. Labelled (Hyper)Graphs, Negotiations and the Naming Problem in GRAPH TRANSFORMATIONS
  • 2004. Election and Local Computations on Edges in FOUNDATIONS OF SOFTWARE SCIENCE AND COMPUTATION STRUCTURES
  • 2001-07-04. Routing in Trees in AUTOMATA, LANGUAGES AND PROGRAMMING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00446-011-0131-y

    DOI

    http://dx.doi.org/10.1007/s00446-011-0131-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1034295166


    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/2008/1701", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Psychology", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/17", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Psychology and Cognitive Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Sapienza University of Rome", 
              "id": "https://www.grid.ac/institutes/grid.7841.a", 
              "name": [
                "Computer Science Department, Sapienza, University of Rome, 00198, Rome, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fusco", 
            "givenName": "Emanuele G.", 
            "id": "sg:person.013526501407.57", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013526501407.57"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Universit\u00e9 du Qu\u00e9bec en Outaouais", 
              "id": "https://www.grid.ac/institutes/grid.265705.3", 
              "name": [
                "D\u00e9partement d\u2019informatique, Universit\u00e9 du Qu\u00e9bec en Outaouais, J8X 3X7, Gatineau, QC, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pelc", 
            "givenName": "Andrzej", 
            "id": "sg:person.013306156242.32", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013306156242.32"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/0304-3975(94)00178-l", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001993791"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30577-4_11", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002152364", 
              "https://doi.org/10.1007/978-3-540-30577-4_11"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30577-4_11", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002152364", 
              "https://doi.org/10.1007/978-3-540-30577-4_11"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/301308.301352", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003092108"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0196-6774(91)90002-g", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005265549"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jpdc.2003.11.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008759258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-87779-0_17", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009045352", 
              "https://doi.org/10.1007/978-3-540-87779-0_17"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-87779-0_17", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009045352", 
              "https://doi.org/10.1007/978-3-540-87779-0_17"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/359024.359029", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018801160"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24749-4_22", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019111927", 
              "https://doi.org/10.1007/978-3-540-24749-4_22"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24749-4_22", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019111927", 
              "https://doi.org/10.1007/978-3-540-24749-4_22"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-87405-8_5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020592729", 
              "https://doi.org/10.1007/978-3-540-87405-8_5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-87405-8_5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020592729", 
              "https://doi.org/10.1007/978-3-540-87405-8_5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/571825.571833", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021165716"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0022-0000(02)00023-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022889695"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0022-0000(02)00023-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022889695"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-78773-0_52", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027755793", 
              "https://doi.org/10.1007/978-3-540-78773-0_52"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-78773-0_52", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027755793", 
              "https://doi.org/10.1007/978-3-540-78773-0_52"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-48224-5_62", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028223272", 
              "https://doi.org/10.1007/3-540-48224-5_62"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-48224-5_62", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028223272", 
              "https://doi.org/10.1007/3-540-48224-5_62"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1835698.1835801", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028934550"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/69622.357194", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032495091"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/7531.7919", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033074534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-02930-1_43", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033689696", 
              "https://doi.org/10.1007/978-3-642-02930-1_43"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-02930-1_43", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033689696", 
              "https://doi.org/10.1007/978-3-642-02930-1_43"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24727-2_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036094667", 
              "https://doi.org/10.1007/978-3-540-24727-2_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24727-2_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036094667", 
              "https://doi.org/10.1007/978-3-540-24727-2_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1391289.1391291", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037199442"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/301308.301355", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037385852"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/48014.48247", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037496106"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/inco.1994.1086", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038251140"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1810479.1810524", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040005316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-45841-7_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041924256", 
              "https://doi.org/10.1007/3-540-45841-7_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-45841-7_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041924256", 
              "https://doi.org/10.1007/3-540-45841-7_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0166-218x(93)e0133-j", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043469437"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/71.481599", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061217493"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpds.2002.1003864", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061752580"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/0209048", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062841537"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/0215032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062841894"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2011-10", 
        "datePublishedReg": "2011-10-01", 
        "description": "We study the minimum memory size with which nodes of a network have to be equipped, in order to solve deterministically the leader election problem. Nodes are unlabeled, but ports at each node have arbitrary fixed labelings which, together with the topology of the network, can create asymmetries to be exploited in leader election. We consider two versions of the leader election problem: strong LE in which exactly one leader has to be elected, if this is possible, while all nodes must terminate in a state \u201cinfeasible\u201d when the election of a unique leader fails, and weak LE, which differs from strong LE in that no requirement on the behavior of nodes is imposed, if leader election is impossible. Nodes are modeled as identical automata and we ask what is the minimum amount of memory of such an automaton to enable leader election. We show that logarithmic memory is optimal for both strong and weak leader election in the class of arbitrary connected graphs. By contrast we show that strong LE can be accomplished in the class of trees of maximum degree \u0394 using only O(log log \u0394) bits of memory, thus proving an exponential gap in memory requirements for leader election between the class of trees and the class of arbitrary graphs.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s00446-011-0131-y", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1052621", 
            "issn": [
              "0178-2770", 
              "1432-0452"
            ], 
            "name": "Distributed Computing", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "2", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "24"
          }
        ], 
        "name": "How much memory is needed for leader election", 
        "pagination": "65", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "a35e4a81a197a010181dcd74f03b972a19be15552d33f99ba4f3fed5d6c37731"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00446-011-0131-y"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1034295166"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00446-011-0131-y", 
          "https://app.dimensions.ai/details/publication/pub.1034295166"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T14:03", 
        "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/v90/0000000001_0000000264/records_8660_00000489.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007/s00446-011-0131-y"
      }
    ]
     

    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/s00446-011-0131-y'

    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/s00446-011-0131-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00446-011-0131-y'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00446-011-0131-y'


     

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

    167 TRIPLES      21 PREDICATES      56 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00446-011-0131-y schema:about anzsrc-for:17
    2 anzsrc-for:1701
    3 schema:author N12a7ae795aff46009d5761e1ea2bc64a
    4 schema:citation sg:pub.10.1007/3-540-45841-7_4
    5 sg:pub.10.1007/3-540-48224-5_62
    6 sg:pub.10.1007/978-3-540-24727-2_8
    7 sg:pub.10.1007/978-3-540-24749-4_22
    8 sg:pub.10.1007/978-3-540-30577-4_11
    9 sg:pub.10.1007/978-3-540-78773-0_52
    10 sg:pub.10.1007/978-3-540-87405-8_5
    11 sg:pub.10.1007/978-3-540-87779-0_17
    12 sg:pub.10.1007/978-3-642-02930-1_43
    13 https://doi.org/10.1006/inco.1994.1086
    14 https://doi.org/10.1016/0166-218x(93)e0133-j
    15 https://doi.org/10.1016/0196-6774(91)90002-g
    16 https://doi.org/10.1016/0304-3975(94)00178-l
    17 https://doi.org/10.1016/j.jpdc.2003.11.007
    18 https://doi.org/10.1016/s0022-0000(02)00023-5
    19 https://doi.org/10.1109/71.481599
    20 https://doi.org/10.1109/tpds.2002.1003864
    21 https://doi.org/10.1137/0209048
    22 https://doi.org/10.1137/0215032
    23 https://doi.org/10.1145/1391289.1391291
    24 https://doi.org/10.1145/1810479.1810524
    25 https://doi.org/10.1145/1835698.1835801
    26 https://doi.org/10.1145/301308.301352
    27 https://doi.org/10.1145/301308.301355
    28 https://doi.org/10.1145/359024.359029
    29 https://doi.org/10.1145/48014.48247
    30 https://doi.org/10.1145/571825.571833
    31 https://doi.org/10.1145/69622.357194
    32 https://doi.org/10.1145/7531.7919
    33 schema:datePublished 2011-10
    34 schema:datePublishedReg 2011-10-01
    35 schema:description We study the minimum memory size with which nodes of a network have to be equipped, in order to solve deterministically the leader election problem. Nodes are unlabeled, but ports at each node have arbitrary fixed labelings which, together with the topology of the network, can create asymmetries to be exploited in leader election. We consider two versions of the leader election problem: strong LE in which exactly one leader has to be elected, if this is possible, while all nodes must terminate in a state “infeasible” when the election of a unique leader fails, and weak LE, which differs from strong LE in that no requirement on the behavior of nodes is imposed, if leader election is impossible. Nodes are modeled as identical automata and we ask what is the minimum amount of memory of such an automaton to enable leader election. We show that logarithmic memory is optimal for both strong and weak leader election in the class of arbitrary connected graphs. By contrast we show that strong LE can be accomplished in the class of trees of maximum degree Δ using only O(log log Δ) bits of memory, thus proving an exponential gap in memory requirements for leader election between the class of trees and the class of arbitrary graphs.
    36 schema:genre research_article
    37 schema:inLanguage en
    38 schema:isAccessibleForFree true
    39 schema:isPartOf N7804d90a37c6454e98b07774b39e067d
    40 Nddd6b23ceb9c465681dac9e394aab9a9
    41 sg:journal.1052621
    42 schema:name How much memory is needed for leader election
    43 schema:pagination 65
    44 schema:productId N661e6d72ae634e62848114873c01d773
    45 N934a4862fbd5401b894aa2347137271a
    46 Ne6102c90aab74421bf18463128f3ffb6
    47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034295166
    48 https://doi.org/10.1007/s00446-011-0131-y
    49 schema:sdDatePublished 2019-04-10T14:03
    50 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    51 schema:sdPublisher N37bd54a798d04b63bf04d71f87792830
    52 schema:url http://link.springer.com/10.1007/s00446-011-0131-y
    53 sgo:license sg:explorer/license/
    54 sgo:sdDataset articles
    55 rdf:type schema:ScholarlyArticle
    56 N12a7ae795aff46009d5761e1ea2bc64a rdf:first sg:person.013526501407.57
    57 rdf:rest N1f7212156e794dea878825889f4950ad
    58 N1f7212156e794dea878825889f4950ad rdf:first sg:person.013306156242.32
    59 rdf:rest rdf:nil
    60 N37bd54a798d04b63bf04d71f87792830 schema:name Springer Nature - SN SciGraph project
    61 rdf:type schema:Organization
    62 N661e6d72ae634e62848114873c01d773 schema:name dimensions_id
    63 schema:value pub.1034295166
    64 rdf:type schema:PropertyValue
    65 N7804d90a37c6454e98b07774b39e067d schema:issueNumber 2
    66 rdf:type schema:PublicationIssue
    67 N934a4862fbd5401b894aa2347137271a schema:name readcube_id
    68 schema:value a35e4a81a197a010181dcd74f03b972a19be15552d33f99ba4f3fed5d6c37731
    69 rdf:type schema:PropertyValue
    70 Nddd6b23ceb9c465681dac9e394aab9a9 schema:volumeNumber 24
    71 rdf:type schema:PublicationVolume
    72 Ne6102c90aab74421bf18463128f3ffb6 schema:name doi
    73 schema:value 10.1007/s00446-011-0131-y
    74 rdf:type schema:PropertyValue
    75 anzsrc-for:17 schema:inDefinedTermSet anzsrc-for:
    76 schema:name Psychology and Cognitive Sciences
    77 rdf:type schema:DefinedTerm
    78 anzsrc-for:1701 schema:inDefinedTermSet anzsrc-for:
    79 schema:name Psychology
    80 rdf:type schema:DefinedTerm
    81 sg:journal.1052621 schema:issn 0178-2770
    82 1432-0452
    83 schema:name Distributed Computing
    84 rdf:type schema:Periodical
    85 sg:person.013306156242.32 schema:affiliation https://www.grid.ac/institutes/grid.265705.3
    86 schema:familyName Pelc
    87 schema:givenName Andrzej
    88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013306156242.32
    89 rdf:type schema:Person
    90 sg:person.013526501407.57 schema:affiliation https://www.grid.ac/institutes/grid.7841.a
    91 schema:familyName Fusco
    92 schema:givenName Emanuele G.
    93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013526501407.57
    94 rdf:type schema:Person
    95 sg:pub.10.1007/3-540-45841-7_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041924256
    96 https://doi.org/10.1007/3-540-45841-7_4
    97 rdf:type schema:CreativeWork
    98 sg:pub.10.1007/3-540-48224-5_62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028223272
    99 https://doi.org/10.1007/3-540-48224-5_62
    100 rdf:type schema:CreativeWork
    101 sg:pub.10.1007/978-3-540-24727-2_8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036094667
    102 https://doi.org/10.1007/978-3-540-24727-2_8
    103 rdf:type schema:CreativeWork
    104 sg:pub.10.1007/978-3-540-24749-4_22 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019111927
    105 https://doi.org/10.1007/978-3-540-24749-4_22
    106 rdf:type schema:CreativeWork
    107 sg:pub.10.1007/978-3-540-30577-4_11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002152364
    108 https://doi.org/10.1007/978-3-540-30577-4_11
    109 rdf:type schema:CreativeWork
    110 sg:pub.10.1007/978-3-540-78773-0_52 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027755793
    111 https://doi.org/10.1007/978-3-540-78773-0_52
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1007/978-3-540-87405-8_5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020592729
    114 https://doi.org/10.1007/978-3-540-87405-8_5
    115 rdf:type schema:CreativeWork
    116 sg:pub.10.1007/978-3-540-87779-0_17 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009045352
    117 https://doi.org/10.1007/978-3-540-87779-0_17
    118 rdf:type schema:CreativeWork
    119 sg:pub.10.1007/978-3-642-02930-1_43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033689696
    120 https://doi.org/10.1007/978-3-642-02930-1_43
    121 rdf:type schema:CreativeWork
    122 https://doi.org/10.1006/inco.1994.1086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038251140
    123 rdf:type schema:CreativeWork
    124 https://doi.org/10.1016/0166-218x(93)e0133-j schema:sameAs https://app.dimensions.ai/details/publication/pub.1043469437
    125 rdf:type schema:CreativeWork
    126 https://doi.org/10.1016/0196-6774(91)90002-g schema:sameAs https://app.dimensions.ai/details/publication/pub.1005265549
    127 rdf:type schema:CreativeWork
    128 https://doi.org/10.1016/0304-3975(94)00178-l schema:sameAs https://app.dimensions.ai/details/publication/pub.1001993791
    129 rdf:type schema:CreativeWork
    130 https://doi.org/10.1016/j.jpdc.2003.11.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008759258
    131 rdf:type schema:CreativeWork
    132 https://doi.org/10.1016/s0022-0000(02)00023-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022889695
    133 rdf:type schema:CreativeWork
    134 https://doi.org/10.1109/71.481599 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061217493
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.1109/tpds.2002.1003864 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061752580
    137 rdf:type schema:CreativeWork
    138 https://doi.org/10.1137/0209048 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062841537
    139 rdf:type schema:CreativeWork
    140 https://doi.org/10.1137/0215032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062841894
    141 rdf:type schema:CreativeWork
    142 https://doi.org/10.1145/1391289.1391291 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037199442
    143 rdf:type schema:CreativeWork
    144 https://doi.org/10.1145/1810479.1810524 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040005316
    145 rdf:type schema:CreativeWork
    146 https://doi.org/10.1145/1835698.1835801 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028934550
    147 rdf:type schema:CreativeWork
    148 https://doi.org/10.1145/301308.301352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003092108
    149 rdf:type schema:CreativeWork
    150 https://doi.org/10.1145/301308.301355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037385852
    151 rdf:type schema:CreativeWork
    152 https://doi.org/10.1145/359024.359029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018801160
    153 rdf:type schema:CreativeWork
    154 https://doi.org/10.1145/48014.48247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037496106
    155 rdf:type schema:CreativeWork
    156 https://doi.org/10.1145/571825.571833 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021165716
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1145/69622.357194 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032495091
    159 rdf:type schema:CreativeWork
    160 https://doi.org/10.1145/7531.7919 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033074534
    161 rdf:type schema:CreativeWork
    162 https://www.grid.ac/institutes/grid.265705.3 schema:alternateName Université du Québec en Outaouais
    163 schema:name Département d’informatique, Université du Québec en Outaouais, J8X 3X7, Gatineau, QC, Canada
    164 rdf:type schema:Organization
    165 https://www.grid.ac/institutes/grid.7841.a schema:alternateName Sapienza University of Rome
    166 schema:name Computer Science Department, Sapienza, University of Rome, 00198, Rome, Italy
    167 rdf:type schema:Organization
     




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


    ...