Energy-Efficient Process Replication by Forcing Meaningless Replicas to Terminate in Virtual Machine Environment View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Tomoya Enokido , Dilawaer Duolikun , Makoto Takizawa

ABSTRACT

Server cluster systems equipped with virtual machines are widely used to provide various types of reliable application services. Especially, multiple replicas of each application process can be redundantly performed on multiple virtual machines to realize reliable application services. On the other hand, a large amount of electric energy is consumed in a server cluster since multiple replicas of each application process are performed on multiple virtual machines. In this paper, the improved redundant energy consumption laxity based (IRECLB) algorithm is newly proposed to reduce the total electric energy consumption of a server cluster for redundantly performing each application process by forcing meaningless replicas to terminate. We evaluate the IRECLB algorithm in terms of the total electric energy consumption of a server cluster and the average response time of each process compared with the redundant energy consumption laxity based (RECLB) algorithm previously proposed. More... »

PAGES

149-160

References to SciGraph publications

  • 2017. An Energy-Efficient Process Replication Algorithm in Virtual Machine Environments in ADVANCES ON BROAD-BAND WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS
  • Book

    TITLE

    Complex, Intelligent, and Software Intensive Systems

    ISBN

    978-3-319-93658-1
    978-3-319-93659-8

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-93659-8_13

    DOI

    http://dx.doi.org/10.1007/978-3-319-93659-8_13

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1104892966


    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/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "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"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Rissho University", 
              "id": "https://www.grid.ac/institutes/grid.442924.d", 
              "name": [
                "Rissho University"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Enokido", 
            "givenName": "Tomoya", 
            "id": "sg:person.011323525173.27", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011323525173.27"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hosei University", 
              "id": "https://www.grid.ac/institutes/grid.257114.4", 
              "name": [
                "Hosei University"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Duolikun", 
            "givenName": "Dilawaer", 
            "id": "sg:person.015403137025.41", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015403137025.41"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hosei University", 
              "id": "https://www.grid.ac/institutes/grid.257114.4", 
              "name": [
                "Hosei University"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Takizawa", 
            "givenName": "Makoto", 
            "id": "sg:person.010241424037.00", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010241424037.00"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1145/357172.357176", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001982359"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-49106-6_10", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020553329", 
              "https://doi.org/10.1007/978-3-319-49106-6_10"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/jsyst.2010.2047296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061338840"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tie.2010.2060453", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061624601"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tie.2012.2206357", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061625701"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tii.2011.2173203", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061632013"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tii.2014.2303315", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061632445"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cisis.2015.18", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094447487"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019", 
        "datePublishedReg": "2019-01-01", 
        "description": "Server cluster systems equipped with virtual machines are widely used to provide various types of reliable application services. Especially, multiple replicas of each application process can be redundantly performed on multiple virtual machines to realize reliable application services. On the other hand, a large amount of electric energy is consumed in a server cluster since multiple replicas of each application process are performed on multiple virtual machines. In this paper, the improved redundant energy consumption laxity based (IRECLB) algorithm is newly proposed to reduce the total electric energy consumption of a server cluster for redundantly performing each application process by forcing meaningless replicas to terminate. We evaluate the IRECLB algorithm in terms of the total electric energy consumption of a server cluster and the average response time of each process compared with the redundant energy consumption laxity based (RECLB) algorithm previously proposed.", 
        "editor": [
          {
            "familyName": "Barolli", 
            "givenName": "Leonard", 
            "type": "Person"
          }, 
          {
            "familyName": "Javaid", 
            "givenName": "Nadeem", 
            "type": "Person"
          }, 
          {
            "familyName": "Ikeda", 
            "givenName": "Makoto", 
            "type": "Person"
          }, 
          {
            "familyName": "Takizawa", 
            "givenName": "Makoto", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-319-93659-8_13", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-3-319-93658-1", 
            "978-3-319-93659-8"
          ], 
          "name": "Complex, Intelligent, and Software Intensive Systems", 
          "type": "Book"
        }, 
        "name": "Energy-Efficient Process Replication by Forcing Meaningless Replicas to Terminate in Virtual Machine Environment", 
        "pagination": "149-160", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-319-93659-8_13"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "2e64afc7b220cd48354d47cf39752fd1cfc8f454bc0418d5061ad8059c29d7c9"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1104892966"
            ]
          }
        ], 
        "publisher": {
          "location": "Cham", 
          "name": "Springer International Publishing", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-319-93659-8_13", 
          "https://app.dimensions.ai/details/publication/pub.1104892966"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T14:43", 
        "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_8669_00000427.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-3-319-93659-8_13"
      }
    ]
     

    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.10.1007/978-3-319-93659-8_13'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-93659-8_13'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-93659-8_13'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-93659-8_13'


     

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

    122 TRIPLES      23 PREDICATES      35 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-319-93659-8_13 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author N0a7708c07585455381d4f376c93624fb
    4 schema:citation sg:pub.10.1007/978-3-319-49106-6_10
    5 https://doi.org/10.1109/cisis.2015.18
    6 https://doi.org/10.1109/jsyst.2010.2047296
    7 https://doi.org/10.1109/tie.2010.2060453
    8 https://doi.org/10.1109/tie.2012.2206357
    9 https://doi.org/10.1109/tii.2011.2173203
    10 https://doi.org/10.1109/tii.2014.2303315
    11 https://doi.org/10.1145/357172.357176
    12 schema:datePublished 2019
    13 schema:datePublishedReg 2019-01-01
    14 schema:description Server cluster systems equipped with virtual machines are widely used to provide various types of reliable application services. Especially, multiple replicas of each application process can be redundantly performed on multiple virtual machines to realize reliable application services. On the other hand, a large amount of electric energy is consumed in a server cluster since multiple replicas of each application process are performed on multiple virtual machines. In this paper, the improved redundant energy consumption laxity based (IRECLB) algorithm is newly proposed to reduce the total electric energy consumption of a server cluster for redundantly performing each application process by forcing meaningless replicas to terminate. We evaluate the IRECLB algorithm in terms of the total electric energy consumption of a server cluster and the average response time of each process compared with the redundant energy consumption laxity based (RECLB) algorithm previously proposed.
    15 schema:editor Na2460ff6588e408daee77270e2483502
    16 schema:genre chapter
    17 schema:inLanguage en
    18 schema:isAccessibleForFree false
    19 schema:isPartOf N7b0d245d5c9a4f4e9681f48746ba9e19
    20 schema:name Energy-Efficient Process Replication by Forcing Meaningless Replicas to Terminate in Virtual Machine Environment
    21 schema:pagination 149-160
    22 schema:productId N45e8c2802d524b5885ab12bc27bbe380
    23 N4e0952a0538f43dcb6b710a71bf5abd8
    24 N6c4a3ea92eb24bc48aec984b5a9a60c4
    25 schema:publisher Nee899beb1d7948348d77d326071375bc
    26 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104892966
    27 https://doi.org/10.1007/978-3-319-93659-8_13
    28 schema:sdDatePublished 2019-04-15T14:43
    29 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    30 schema:sdPublisher N014729a4775c424295919ddbcd68299c
    31 schema:url http://link.springer.com/10.1007/978-3-319-93659-8_13
    32 sgo:license sg:explorer/license/
    33 sgo:sdDataset chapters
    34 rdf:type schema:Chapter
    35 N014729a4775c424295919ddbcd68299c schema:name Springer Nature - SN SciGraph project
    36 rdf:type schema:Organization
    37 N0a7708c07585455381d4f376c93624fb rdf:first sg:person.011323525173.27
    38 rdf:rest N7f3254268ca948d58d7ed1e433c1869f
    39 N0f7ca2cb0f0945ba8fd8b3f4ab0f7817 rdf:first sg:person.010241424037.00
    40 rdf:rest rdf:nil
    41 N15587afe1a7a45b388c3584224e152fa schema:familyName Barolli
    42 schema:givenName Leonard
    43 rdf:type schema:Person
    44 N3d865e41d6454c02a3280fa18c7a1d2b schema:familyName Javaid
    45 schema:givenName Nadeem
    46 rdf:type schema:Person
    47 N45e8c2802d524b5885ab12bc27bbe380 schema:name doi
    48 schema:value 10.1007/978-3-319-93659-8_13
    49 rdf:type schema:PropertyValue
    50 N49a169d4f7ba4d0cbbd5742ff966cd44 schema:familyName Ikeda
    51 schema:givenName Makoto
    52 rdf:type schema:Person
    53 N4e0952a0538f43dcb6b710a71bf5abd8 schema:name dimensions_id
    54 schema:value pub.1104892966
    55 rdf:type schema:PropertyValue
    56 N6c4a3ea92eb24bc48aec984b5a9a60c4 schema:name readcube_id
    57 schema:value 2e64afc7b220cd48354d47cf39752fd1cfc8f454bc0418d5061ad8059c29d7c9
    58 rdf:type schema:PropertyValue
    59 N7b0d245d5c9a4f4e9681f48746ba9e19 schema:isbn 978-3-319-93658-1
    60 978-3-319-93659-8
    61 schema:name Complex, Intelligent, and Software Intensive Systems
    62 rdf:type schema:Book
    63 N7f3254268ca948d58d7ed1e433c1869f rdf:first sg:person.015403137025.41
    64 rdf:rest N0f7ca2cb0f0945ba8fd8b3f4ab0f7817
    65 N8c44271cc8ad48a1ba0edd7ec4f67f78 rdf:first N49a169d4f7ba4d0cbbd5742ff966cd44
    66 rdf:rest Ne1b640a56d2444bf86d5d29fa6d8882f
    67 N9898154758144896b874c8abf0445842 schema:familyName Takizawa
    68 schema:givenName Makoto
    69 rdf:type schema:Person
    70 Na2460ff6588e408daee77270e2483502 rdf:first N15587afe1a7a45b388c3584224e152fa
    71 rdf:rest Nf4f2cee299de45018bf32d0e9ea88578
    72 Ne1b640a56d2444bf86d5d29fa6d8882f rdf:first N9898154758144896b874c8abf0445842
    73 rdf:rest rdf:nil
    74 Nee899beb1d7948348d77d326071375bc schema:location Cham
    75 schema:name Springer International Publishing
    76 rdf:type schema:Organisation
    77 Nf4f2cee299de45018bf32d0e9ea88578 rdf:first N3d865e41d6454c02a3280fa18c7a1d2b
    78 rdf:rest N8c44271cc8ad48a1ba0edd7ec4f67f78
    79 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    80 schema:name Information and Computing Sciences
    81 rdf:type schema:DefinedTerm
    82 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    83 schema:name Artificial Intelligence and Image Processing
    84 rdf:type schema:DefinedTerm
    85 sg:person.010241424037.00 schema:affiliation https://www.grid.ac/institutes/grid.257114.4
    86 schema:familyName Takizawa
    87 schema:givenName Makoto
    88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010241424037.00
    89 rdf:type schema:Person
    90 sg:person.011323525173.27 schema:affiliation https://www.grid.ac/institutes/grid.442924.d
    91 schema:familyName Enokido
    92 schema:givenName Tomoya
    93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011323525173.27
    94 rdf:type schema:Person
    95 sg:person.015403137025.41 schema:affiliation https://www.grid.ac/institutes/grid.257114.4
    96 schema:familyName Duolikun
    97 schema:givenName Dilawaer
    98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015403137025.41
    99 rdf:type schema:Person
    100 sg:pub.10.1007/978-3-319-49106-6_10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020553329
    101 https://doi.org/10.1007/978-3-319-49106-6_10
    102 rdf:type schema:CreativeWork
    103 https://doi.org/10.1109/cisis.2015.18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094447487
    104 rdf:type schema:CreativeWork
    105 https://doi.org/10.1109/jsyst.2010.2047296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061338840
    106 rdf:type schema:CreativeWork
    107 https://doi.org/10.1109/tie.2010.2060453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061624601
    108 rdf:type schema:CreativeWork
    109 https://doi.org/10.1109/tie.2012.2206357 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061625701
    110 rdf:type schema:CreativeWork
    111 https://doi.org/10.1109/tii.2011.2173203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061632013
    112 rdf:type schema:CreativeWork
    113 https://doi.org/10.1109/tii.2014.2303315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061632445
    114 rdf:type schema:CreativeWork
    115 https://doi.org/10.1145/357172.357176 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001982359
    116 rdf:type schema:CreativeWork
    117 https://www.grid.ac/institutes/grid.257114.4 schema:alternateName Hosei University
    118 schema:name Hosei University
    119 rdf:type schema:Organization
    120 https://www.grid.ac/institutes/grid.442924.d schema:alternateName Rissho University
    121 schema:name Rissho University
    122 rdf:type schema:Organization
     




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


    ...