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 N77a6b2fdcf17456b9ee552b2bb4d5ed9
    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 N81407e0f17594f8ba59b25b8eabfd8ba
    16 schema:genre chapter
    17 schema:inLanguage en
    18 schema:isAccessibleForFree false
    19 schema:isPartOf N81d28650b5134e538d233c99b482181d
    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 Naae82ba186de46aab351b98dc5520543
    23 Nc8538be4e2884563b531b9e3c299cc2a
    24 Nd9cbb839ec164255a9198d8ba4a5794a
    25 schema:publisher N35e2da16e3ea484db4a1969493776c8a
    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 Ned091c1a48cf4ba18998a5d1261777d5
    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 N21994239015b4a95a46b1c30a8506d7d rdf:first sg:person.015403137025.41
    36 rdf:rest Nc9aa922e54d84848b56baaa9ba47c7cb
    37 N35e2da16e3ea484db4a1969493776c8a schema:location Cham
    38 schema:name Springer International Publishing
    39 rdf:type schema:Organisation
    40 N40ee8b5f67d24e38ae4a0b0dec470d21 schema:familyName Javaid
    41 schema:givenName Nadeem
    42 rdf:type schema:Person
    43 N697511983b3c4e5dba143553176821a8 rdf:first N40ee8b5f67d24e38ae4a0b0dec470d21
    44 rdf:rest N739a285830c14ca984e3ed1c0e6c4905
    45 N71dc4ad6990d4894b4795c998878e4f7 schema:familyName Ikeda
    46 schema:givenName Makoto
    47 rdf:type schema:Person
    48 N739a285830c14ca984e3ed1c0e6c4905 rdf:first N71dc4ad6990d4894b4795c998878e4f7
    49 rdf:rest N8aa789ee8e824a9aa72e00d9e24aadf5
    50 N77a6b2fdcf17456b9ee552b2bb4d5ed9 rdf:first sg:person.011323525173.27
    51 rdf:rest N21994239015b4a95a46b1c30a8506d7d
    52 N81407e0f17594f8ba59b25b8eabfd8ba rdf:first Ndda6598d4f7740f0a134357c61e8319b
    53 rdf:rest N697511983b3c4e5dba143553176821a8
    54 N81d28650b5134e538d233c99b482181d schema:isbn 978-3-319-93658-1
    55 978-3-319-93659-8
    56 schema:name Complex, Intelligent, and Software Intensive Systems
    57 rdf:type schema:Book
    58 N8aa789ee8e824a9aa72e00d9e24aadf5 rdf:first Ne811146f34de4eeca1cd5146e40abf06
    59 rdf:rest rdf:nil
    60 Naae82ba186de46aab351b98dc5520543 schema:name dimensions_id
    61 schema:value pub.1104892966
    62 rdf:type schema:PropertyValue
    63 Nc8538be4e2884563b531b9e3c299cc2a schema:name readcube_id
    64 schema:value 2e64afc7b220cd48354d47cf39752fd1cfc8f454bc0418d5061ad8059c29d7c9
    65 rdf:type schema:PropertyValue
    66 Nc9aa922e54d84848b56baaa9ba47c7cb rdf:first sg:person.010241424037.00
    67 rdf:rest rdf:nil
    68 Nd9cbb839ec164255a9198d8ba4a5794a schema:name doi
    69 schema:value 10.1007/978-3-319-93659-8_13
    70 rdf:type schema:PropertyValue
    71 Ndda6598d4f7740f0a134357c61e8319b schema:familyName Barolli
    72 schema:givenName Leonard
    73 rdf:type schema:Person
    74 Ne811146f34de4eeca1cd5146e40abf06 schema:familyName Takizawa
    75 schema:givenName Makoto
    76 rdf:type schema:Person
    77 Ned091c1a48cf4ba18998a5d1261777d5 schema:name Springer Nature - SN SciGraph project
    78 rdf:type schema:Organization
    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)


    ...