{"id":"https://openalex.org/W3040810095","doi":"https://doi.org/10.1186/s40537-020-00321-w","title":"Hybrid gradient descent spider monkey optimization (HGDSMO) algorithm for efficient resource scheduling for big data processing in heterogenous environment","display_name":"Hybrid gradient descent spider monkey optimization (HGDSMO) algorithm for efficient resource scheduling for big data processing in heterogenous environment","publication_year":2020,"publication_date":"2020-07-10","ids":{"openalex":"https://openalex.org/W3040810095","doi":"https://doi.org/10.1186/s40537-020-00321-w","mag":"3040810095"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-020-00321-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-020-00321-w","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00321-w","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00321-w","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077280437","display_name":"V. Seethalakshmi","orcid":null},"institutions":[{"id":"https://openalex.org/I175691731","display_name":"Pondicherry University","ror":"https://ror.org/01a3mef16","country_code":"IN","type":"education","lineage":["https://openalex.org/I175691731"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"V. Seethalakshmi","raw_affiliation_strings":["Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India"],"raw_orcid":"https://orcid.org/0000-0002-2151-4911","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India","institution_ids":["https://openalex.org/I175691731"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031618004","display_name":"V. Govindasamy","orcid":"https://orcid.org/0000-0002-9371-8868"},"institutions":[{"id":"https://openalex.org/I175691731","display_name":"Pondicherry University","ror":"https://ror.org/01a3mef16","country_code":"IN","type":"education","lineage":["https://openalex.org/I175691731"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Govindasamy","raw_affiliation_strings":["Department of Information Technology, Pondicherry Engineering College, Puducherry, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Pondicherry Engineering College, Puducherry, India","institution_ids":["https://openalex.org/I175691731"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023735590","display_name":"V. Akila","orcid":null},"institutions":[{"id":"https://openalex.org/I175691731","display_name":"Pondicherry University","ror":"https://ror.org/01a3mef16","country_code":"IN","type":"education","lineage":["https://openalex.org/I175691731"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Akila","raw_affiliation_strings":["Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India","institution_ids":["https://openalex.org/I175691731"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077280437"],"corresponding_institution_ids":["https://openalex.org/I175691731"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":5.5672,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.96178671,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"7","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8575928211212158},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.6850240230560303},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6295448541641235},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6203858256340027},{"id":"https://openalex.org/keywords/load-balancing","display_name":"Load balancing (electrical power)","score":0.5989155173301697},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5747994184494019},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4502529203891754},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.20232143998146057},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11313477158546448},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.09073770046234131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8575928211212158},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6850240230560303},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6295448541641235},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6203858256340027},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.5989155173301697},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5747994184494019},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4502529203891754},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.20232143998146057},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11313477158546448},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.09073770046234131},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-020-00321-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-020-00321-w","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00321-w","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1d5c1949933949a5aca4c1f87005e21d","is_oa":true,"landing_page_url":"https://doaj.org/article/1d5c1949933949a5aca4c1f87005e21d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 7, Iss 1, Pp 1-25 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-020-00321-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-020-00321-w","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00321-w","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5199999809265137,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3040810095.pdf","grobid_xml":"https://content.openalex.org/works/W3040810095.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1120107613","https://openalex.org/W1141949320","https://openalex.org/W1202959476","https://openalex.org/W1984688127","https://openalex.org/W2028629398","https://openalex.org/W2034698933","https://openalex.org/W2035978754","https://openalex.org/W2063281062","https://openalex.org/W2075372670","https://openalex.org/W2142801346","https://openalex.org/W2167640678","https://openalex.org/W2171439285","https://openalex.org/W2207496718","https://openalex.org/W2360786640","https://openalex.org/W2463235085","https://openalex.org/W2530763462","https://openalex.org/W2564566967","https://openalex.org/W2584793861","https://openalex.org/W2740169236","https://openalex.org/W2772669830","https://openalex.org/W2793686583","https://openalex.org/W2802578596","https://openalex.org/W2886611439","https://openalex.org/W2896791697","https://openalex.org/W2898359708","https://openalex.org/W2901091318","https://openalex.org/W2911552803","https://openalex.org/W2941552006","https://openalex.org/W2965205488","https://openalex.org/W2990298958","https://openalex.org/W3020998497","https://openalex.org/W4248437134"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W4244478748","https://openalex.org/W4233347783","https://openalex.org/W2910064364","https://openalex.org/W2166734474"],"abstract_inverted_index":{"Abstract":[0],"Big":[1,75],"Data":[2,21,76],"constructed":[3],"based":[4],"on":[5,192],"the":[6,16,47,59,74,80,104,108,134,139,148,156,163,173,180,183,208,221,237],"advancement":[7],"of":[8,30,49,61,69,82,93,107,155,165,182,214,220],"distributed":[9],"computing":[10,31,71],"and":[11,37,86,110,136,152,233],"virtualization":[12],"is":[13,24,44,95,126,170,196],"considered":[14,45,96],"as":[15,46,97,172,199],"current":[17],"emerging":[18],"trends":[19],"in":[20,138,162,229],"Analytics.":[22],"It":[23,169,195],"used":[25,244],"for":[26,205,211,245],"supporting":[27],"potential":[28],"utilization":[29],"resources":[32,72,94,109,210],"focusing":[33],"on,":[34],"on-demand":[35],"services":[36],"resource":[38,42,50,88,130,167,202,241],"scalability.":[39],"In":[40,114],"particular,":[41],"scheduling":[43,92,131,176],"process":[48,57],"distribution":[51],"through":[52],"an":[53,98],"effective":[54,166,212],"decision":[55],"making":[56],"with":[58],"objective":[60,164],"facilitating":[62],"required":[63],"tasks":[64],"over":[65],"time.":[66],"The":[67,143,217],"incorporation":[68],"heterogeneous":[70],"by":[73,132,185],"consumers":[77],"also":[78,197],"permits":[79],"option":[81],"reducing":[83],"energy":[84],"usage":[85],"enhanced":[87],"efficiency.":[89],"Further,":[90],"optimal":[91],"NP":[99],"hard":[100],"problem":[101],"due":[102],"to":[103,128,188,226,236],"dynamic":[105,201],"characteristics":[106],"fluctuating":[111],"users\u2019":[112],"demand.":[113],"this":[115],"paper,":[116],"a":[117,200],"Hybrid":[118],"Gradient":[119,149],"Descent":[120],"Spider":[121],"Monkey":[122],"Optimization":[123],"(HGDSMO)":[124],"algorithm":[125,146,160,224],"proposed":[127,144,198,222],"efficient":[129,174],"handling":[133],"issues":[135],"challenges":[137],"Hadoop":[140],"heterogenous":[141],"environment.":[142],"HGDSMO":[145,223],"uses":[147],"Descentand":[150],"foraging":[151],"social":[153],"behavior":[154],"spider":[157],"monkey":[158],"optimization":[159],"involved":[161],"allocation.":[168],"designed":[171],"task":[175],"approach":[177],"that":[178],"balances":[179],"load":[181,231],"cloud":[184,209],"allocating":[186,207],"them":[187],"appropriate":[189],"VMs":[190],"depending":[191],"their":[193],"requirements.":[194],"management":[203],"scheme":[204],"efficiently":[206],"execution":[213],"clients\u2019":[215],"tasks.":[216],"simulation":[218],"results":[219],"confirmed":[225],"be":[227],"potent":[228],"throughput,":[230],"balancing":[232],"makespan":[234],"compared":[235],"baseline":[238],"hybrid":[239],"meta-heuristic":[240],"allocation":[242],"algorithms":[243],"investigation.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
