A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree
As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modifi...
Gespeichert in:
Veröffentlicht in: | International journal of information systems and supply chain management 2021-07, Vol.14 (3), p.1-17 |
---|---|
Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 17 |
---|---|
container_issue | 3 |
container_start_page | 1 |
container_title | International journal of information systems and supply chain management |
container_volume | 14 |
creator | Aliyu, Muhammad Murali M Gital, Abdulsalam Y Boukari, Souley Kabir, Rumana Musa, Maryam Abdullahi Zambuk, Fatima Umar Shawulu, Joshua Caleb Umar, Ibrahim M |
description | As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance. |
doi_str_mv | 10.4018/IJISSCM.2021070101 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_gale_businessinsightsgauss_A760500894</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A760500894</galeid><sourcerecordid>A760500894</sourcerecordid><originalsourceid>FETCH-LOGICAL-c361t-1ca2f77694773348e5065247c1d6426ce66d37e2873ea9e6453b70a2af52db093</originalsourceid><addsrcrecordid>eNp1kd1u0zAcxSMEEmPwAlxZ4pYOfyR2zV0UDShamUQ7bi03-SfxlNrBdiZ178g74SgVQ0jc-Es_n3Psk2VvCb7KMVl_2Hzd7HbV9opiSrDABJNn2QWRrFgVguXP_6wpf5m9CuEe40JKhi-yXyXaTkM0q70Bj0pf9yZCHScPqHUexR7QVlvdwRFsRK5Fu2kchxOqem3svK8GNzXoOwQ3-RoCSqca_TA-Tnowj9CcgWv7YLyzs8pHVKJv7gEGlBKjPdS9NT-nxe9ftbtgbIfKZF25wdkTuh2jOZpHHY1LRrZBu1FbO0N7D_A6e9HqIcCb83yZ3X263ldfVje3nzdVebOqGSdxRWpNWyG4zIVgLF9DgXlBc1GThueU18B5wwTQtWCgJfC8YAeBNdVtQZsDluwye7fojt6l6CGq-xTYJktFJSOSC0lm6v1CdXoAdZjSWyCkIZiuj6HTUwiqFBwXGK9lnnC64LV3IXho1ejNUfuTIljNLatzy-qp5XRps1wynXkKkQpVc6Hq70JV-uD_K5Gc_QZ5VbT3</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2931967919</pqid></control><display><type>article</type><title>A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree</title><source>ProQuest Central</source><creator>Aliyu, Muhammad ; Murali M ; Gital, Abdulsalam Y ; Boukari, Souley ; Kabir, Rumana ; Musa, Maryam Abdullahi ; Zambuk, Fatima Umar ; Shawulu, Joshua Caleb ; Umar, Ibrahim M</creator><creatorcontrib>Aliyu, Muhammad ; Murali M ; Gital, Abdulsalam Y ; Boukari, Souley ; Kabir, Rumana ; Musa, Maryam Abdullahi ; Zambuk, Fatima Umar ; Shawulu, Joshua Caleb ; Umar, Ibrahim M</creatorcontrib><description>As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.</description><identifier>ISSN: 1935-5726</identifier><identifier>EISSN: 1935-5734</identifier><identifier>DOI: 10.4018/IJISSCM.2021070101</identifier><language>eng</language><publisher>Hershey: IGI Global</publisher><subject>Algorithms ; Ant colony optimization ; Cloud computing ; Graph theory ; Heuristic methods ; Logistics ; Methods ; Resource utilization ; Supply chains</subject><ispartof>International journal of information systems and supply chain management, 2021-07, Vol.14 (3), p.1-17</ispartof><rights>COPYRIGHT 2021 IGI Global</rights><rights>Copyright © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-6155-3133 ; 0000-0003-1705-5641</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2931967919?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,43781</link.rule.ids></links><search><creatorcontrib>Aliyu, Muhammad</creatorcontrib><creatorcontrib>Murali M</creatorcontrib><creatorcontrib>Gital, Abdulsalam Y</creatorcontrib><creatorcontrib>Boukari, Souley</creatorcontrib><creatorcontrib>Kabir, Rumana</creatorcontrib><creatorcontrib>Musa, Maryam Abdullahi</creatorcontrib><creatorcontrib>Zambuk, Fatima Umar</creatorcontrib><creatorcontrib>Shawulu, Joshua Caleb</creatorcontrib><creatorcontrib>Umar, Ibrahim M</creatorcontrib><title>A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree</title><title>International journal of information systems and supply chain management</title><description>As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.</description><subject>Algorithms</subject><subject>Ant colony optimization</subject><subject>Cloud computing</subject><subject>Graph theory</subject><subject>Heuristic methods</subject><subject>Logistics</subject><subject>Methods</subject><subject>Resource utilization</subject><subject>Supply chains</subject><issn>1935-5726</issn><issn>1935-5734</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kd1u0zAcxSMEEmPwAlxZ4pYOfyR2zV0UDShamUQ7bi03-SfxlNrBdiZ178g74SgVQ0jc-Es_n3Psk2VvCb7KMVl_2Hzd7HbV9opiSrDABJNn2QWRrFgVguXP_6wpf5m9CuEe40JKhi-yXyXaTkM0q70Bj0pf9yZCHScPqHUexR7QVlvdwRFsRK5Fu2kchxOqem3svK8GNzXoOwQ3-RoCSqca_TA-Tnowj9CcgWv7YLyzs8pHVKJv7gEGlBKjPdS9NT-nxe9ftbtgbIfKZF25wdkTuh2jOZpHHY1LRrZBu1FbO0N7D_A6e9HqIcCb83yZ3X263ldfVje3nzdVebOqGSdxRWpNWyG4zIVgLF9DgXlBc1GThueU18B5wwTQtWCgJfC8YAeBNdVtQZsDluwye7fojt6l6CGq-xTYJktFJSOSC0lm6v1CdXoAdZjSWyCkIZiuj6HTUwiqFBwXGK9lnnC64LV3IXho1ejNUfuTIljNLatzy-qp5XRps1wynXkKkQpVc6Hq70JV-uD_K5Gc_QZ5VbT3</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Aliyu, Muhammad</creator><creator>Murali M</creator><creator>Gital, Abdulsalam Y</creator><creator>Boukari, Souley</creator><creator>Kabir, Rumana</creator><creator>Musa, Maryam Abdullahi</creator><creator>Zambuk, Fatima Umar</creator><creator>Shawulu, Joshua Caleb</creator><creator>Umar, Ibrahim M</creator><general>IGI Global</general><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M7S</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-6155-3133</orcidid><orcidid>https://orcid.org/0000-0003-1705-5641</orcidid></search><sort><creationdate>20210701</creationdate><title>A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree</title><author>Aliyu, Muhammad ; Murali M ; Gital, Abdulsalam Y ; Boukari, Souley ; Kabir, Rumana ; Musa, Maryam Abdullahi ; Zambuk, Fatima Umar ; Shawulu, Joshua Caleb ; Umar, Ibrahim M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-1ca2f77694773348e5065247c1d6426ce66d37e2873ea9e6453b70a2af52db093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Ant colony optimization</topic><topic>Cloud computing</topic><topic>Graph theory</topic><topic>Heuristic methods</topic><topic>Logistics</topic><topic>Methods</topic><topic>Resource utilization</topic><topic>Supply chains</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aliyu, Muhammad</creatorcontrib><creatorcontrib>Murali M</creatorcontrib><creatorcontrib>Gital, Abdulsalam Y</creatorcontrib><creatorcontrib>Boukari, Souley</creatorcontrib><creatorcontrib>Kabir, Rumana</creatorcontrib><creatorcontrib>Musa, Maryam Abdullahi</creatorcontrib><creatorcontrib>Zambuk, Fatima Umar</creatorcontrib><creatorcontrib>Shawulu, Joshua Caleb</creatorcontrib><creatorcontrib>Umar, Ibrahim M</creatorcontrib><collection>CrossRef</collection><collection>Gale Business: Insights</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Engineering Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>International journal of information systems and supply chain management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aliyu, Muhammad</au><au>Murali M</au><au>Gital, Abdulsalam Y</au><au>Boukari, Souley</au><au>Kabir, Rumana</au><au>Musa, Maryam Abdullahi</au><au>Zambuk, Fatima Umar</au><au>Shawulu, Joshua Caleb</au><au>Umar, Ibrahim M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree</atitle><jtitle>International journal of information systems and supply chain management</jtitle><date>2021-07-01</date><risdate>2021</risdate><volume>14</volume><issue>3</issue><spage>1</spage><epage>17</epage><pages>1-17</pages><issn>1935-5726</issn><eissn>1935-5734</eissn><abstract>As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.</abstract><cop>Hershey</cop><pub>IGI Global</pub><doi>10.4018/IJISSCM.2021070101</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0001-6155-3133</orcidid><orcidid>https://orcid.org/0000-0003-1705-5641</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1935-5726 |
ispartof | International journal of information systems and supply chain management, 2021-07, Vol.14 (3), p.1-17 |
issn | 1935-5726 1935-5734 |
language | eng |
recordid | cdi_gale_businessinsightsgauss_A760500894 |
source | ProQuest Central |
subjects | Algorithms Ant colony optimization Cloud computing Graph theory Heuristic methods Logistics Methods Resource utilization Supply chains |
title | A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-04T05%3A56%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Multi-Tier%20Architecture%20for%20the%20Management%20of%20Supply%20Chain%20of%20Cloud%20Resources%20in%20a%20Virtualized%20Cloud%20Environment:%20A%20Novel%20SCM%20Technique%20for%20Cloud%20Resources%20Using%20Ant%20Colony%20Optimization%20and%20Spanning%20Tree&rft.jtitle=International%20journal%20of%20information%20systems%20and%20supply%20chain%20management&rft.au=Aliyu,%20Muhammad&rft.date=2021-07-01&rft.volume=14&rft.issue=3&rft.spage=1&rft.epage=17&rft.pages=1-17&rft.issn=1935-5726&rft.eissn=1935-5734&rft_id=info:doi/10.4018/IJISSCM.2021070101&rft_dat=%3Cgale_proqu%3EA760500894%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2931967919&rft_id=info:pmid/&rft_galeid=A760500894&rfr_iscdi=true |