Loading…
An Improved Quality-of-Service Performance Using RED's Active Queue Management Flow Control in Classifying Networks
Traffic classification networks have various applications for data transmissions to ensure quality of service (QoS) for various classes of traffic at the routers. Multi-level random early detection (MRED) scheduling algorithm is used to manage resources at the routers guaranteeing QoS. However, the...
Saved in:
Published in: | IEEE access 2017-01, Vol.5, p.24467-24478 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43 |
---|---|
cites | cdi_FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43 |
container_end_page | 24478 |
container_issue | |
container_start_page | 24467 |
container_title | IEEE access |
container_volume | 5 |
creator | Alkharasani, Ameen M. Othman, Mohamed Abdullah, Azizol Kweh Yeah Lun |
description | Traffic classification networks have various applications for data transmissions to ensure quality of service (QoS) for various classes of traffic at the routers. Multi-level random early detection (MRED) scheduling algorithm is used to manage resources at the routers guaranteeing QoS. However, the MRED queue mechanism is insensitive to traffic and difficult to set parameters, for the average queue is sensitive to high congestion level of multi-flow which is a major issue affecting the performance of the queue in the networks. This paper propose a new scheduling algorithm that manages congestion level by increasing the stability of parameters, using dynamic weighted traffic with redefining probability drop traffic in the MRED algorithm. The results present the performance algorithm while utilizing the reference algorithms, improving the bandwidth fairness and average throughput and reduce the average delay and packet drop. |
doi_str_mv | 10.1109/ACCESS.2017.2767071 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_a053dfd37ed7427fb802d58ea86d25d6</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8086127</ieee_id><doaj_id>oai_doaj_org_article_a053dfd37ed7427fb802d58ea86d25d6</doaj_id><sourcerecordid>2455946322</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43</originalsourceid><addsrcrecordid>eNpNkU1v2zAMho1hA1Z0_QW9CNhhJ2f6lnwMvLQL0HYfWc-CbFGBMsfqJCdF_v2UuSjGCwmCz0uCb1VdE7wgBDefl2272mwWFBO1oEoqrMib6oIS2dRMMPn2v_p9dZXzDpfQpSXURZWXI1rvn1I8gkM_DnYI06mOvt5AOoYe0HdIPqa9HUv9mMO4RT9XXz5ltOyncIRCwAHQvR3tFvYwTuhmiM-ojeOU4oDCiNrB5hz86Uw-wPQc0-_8oXrn7ZDh6iVfVo83q1_t1_ru2-26Xd7VPVd8qoliwuveMik55g2muOsYdJI4zqzm1gE0lGvlhPIMSMcVww3vFbbgseg5u6zWs66LdmeeUtjbdDLRBvOvEdPW2DSFfgBjsWDOO6bAKU6V7zSmTmiwWjoqnCxaH2et8qo_B8iT2cVDGsv5hnIhGi4ZpWWKzVN9ijkn8K9bCTZns8xsljmbZV7MKtT1TAUAeCU01pJQxf4CHdiP6Q</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2455946322</pqid></control><display><type>article</type><title>An Improved Quality-of-Service Performance Using RED's Active Queue Management Flow Control in Classifying Networks</title><source>IEEE Open Access Journals</source><creator>Alkharasani, Ameen M. ; Othman, Mohamed ; Abdullah, Azizol ; Kweh Yeah Lun</creator><creatorcontrib>Alkharasani, Ameen M. ; Othman, Mohamed ; Abdullah, Azizol ; Kweh Yeah Lun</creatorcontrib><description>Traffic classification networks have various applications for data transmissions to ensure quality of service (QoS) for various classes of traffic at the routers. Multi-level random early detection (MRED) scheduling algorithm is used to manage resources at the routers guaranteeing QoS. However, the MRED queue mechanism is insensitive to traffic and difficult to set parameters, for the average queue is sensitive to high congestion level of multi-flow which is a major issue affecting the performance of the queue in the networks. This paper propose a new scheduling algorithm that manages congestion level by increasing the stability of parameters, using dynamic weighted traffic with redefining probability drop traffic in the MRED algorithm. The results present the performance algorithm while utilizing the reference algorithms, improving the bandwidth fairness and average throughput and reduce the average delay and packet drop.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2017.2767071</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Active control ; active queue management ; Algorithm design and analysis ; Algorithms ; Bandwidth ; classes of traffic ; Classification ; Data transmission ; Delays ; Dynamic stability ; Flow control ; Heuristic algorithms ; marker algorithm ; Networks ; Parameter sensitivity ; Quality of service ; Quality of service architectures ; Queuing theory ; Routers ; Scheduling ; scheduling algorithm ; Scheduling algorithms ; Throughput ; Traffic congestion ; Traffic control</subject><ispartof>IEEE access, 2017-01, Vol.5, p.24467-24478</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43</citedby><cites>FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43</cites><orcidid>0000-0001-8522-5388</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8086127$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,27631,27922,27923,54931</link.rule.ids></links><search><creatorcontrib>Alkharasani, Ameen M.</creatorcontrib><creatorcontrib>Othman, Mohamed</creatorcontrib><creatorcontrib>Abdullah, Azizol</creatorcontrib><creatorcontrib>Kweh Yeah Lun</creatorcontrib><title>An Improved Quality-of-Service Performance Using RED's Active Queue Management Flow Control in Classifying Networks</title><title>IEEE access</title><addtitle>Access</addtitle><description>Traffic classification networks have various applications for data transmissions to ensure quality of service (QoS) for various classes of traffic at the routers. Multi-level random early detection (MRED) scheduling algorithm is used to manage resources at the routers guaranteeing QoS. However, the MRED queue mechanism is insensitive to traffic and difficult to set parameters, for the average queue is sensitive to high congestion level of multi-flow which is a major issue affecting the performance of the queue in the networks. This paper propose a new scheduling algorithm that manages congestion level by increasing the stability of parameters, using dynamic weighted traffic with redefining probability drop traffic in the MRED algorithm. The results present the performance algorithm while utilizing the reference algorithms, improving the bandwidth fairness and average throughput and reduce the average delay and packet drop.</description><subject>Active control</subject><subject>active queue management</subject><subject>Algorithm design and analysis</subject><subject>Algorithms</subject><subject>Bandwidth</subject><subject>classes of traffic</subject><subject>Classification</subject><subject>Data transmission</subject><subject>Delays</subject><subject>Dynamic stability</subject><subject>Flow control</subject><subject>Heuristic algorithms</subject><subject>marker algorithm</subject><subject>Networks</subject><subject>Parameter sensitivity</subject><subject>Quality of service</subject><subject>Quality of service architectures</subject><subject>Queuing theory</subject><subject>Routers</subject><subject>Scheduling</subject><subject>scheduling algorithm</subject><subject>Scheduling algorithms</subject><subject>Throughput</subject><subject>Traffic congestion</subject><subject>Traffic control</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNkU1v2zAMho1hA1Z0_QW9CNhhJ2f6lnwMvLQL0HYfWc-CbFGBMsfqJCdF_v2UuSjGCwmCz0uCb1VdE7wgBDefl2272mwWFBO1oEoqrMib6oIS2dRMMPn2v_p9dZXzDpfQpSXURZWXI1rvn1I8gkM_DnYI06mOvt5AOoYe0HdIPqa9HUv9mMO4RT9XXz5ltOyncIRCwAHQvR3tFvYwTuhmiM-ojeOU4oDCiNrB5hz86Uw-wPQc0-_8oXrn7ZDh6iVfVo83q1_t1_ru2-26Xd7VPVd8qoliwuveMik55g2muOsYdJI4zqzm1gE0lGvlhPIMSMcVww3vFbbgseg5u6zWs66LdmeeUtjbdDLRBvOvEdPW2DSFfgBjsWDOO6bAKU6V7zSmTmiwWjoqnCxaH2et8qo_B8iT2cVDGsv5hnIhGi4ZpWWKzVN9ijkn8K9bCTZns8xsljmbZV7MKtT1TAUAeCU01pJQxf4CHdiP6Q</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>Alkharasani, Ameen M.</creator><creator>Othman, Mohamed</creator><creator>Abdullah, Azizol</creator><creator>Kweh Yeah Lun</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8522-5388</orcidid></search><sort><creationdate>20170101</creationdate><title>An Improved Quality-of-Service Performance Using RED's Active Queue Management Flow Control in Classifying Networks</title><author>Alkharasani, Ameen M. ; Othman, Mohamed ; Abdullah, Azizol ; Kweh Yeah Lun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Active control</topic><topic>active queue management</topic><topic>Algorithm design and analysis</topic><topic>Algorithms</topic><topic>Bandwidth</topic><topic>classes of traffic</topic><topic>Classification</topic><topic>Data transmission</topic><topic>Delays</topic><topic>Dynamic stability</topic><topic>Flow control</topic><topic>Heuristic algorithms</topic><topic>marker algorithm</topic><topic>Networks</topic><topic>Parameter sensitivity</topic><topic>Quality of service</topic><topic>Quality of service architectures</topic><topic>Queuing theory</topic><topic>Routers</topic><topic>Scheduling</topic><topic>scheduling algorithm</topic><topic>Scheduling algorithms</topic><topic>Throughput</topic><topic>Traffic congestion</topic><topic>Traffic control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alkharasani, Ameen M.</creatorcontrib><creatorcontrib>Othman, Mohamed</creatorcontrib><creatorcontrib>Abdullah, Azizol</creatorcontrib><creatorcontrib>Kweh Yeah Lun</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science 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>Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alkharasani, Ameen M.</au><au>Othman, Mohamed</au><au>Abdullah, Azizol</au><au>Kweh Yeah Lun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Improved Quality-of-Service Performance Using RED's Active Queue Management Flow Control in Classifying Networks</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2017-01-01</date><risdate>2017</risdate><volume>5</volume><spage>24467</spage><epage>24478</epage><pages>24467-24478</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Traffic classification networks have various applications for data transmissions to ensure quality of service (QoS) for various classes of traffic at the routers. Multi-level random early detection (MRED) scheduling algorithm is used to manage resources at the routers guaranteeing QoS. However, the MRED queue mechanism is insensitive to traffic and difficult to set parameters, for the average queue is sensitive to high congestion level of multi-flow which is a major issue affecting the performance of the queue in the networks. This paper propose a new scheduling algorithm that manages congestion level by increasing the stability of parameters, using dynamic weighted traffic with redefining probability drop traffic in the MRED algorithm. The results present the performance algorithm while utilizing the reference algorithms, improving the bandwidth fairness and average throughput and reduce the average delay and packet drop.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2017.2767071</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-8522-5388</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2169-3536 |
ispartof | IEEE access, 2017-01, Vol.5, p.24467-24478 |
issn | 2169-3536 2169-3536 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_a053dfd37ed7427fb802d58ea86d25d6 |
source | IEEE Open Access Journals |
subjects | Active control active queue management Algorithm design and analysis Algorithms Bandwidth classes of traffic Classification Data transmission Delays Dynamic stability Flow control Heuristic algorithms marker algorithm Networks Parameter sensitivity Quality of service Quality of service architectures Queuing theory Routers Scheduling scheduling algorithm Scheduling algorithms Throughput Traffic congestion Traffic control |
title | An Improved Quality-of-Service Performance Using RED's Active Queue Management Flow Control in Classifying Networks |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T20%3A49%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Improved%20Quality-of-Service%20Performance%20Using%20RED's%20Active%20Queue%20Management%20Flow%20Control%20in%20Classifying%20Networks&rft.jtitle=IEEE%20access&rft.au=Alkharasani,%20Ameen%20M.&rft.date=2017-01-01&rft.volume=5&rft.spage=24467&rft.epage=24478&rft.pages=24467-24478&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2017.2767071&rft_dat=%3Cproquest_doaj_%3E2455946322%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c474t-1735f8ca3664049020bb3eb61d43a84adee92487d57f3e1b473094c70aef05c43%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2455946322&rft_id=info:pmid/&rft_ieee_id=8086127&rfr_iscdi=true |