Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand

This paper introduces a method to estimate latent traffic from its origin to destination from the link packet loss rate and traffic volume. In addition, we propose a method for the joint optimization of routing and link provisioning based on the estimated latent traffic. Observed traffic could devia...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEICE Transactions on Communications 2021/07/01, Vol.E104.B(7), pp.781-790
Hauptverfasser: UCHIDA, Takumi, ISHIBASHI, Keisuke, FUKUDA, Kensuke
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 790
container_issue 7
container_start_page 781
container_title IEICE Transactions on Communications
container_volume E104.B
creator UCHIDA, Takumi
ISHIBASHI, Keisuke
FUKUDA, Kensuke
description This paper introduces a method to estimate latent traffic from its origin to destination from the link packet loss rate and traffic volume. In addition, we propose a method for the joint optimization of routing and link provisioning based on the estimated latent traffic. Observed traffic could deviate from the original traffic demand and become latent when the traffic passes through congested links because of changes in user behavioral and/or applications as a result of degraded quality of experience (QoE). The latent traffic is actualized by improving congested link capacity. When link provisioning is based on observed traffic, actual traffic might cause new congestion at other links. Thus, network providers need to estimate the origin-destination (OD) original traffic demand for network planning. Although the estimation of original traffic has been well studied, the estimation was only applicable for links. In this paper, we propose a method to estimate latent OD traffic by combining and expanding techniques. The method consists of three steps. The first step is to estimate the actual OD traffic and loss rate from the actual traffic and packet loss rate of the links. The second step is to estimate the latent traffic demand. Finally, using this estimated demand, the link capacity and routing matrix are optimized. We evaluate our method by simulation and confirm that congestion could be avoided by capacity provisioning based on estimated latent traffic, while provisioning based on observed traffic retains the congestion. The combined method can avoid congestion with an increment of 23% compared with capacity provisioning only. We also evaluated our method's adaptability, i.e., the ability to estimate the required parameter for the estimations using fewer given values, but values obtained in the environment.
doi_str_mv 10.1587/transcom.2020CQP0008
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2547625803</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2547625803</sourcerecordid><originalsourceid>FETCH-LOGICAL-c477t-d1d5a069862b6a02fb5d83ff2b37f206acdf7c5881233bc3fdef0559012b6cd23</originalsourceid><addsrcrecordid>eNpNUE1PAjEQbYwmIvoPPGzieXHabrflKAt-JBiU4LnpdltcArtrWw74661BkMvMm8l7bzIPoVsMA8wEvw9ONV63mwEBAsX7GwCIM9TDPGMpphk7Rz0Y4jwVDOeX6Mr7FQAWBJMeep2321A3y0Q1VVKoTuk67JJZF-pN_a1C3TbJSHlTJRFMfNyqEIdprE1IZuNk4ZS1tU7GZhMdrtGFVWtvbv56H308ThbFczqdPb0UD9NUZ5yHtMIVU5APRU7KXAGxJasEtZaUlFsCudKV5ZoJgQmlpaa2MhYYGwKOfF0R2kd3e9_OtV9b44NctVvXxJOSsIznhAmgkZXtWdq13jtjZefiA24nMcjf4OQhOHkSXJTN97KVD2ppjiLlQq3X5l80wZDJkeQHcGJyJOtP5aRp6A-EXIAf</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2547625803</pqid></control><display><type>article</type><title>Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand</title><source>Alma/SFX Local Collection</source><creator>UCHIDA, Takumi ; ISHIBASHI, Keisuke ; FUKUDA, Kensuke</creator><creatorcontrib>UCHIDA, Takumi ; ISHIBASHI, Keisuke ; FUKUDA, Kensuke</creatorcontrib><description>This paper introduces a method to estimate latent traffic from its origin to destination from the link packet loss rate and traffic volume. In addition, we propose a method for the joint optimization of routing and link provisioning based on the estimated latent traffic. Observed traffic could deviate from the original traffic demand and become latent when the traffic passes through congested links because of changes in user behavioral and/or applications as a result of degraded quality of experience (QoE). The latent traffic is actualized by improving congested link capacity. When link provisioning is based on observed traffic, actual traffic might cause new congestion at other links. Thus, network providers need to estimate the origin-destination (OD) original traffic demand for network planning. Although the estimation of original traffic has been well studied, the estimation was only applicable for links. In this paper, we propose a method to estimate latent OD traffic by combining and expanding techniques. The method consists of three steps. The first step is to estimate the actual OD traffic and loss rate from the actual traffic and packet loss rate of the links. The second step is to estimate the latent traffic demand. Finally, using this estimated demand, the link capacity and routing matrix are optimized. We evaluate our method by simulation and confirm that congestion could be avoided by capacity provisioning based on estimated latent traffic, while provisioning based on observed traffic retains the congestion. The combined method can avoid congestion with an increment of 23% compared with capacity provisioning only. We also evaluated our method's adaptability, i.e., the ability to estimate the required parameter for the estimations using fewer given values, but values obtained in the environment.</description><identifier>ISSN: 0916-8516</identifier><identifier>EISSN: 1745-1345</identifier><identifier>DOI: 10.1587/transcom.2020CQP0008</identifier><language>eng</language><publisher>Tokyo: The Institute of Electronics, Information and Communication Engineers</publisher><subject>capacity provisioning ; Communications traffic ; Demand ; estimation ; Links ; Optimization ; Parameter estimation ; Provisioning ; Traffic capacity ; Traffic congestion ; traffic engineering ; Traffic flow ; Traffic planning ; Traffic volume</subject><ispartof>IEICE Transactions on Communications, 2021/07/01, Vol.E104.B(7), pp.781-790</ispartof><rights>2021 The Institute of Electronics, Information and Communication Engineers</rights><rights>Copyright Japan Science and Technology Agency 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c477t-d1d5a069862b6a02fb5d83ff2b37f206acdf7c5881233bc3fdef0559012b6cd23</citedby><cites>FETCH-LOGICAL-c477t-d1d5a069862b6a02fb5d83ff2b37f206acdf7c5881233bc3fdef0559012b6cd23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>UCHIDA, Takumi</creatorcontrib><creatorcontrib>ISHIBASHI, Keisuke</creatorcontrib><creatorcontrib>FUKUDA, Kensuke</creatorcontrib><title>Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand</title><title>IEICE Transactions on Communications</title><addtitle>IEICE Trans. Commun.</addtitle><description>This paper introduces a method to estimate latent traffic from its origin to destination from the link packet loss rate and traffic volume. In addition, we propose a method for the joint optimization of routing and link provisioning based on the estimated latent traffic. Observed traffic could deviate from the original traffic demand and become latent when the traffic passes through congested links because of changes in user behavioral and/or applications as a result of degraded quality of experience (QoE). The latent traffic is actualized by improving congested link capacity. When link provisioning is based on observed traffic, actual traffic might cause new congestion at other links. Thus, network providers need to estimate the origin-destination (OD) original traffic demand for network planning. Although the estimation of original traffic has been well studied, the estimation was only applicable for links. In this paper, we propose a method to estimate latent OD traffic by combining and expanding techniques. The method consists of three steps. The first step is to estimate the actual OD traffic and loss rate from the actual traffic and packet loss rate of the links. The second step is to estimate the latent traffic demand. Finally, using this estimated demand, the link capacity and routing matrix are optimized. We evaluate our method by simulation and confirm that congestion could be avoided by capacity provisioning based on estimated latent traffic, while provisioning based on observed traffic retains the congestion. The combined method can avoid congestion with an increment of 23% compared with capacity provisioning only. We also evaluated our method's adaptability, i.e., the ability to estimate the required parameter for the estimations using fewer given values, but values obtained in the environment.</description><subject>capacity provisioning</subject><subject>Communications traffic</subject><subject>Demand</subject><subject>estimation</subject><subject>Links</subject><subject>Optimization</subject><subject>Parameter estimation</subject><subject>Provisioning</subject><subject>Traffic capacity</subject><subject>Traffic congestion</subject><subject>traffic engineering</subject><subject>Traffic flow</subject><subject>Traffic planning</subject><subject>Traffic volume</subject><issn>0916-8516</issn><issn>1745-1345</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpNUE1PAjEQbYwmIvoPPGzieXHabrflKAt-JBiU4LnpdltcArtrWw74661BkMvMm8l7bzIPoVsMA8wEvw9ONV63mwEBAsX7GwCIM9TDPGMpphk7Rz0Y4jwVDOeX6Mr7FQAWBJMeep2321A3y0Q1VVKoTuk67JJZF-pN_a1C3TbJSHlTJRFMfNyqEIdprE1IZuNk4ZS1tU7GZhMdrtGFVWtvbv56H308ThbFczqdPb0UD9NUZ5yHtMIVU5APRU7KXAGxJasEtZaUlFsCudKV5ZoJgQmlpaa2MhYYGwKOfF0R2kd3e9_OtV9b44NctVvXxJOSsIznhAmgkZXtWdq13jtjZefiA24nMcjf4OQhOHkSXJTN97KVD2ppjiLlQq3X5l80wZDJkeQHcGJyJOtP5aRp6A-EXIAf</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>UCHIDA, Takumi</creator><creator>ISHIBASHI, Keisuke</creator><creator>FUKUDA, Kensuke</creator><general>The Institute of Electronics, Information and Communication Engineers</general><general>Japan Science and Technology Agency</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>20210701</creationdate><title>Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand</title><author>UCHIDA, Takumi ; ISHIBASHI, Keisuke ; FUKUDA, Kensuke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c477t-d1d5a069862b6a02fb5d83ff2b37f206acdf7c5881233bc3fdef0559012b6cd23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>capacity provisioning</topic><topic>Communications traffic</topic><topic>Demand</topic><topic>estimation</topic><topic>Links</topic><topic>Optimization</topic><topic>Parameter estimation</topic><topic>Provisioning</topic><topic>Traffic capacity</topic><topic>Traffic congestion</topic><topic>traffic engineering</topic><topic>Traffic flow</topic><topic>Traffic planning</topic><topic>Traffic volume</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>UCHIDA, Takumi</creatorcontrib><creatorcontrib>ISHIBASHI, Keisuke</creatorcontrib><creatorcontrib>FUKUDA, Kensuke</creatorcontrib><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEICE Transactions on Communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>UCHIDA, Takumi</au><au>ISHIBASHI, Keisuke</au><au>FUKUDA, Kensuke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand</atitle><jtitle>IEICE Transactions on Communications</jtitle><addtitle>IEICE Trans. Commun.</addtitle><date>2021-07-01</date><risdate>2021</risdate><volume>E104.B</volume><issue>7</issue><spage>781</spage><epage>790</epage><pages>781-790</pages><artnum>2020CQP0008</artnum><issn>0916-8516</issn><eissn>1745-1345</eissn><abstract>This paper introduces a method to estimate latent traffic from its origin to destination from the link packet loss rate and traffic volume. In addition, we propose a method for the joint optimization of routing and link provisioning based on the estimated latent traffic. Observed traffic could deviate from the original traffic demand and become latent when the traffic passes through congested links because of changes in user behavioral and/or applications as a result of degraded quality of experience (QoE). The latent traffic is actualized by improving congested link capacity. When link provisioning is based on observed traffic, actual traffic might cause new congestion at other links. Thus, network providers need to estimate the origin-destination (OD) original traffic demand for network planning. Although the estimation of original traffic has been well studied, the estimation was only applicable for links. In this paper, we propose a method to estimate latent OD traffic by combining and expanding techniques. The method consists of three steps. The first step is to estimate the actual OD traffic and loss rate from the actual traffic and packet loss rate of the links. The second step is to estimate the latent traffic demand. Finally, using this estimated demand, the link capacity and routing matrix are optimized. We evaluate our method by simulation and confirm that congestion could be avoided by capacity provisioning based on estimated latent traffic, while provisioning based on observed traffic retains the congestion. The combined method can avoid congestion with an increment of 23% compared with capacity provisioning only. We also evaluated our method's adaptability, i.e., the ability to estimate the required parameter for the estimations using fewer given values, but values obtained in the environment.</abstract><cop>Tokyo</cop><pub>The Institute of Electronics, Information and Communication Engineers</pub><doi>10.1587/transcom.2020CQP0008</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0916-8516
ispartof IEICE Transactions on Communications, 2021/07/01, Vol.E104.B(7), pp.781-790
issn 0916-8516
1745-1345
language eng
recordid cdi_proquest_journals_2547625803
source Alma/SFX Local Collection
subjects capacity provisioning
Communications traffic
Demand
estimation
Links
Optimization
Parameter estimation
Provisioning
Traffic capacity
Traffic congestion
traffic engineering
Traffic flow
Traffic planning
Traffic volume
title Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T00%3A24%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Routing%20and%20Capacity%20Optimization%20Based%20on%20Estimated%20Latent%20OD%20Traffic%20Demand&rft.jtitle=IEICE%20Transactions%20on%20Communications&rft.au=UCHIDA,%20Takumi&rft.date=2021-07-01&rft.volume=E104.B&rft.issue=7&rft.spage=781&rft.epage=790&rft.pages=781-790&rft.artnum=2020CQP0008&rft.issn=0916-8516&rft.eissn=1745-1345&rft_id=info:doi/10.1587/transcom.2020CQP0008&rft_dat=%3Cproquest_cross%3E2547625803%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2547625803&rft_id=info:pmid/&rfr_iscdi=true