Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic
The existing Internet provides best effort service. As such the quality of service (QoS) perceived by a user is inconsistent and unpredictable. In particular, the QoS for such applications is often poor when the links between communicating entities are congested or subject to sudden and unpredictabl...
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my.uniten.dspace-298832023-12-28T16:58:03Z Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic Din N.M. Fisal N. 9335429400 16021700100 Bandwidth Channel allocation Diffserv networks Fuzzy logic Multiprotocol label switching Quality of service Resource management Search engines Surges Web and internet services Bandwidth Fuzzy logic Internet Internet protocols Memory architecture Network architecture Resource allocation Routers Search engines Telecommunication services Channel allocation Diffserv networks Internet services Multi protocol label switching Resource management Surges Quality of service The existing Internet provides best effort service. As such the quality of service (QoS) perceived by a user is inconsistent and unpredictable. In particular, the QoS for such applications is often poor when the links between communicating entities are congested or subject to sudden and unpredictable traffic surge. It is therefore desirable to introduce new service architecture in the Internet that guarantees QoS to continuous media application. The DiffServ architecture combined with multi protocol label switching (MPLS) have become a promising mechanism of achieving QoS with the scalability required by the Internet. MPLS achieves fast forwarding of packets through its connection-oriented framework. The MPLS edge router assigns packets with labels. Label switched routers in the MPLS core network direct the packets based on their labels. This paper addresses the resource allocation concerns at the DiffServ-enabled MPLS edge node. A DiffServ-MPLS dynamic link bandwidth allocation engine is described. The link bandwidth allocation engine is based on fuzzy logic and the maximum bandwidth allocation scheme. This work demonstrates that the fuzzy logic scheduler can be used in a hierarchical manner, where it first allocates link bandwidth based on three main traffic classes, i.e. premium, assured and best effort and then divides and allocates the bandwidth in the assured class further, i.e. gold, silver and bronze. � 2003 IEEE. Final 2023-12-28T08:58:03Z 2023-12-28T08:58:03Z 2003 Conference paper 10.1109/APCC.2003.1274371 2-s2.0-84903837965 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903837965&doi=10.1109%2fAPCC.2003.1274371&partnerID=40&md5=6fe5abd7a22cc6e9b45604114621f735 https://irepository.uniten.edu.my/handle/123456789/29883 1 1274371 339 343 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Bandwidth Channel allocation Diffserv networks Fuzzy logic Multiprotocol label switching Quality of service Resource management Search engines Surges Web and internet services Bandwidth Fuzzy logic Internet Internet protocols Memory architecture Network architecture Resource allocation Routers Search engines Telecommunication services Channel allocation Diffserv networks Internet services Multi protocol label switching Resource management Surges Quality of service |
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Bandwidth Channel allocation Diffserv networks Fuzzy logic Multiprotocol label switching Quality of service Resource management Search engines Surges Web and internet services Bandwidth Fuzzy logic Internet Internet protocols Memory architecture Network architecture Resource allocation Routers Search engines Telecommunication services Channel allocation Diffserv networks Internet services Multi protocol label switching Resource management Surges Quality of service Din N.M. Fisal N. Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic |
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The existing Internet provides best effort service. As such the quality of service (QoS) perceived by a user is inconsistent and unpredictable. In particular, the QoS for such applications is often poor when the links between communicating entities are congested or subject to sudden and unpredictable traffic surge. It is therefore desirable to introduce new service architecture in the Internet that guarantees QoS to continuous media application. The DiffServ architecture combined with multi protocol label switching (MPLS) have become a promising mechanism of achieving QoS with the scalability required by the Internet. MPLS achieves fast forwarding of packets through its connection-oriented framework. The MPLS edge router assigns packets with labels. Label switched routers in the MPLS core network direct the packets based on their labels. This paper addresses the resource allocation concerns at the DiffServ-enabled MPLS edge node. A DiffServ-MPLS dynamic link bandwidth allocation engine is described. The link bandwidth allocation engine is based on fuzzy logic and the maximum bandwidth allocation scheme. This work demonstrates that the fuzzy logic scheduler can be used in a hierarchical manner, where it first allocates link bandwidth based on three main traffic classes, i.e. premium, assured and best effort and then divides and allocates the bandwidth in the assured class further, i.e. gold, silver and bronze. � 2003 IEEE. |
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9335429400 |
author_facet |
9335429400 Din N.M. Fisal N. |
format |
Conference paper |
author |
Din N.M. Fisal N. |
author_sort |
Din N.M. |
title |
Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic |
title_short |
Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic |
title_full |
Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic |
title_fullStr |
Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic |
title_full_unstemmed |
Dynamic resource allocation of IP traffic for a DiffServ-MPLS interface using fuzzy logic |
title_sort |
dynamic resource allocation of ip traffic for a diffserv-mpls interface using fuzzy logic |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
_version_ |
1806427965793239040 |
score |
13.214268 |