Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics
Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traf...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020
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| Online Access: | http://eprints.utm.my/91922/1/KamalrulnizamAbuBakar2020_AdaptiveandHybridIdle%E2%80%93HardTimeoutAllocation.pdf |
| _version_ | 1796865323365826560 |
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| author | Isyaku, Babangida Abu Bakar, Kamalrulnizam Mohd. Zahid, Mohd. Soperi Yusuf, Muhammed Nura |
| author_facet | Isyaku, Babangida Abu Bakar, Kamalrulnizam Mohd. Zahid, Mohd. Soperi Yusuf, Muhammed Nura |
| author_sort | Isyaku, Babangida |
| collection | ePrints |
| description | Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics from the proliferation of the Internet of Thing (IoT) devices increase the processing load on the controller and generates an additional number of entries stored in the flow table. However, the switch flow table memory (TCAM) cannot accommodate many entries. Packets from multimedia flows are usually large in size and thus suffer processing delay and require more flow set up requests. The SDN controller may be overloaded and face some scalability problems because it supports a limited number of requests from switches. OpenFlow uses timeout configuration to manage flow setup request. The conventional fixed timeout cannot cope up with the dynamic nature of traffic flows. This paper controls the frequent flow setup requests by proposing an adaptive and hybrid idle–hard timeout allocation (AH-IHTA). The algorithm considers traffic patterns, flow table usage ratio, and returns appropriate the timeout to different flows. The performance evaluations conducted have shown a 28% and 39% reduction in the flow setup request and flow eviction, respectively. |
| first_indexed | 2024-03-05T20:55:14Z |
| format | Article |
| id | utm.eprints-91922 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T20:55:14Z |
| publishDate | 2020 |
| publisher | MDPI AG |
| record_format | dspace |
| spelling | utm.eprints-919222021-08-09T08:45:59Z http://eprints.utm.my/91922/ Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics Isyaku, Babangida Abu Bakar, Kamalrulnizam Mohd. Zahid, Mohd. Soperi Yusuf, Muhammed Nura QA75 Electronic computers. Computer science Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics from the proliferation of the Internet of Thing (IoT) devices increase the processing load on the controller and generates an additional number of entries stored in the flow table. However, the switch flow table memory (TCAM) cannot accommodate many entries. Packets from multimedia flows are usually large in size and thus suffer processing delay and require more flow set up requests. The SDN controller may be overloaded and face some scalability problems because it supports a limited number of requests from switches. OpenFlow uses timeout configuration to manage flow setup request. The conventional fixed timeout cannot cope up with the dynamic nature of traffic flows. This paper controls the frequent flow setup requests by proposing an adaptive and hybrid idle–hard timeout allocation (AH-IHTA). The algorithm considers traffic patterns, flow table usage ratio, and returns appropriate the timeout to different flows. The performance evaluations conducted have shown a 28% and 39% reduction in the flow setup request and flow eviction, respectively. MDPI AG 2020-11 Article PeerReviewed application/pdf en http://eprints.utm.my/91922/1/KamalrulnizamAbuBakar2020_AdaptiveandHybridIdle%E2%80%93HardTimeoutAllocation.pdf Isyaku, Babangida and Abu Bakar, Kamalrulnizam and Mohd. Zahid, Mohd. Soperi and Yusuf, Muhammed Nura (2020) Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics. Electronics (Switzerland), 9 (11). pp. 1-18. ISSN 2079292 http://dx.doi.org/10.3390/electronics9111983 |
| spellingShingle | QA75 Electronic computers. Computer science Isyaku, Babangida Abu Bakar, Kamalrulnizam Mohd. Zahid, Mohd. Soperi Yusuf, Muhammed Nura Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| title | Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| title_full | Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| title_fullStr | Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| title_full_unstemmed | Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| title_short | Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| title_sort | adaptive and hybrid idle hard timeout allocation and flow eviction mechanism considering traffic characteristics |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/91922/1/KamalrulnizamAbuBakar2020_AdaptiveandHybridIdle%E2%80%93HardTimeoutAllocation.pdf |
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