Isyaku, Babangida and Abu Bakar, Kamalrulnizam and Mohd. Zahid, Mohd. Soperi and Alkhammash, Eman H. and Saeed, Faisal and Ghaleb, Fuad A. (2021) Route path selection optimization scheme based link quality estimation and critical switch awareness for software defined networks. Applied Sciences (Switzerland), 11 (19). pp. 1-17. ISSN 2076-3417
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Official URL: http://dx.doi.org/10.3390/app11199100
Abstract
Software-defined network (SDN) is a new paradigm that decouples the control plane and data plane. This offered a more flexible way to efficiently manage the network. However, the in-creasing number of traffics due to the proliferation of the Internet of Things (IoT) devices also in-crease the number of flow arrival which in turn causes flow rules to change more often, and simi-larly, path setup requests increased. These events required route path computation activities to take place immediately to cope with the new network changes. Searching for an optimal route might be costly in terms of the time required to calculate a new path and update the corresponding switches. However, the current path selection schemes considered only single routing metrics either link or switch operation. Incorporating link quality and switch’s role during path selection decisions have not been considered. This paper proposed Route Path Selection Optimization (RPSO) with multi-constraint. RPSO introduced joint parameters based on link and switches such as Link Latency (LL), Link Delivery Ratio (LDR), and Critical Switch Frequency Score (CWFscore). These metrics encour-age path selection with better link quality and a minimal number of critical switches. The experimental results show that the proposed scheme reduced path stretch by 37%, path setup latency by 73% thereby improving throughput by 55.73%, and packet delivery ratio by 12.5% compared to the baseline work.
Item Type: | Article |
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Uncontrolled Keywords: | openflow, path selection, restoration, SDN |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computing |
ID Code: | 94799 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 29 Apr 2022 22:27 |
Last Modified: | 29 Apr 2022 22:27 |
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