LightFD: A lightweight flow detection mechanism for traffic grooming in optical wireless DCNs
LightFD: A lightweight flow detection mechanism for traffic grooming in optical wireless DCNs
Wireless data centers (DCs) are enablers of re-configurable data center network (DCN) topologies by augmenting the cabling complexity and inflexibility of traditional wired DCs. In this paper, we propose an optical traffic grooming (TG) for mice flows (MFs) and elephant flows (EFs) in a wireless DCN which is interconnected with free-space optical (FSO) links operating on wavelength division multiplexing (WDM). Since handling the bandwidth-hungry EFs along with delay-sensitive MFs over the same network resources have undesirable consequences, proposed TG policy treat MFs and EFs separately. MFs/EFs destined to the same rack are groomed into larger rack-to-rack MF/EF flows over dedicated lightpaths whose routes and capacities are jointly determined taking the load balancing into account. Performance evaluations of proposed TG policy show a significant throughput improvement thanks to bandwidth efficient utilization of the wireless links. Therefore, proposed TG requires expeditious flow detection mechanisms which can immediately classify EFs with very high accuracy. Since these demands cannot be met by existing sampling and port-mirroring based solutions, we propose a lightweight and fast in-network flow detection (LightFD) mechanism. LightFD is designed as a module on the Virtual-Switch/Hypervisor, which detects EFs based on acknowledgment sequence number of flow packets. Emulation results show that LightFD can provide up to 110 times faster detection speeds than sampling-based methods with %100 detection accuracy. We also demonstrate that the EF detection speed has a considerable impact on achievable EF throughput.
Alghadhban, Amer
b5789d22-f27e-4307-9483-2d5bdcd540d5
Celik, Abdulkadir
f8e72266-763c-4849-b38e-2ea2f50a69d0
Shihada, Basem
3aad5038-5b7e-4a97-9f22-7e310ea68a27
Alouini, Mohamed Slim
3ccd5915-318e-4f4b-b47a-48257ab4c0eb
2018
Alghadhban, Amer
b5789d22-f27e-4307-9483-2d5bdcd540d5
Celik, Abdulkadir
f8e72266-763c-4849-b38e-2ea2f50a69d0
Shihada, Basem
3aad5038-5b7e-4a97-9f22-7e310ea68a27
Alouini, Mohamed Slim
3ccd5915-318e-4f4b-b47a-48257ab4c0eb
Alghadhban, Amer, Celik, Abdulkadir, Shihada, Basem and Alouini, Mohamed Slim
(2018)
LightFD: A lightweight flow detection mechanism for traffic grooming in optical wireless DCNs.
In 2018 IEEE Global Communications Conference (GLOBECOM).
IEEE..
(doi:10.1109/GLOCOM.2018.8648021).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Wireless data centers (DCs) are enablers of re-configurable data center network (DCN) topologies by augmenting the cabling complexity and inflexibility of traditional wired DCs. In this paper, we propose an optical traffic grooming (TG) for mice flows (MFs) and elephant flows (EFs) in a wireless DCN which is interconnected with free-space optical (FSO) links operating on wavelength division multiplexing (WDM). Since handling the bandwidth-hungry EFs along with delay-sensitive MFs over the same network resources have undesirable consequences, proposed TG policy treat MFs and EFs separately. MFs/EFs destined to the same rack are groomed into larger rack-to-rack MF/EF flows over dedicated lightpaths whose routes and capacities are jointly determined taking the load balancing into account. Performance evaluations of proposed TG policy show a significant throughput improvement thanks to bandwidth efficient utilization of the wireless links. Therefore, proposed TG requires expeditious flow detection mechanisms which can immediately classify EFs with very high accuracy. Since these demands cannot be met by existing sampling and port-mirroring based solutions, we propose a lightweight and fast in-network flow detection (LightFD) mechanism. LightFD is designed as a module on the Virtual-Switch/Hypervisor, which detects EFs based on acknowledgment sequence number of flow packets. Emulation results show that LightFD can provide up to 110 times faster detection speeds than sampling-based methods with %100 detection accuracy. We also demonstrate that the EF detection speed has a considerable impact on achievable EF throughput.
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Published date: 2018
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© 2018 IEEE.
Venue - Dates:
2018 IEEE Global Communications Conference, GLOBECOM 2018, , Abu Dhabi, United Arab Emirates, 2018-12-09 - 2018-12-13
Identifiers
Local EPrints ID: 504842
URI: http://eprints.soton.ac.uk/id/eprint/504842
PURE UUID: a475a531-8ffb-484e-b736-408b436e3a13
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Date deposited: 19 Sep 2025 16:36
Last modified: 20 Sep 2025 02:30
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Contributors
Author:
Amer Alghadhban
Author:
Abdulkadir Celik
Author:
Basem Shihada
Author:
Mohamed Slim Alouini
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