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Open AccessArticle

QoSComm: A Data Flow Allocation Strategy among SDN-Based Data Centers for IoT Big Data Analytics

1
Faculty of Engineering, Architecture and Design, Universidad Autonoma de Baja California, Ensenada 22860, Mexico
2
Telematics Division, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Ensenada 22860, Mexico
3
Research, Innovation and Academic Division, Universidad Politecnica de Pachuca, Zempoala 43830, Mexico
4
Center for Computing Research, Instituto Politecnico Nacional, Ciudad de Mexico 07738, Mexico
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2020, 10(21), 7586; https://doi.org/10.3390/app10217586
Received: 8 October 2020 / Revised: 23 October 2020 / Accepted: 26 October 2020 / Published: 28 October 2020
(This article belongs to the Special Issue Internet of Things (IoT) 2020)
When Internet of Things (IoT) big data analytics (BDA) require to transfer data streams among software defined network (SDN)-based distributed data centers, the data flow forwarding in the communication network is typically done by an SDN controller using a traditional shortest path algorithm or just considering bandwidth requirements by the applications. In BDA, this scheme could affect their performance resulting in a longer job completion time because additional metrics were not considered, such as end-to-end delay, jitter, and packet loss rate in the data transfer path. These metrics are quality of service (QoS) parameters in the communication network. This research proposes a solution called QoSComm, an SDN strategy to allocate QoS-based data flows for BDA running across distributed data centers to minimize their job completion time. QoSComm operates in two phases: (i) based on the current communication network conditions, it calculates the feasible paths for each data center using a multi-objective optimization method; (ii) it distributes the resultant paths among data centers configuring their openflow Switches (OFS) dynamically. Simulation results show that QoSComm can improve BDA job completion time by an average of 18%. View Full-Text
Keywords: IoT big data analytics; SDN; QoS IoT big data analytics; SDN; QoS
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Lozano-Rizk, J.E.; Nieto-Hipolito, J.I.; Rivera-Rodriguez, R.; Cosio-Leon, M.A.; Vazquez-Briseño, M.; Chimal-Eguia, J.C. QoSComm: A Data Flow Allocation Strategy among SDN-Based Data Centers for IoT Big Data Analytics. Appl. Sci. 2020, 10, 7586.

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