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

Faculty of Engineering, Architecture and Design, Universidad Autonoma de Baja California, Ensenada 22860, Mexico
Telematics Division, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Ensenada 22860, Mexico
Research, Innovation and Academic Division, Universidad Politecnica de Pachuca, Zempoala 43830, Mexico
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;
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))
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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MDPI and ACS Style

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.

AMA Style

Lozano-Rizk JE, Nieto-Hipolito JI, Rivera-Rodriguez R, Cosio-Leon MA, Vazquez-Briseño M, Chimal-Eguia JC. QoSComm: A Data Flow Allocation Strategy among SDN-Based Data Centers for IoT Big Data Analytics. Applied Sciences. 2020; 10(21):7586.

Chicago/Turabian Style

Lozano-Rizk, Jose E., Juan I. Nieto-Hipolito, Raul Rivera-Rodriguez, Maria A. Cosio-Leon, Mabel Vazquez-Briseño, and Juan C. Chimal-Eguia 2020. "QoSComm: A Data Flow Allocation Strategy among SDN-Based Data Centers for IoT Big Data Analytics" Applied Sciences 10, no. 21: 7586.

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