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

• Main Authors: Jose E. Lozano-Rizk, Juan I. Nieto-Hipolito, Raul Rivera-Rodriguez, Maria A. Cosio-Leon, Mabel Vazquez-Briseño, Juan C. Chimal-Eguia
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Applied Sciences
• Subjects: IoT big data analytics; SDN; QoS
• Online Access: https://www.mdpi.com/2076-3417/10/21/7586

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%.