TY - JOUR
T1 - QOSCOMM
T2 - A data flow allocation strategy among sdn-based data centers for iot big data analytics
AU - Lozano-Rizk, Jose E.
AU - Nieto-Hipolito, Juan I.
AU - Rivera-Rodriguez, Raul
AU - Cosio-Leon, Maria A.
AU - Vazquez-Briseño, Mabel
AU - Chimal-Eguia, Juan C.
N1 - Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - 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%.
AB - 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%.
KW - IoT Big Data Analytics
KW - QoS
KW - SDN
UR - http://www.scopus.com/inward/record.url?scp=85094194926&partnerID=8YFLogxK
U2 - 10.3390/app10217586
DO - 10.3390/app10217586
M3 - Artículo
AN - SCOPUS:85094194926
SN - 2076-3417
VL - 10
SP - 1
EP - 19
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 21
M1 - 7586
ER -