TY - GEN
T1 - A preemption-based timely software defined networking framework for emergency response traffic delivery
AU - Rahouti, Mohamed
AU - Xiong, Kaiqi
AU - Chin, Tommy
AU - Hu, Peizhao
AU - Oliveira, Diogo
N1 - Funding Information:
We would like to acknowledge the National Science Foundation (NSF) that partially sponsored the work under grants #1633978, #1620871, #1620862, #1651280, and BBN/GPO project #1936 through NSF/CNS grant. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied of NSF.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - In the last several years, the large-scale evolution of emergency response system (ERS) has been enabled by technological advances in the area of Information and Communication Technology (ICT). The ultimate goal of such an ERS is to optimize compute resources to meet customer requirements. Specifically, emergency network traffic should be delivered in a timely manner to help with rescue efforts and recovery once a crisis takes a place. The delivered emergency traffic is usually categorized according to the priority level. In this paper, we consider the adoption of Software Defined Networking (SDN) to support preemptive emergency responses, where we develop an SDN framework to optimize the end-to-end (E2E) delay for emergency service delivery according to the urgency level of services. The emergency service is delivered based on preemptive policies. The proposed SDN-based ERS framework is evaluated on the Global Environment for Network Innovations (GENI) testbed with real-world emergency data whose urgency levels range from 0 to 50. Our experimental evaluation demonstrates that the proposed framework is efficient in delivering emergency service depending on data urgency level. Specifically, our framework provides an improvement of average E2E delays where the preemptive response service guarantees approximately 30% in E2E delay reduction for data with the highest priority. The proposed framework can be applicable to other cyber-physical systems and smart city-enabled applications.
AB - In the last several years, the large-scale evolution of emergency response system (ERS) has been enabled by technological advances in the area of Information and Communication Technology (ICT). The ultimate goal of such an ERS is to optimize compute resources to meet customer requirements. Specifically, emergency network traffic should be delivered in a timely manner to help with rescue efforts and recovery once a crisis takes a place. The delivered emergency traffic is usually categorized according to the priority level. In this paper, we consider the adoption of Software Defined Networking (SDN) to support preemptive emergency responses, where we develop an SDN framework to optimize the end-to-end (E2E) delay for emergency service delivery according to the urgency level of services. The emergency service is delivered based on preemptive policies. The proposed SDN-based ERS framework is evaluated on the Global Environment for Network Innovations (GENI) testbed with real-world emergency data whose urgency levels range from 0 to 50. Our experimental evaluation demonstrates that the proposed framework is efficient in delivering emergency service depending on data urgency level. Specifically, our framework provides an improvement of average E2E delays where the preemptive response service guarantees approximately 30% in E2E delay reduction for data with the highest priority. The proposed framework can be applicable to other cyber-physical systems and smart city-enabled applications.
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U2 - 10.1109/HPCC/SmartCity/DSS.2019.00074
DO - 10.1109/HPCC/SmartCity/DSS.2019.00074
M3 - Conference contribution
AN - SCOPUS:85073547657
T3 - Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019
SP - 452
EP - 459
BT - Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019
A2 - Xiao, Zheng
A2 - Yang, Laurence T.
A2 - Balaji, Pavan
A2 - Li, Tao
A2 - Li, Keqin
A2 - Zomaya, Albert
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019
Y2 - 10 August 2019 through 12 August 2019
ER -
