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A Preemption-Based Timely Software Defined Networking Framework for Emergency Response Traffic Delivery
Conference proceeding   Peer reviewed

A Preemption-Based Timely Software Defined Networking Framework for Emergency Response Traffic Delivery

Mohamed Rahouti, Kaiqi Xiong, Tommy Chin, Peizhao Hu and Diogo Oliveira
2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pp.452-459
IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS) (Zhangjiajie, China, 08/10/2019–08/12/2019)
2019
DOI: https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00074

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Abstract

Emergency Response System (ERS) End-to-End Delay (E2E) Preemption Priority Software-Defined Networking (SDN) Global Environment for Network Innovations (GENI) testbed Emergency or Disaster Planning or Policy Emergency Services
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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