Abstract
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.
| Original language | English (US) |
|---|---|
| Title of host publication | 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 |
| Editors | Zheng Xiao, Laurence T. Yang, Pavan Balaji, Tao Li, Keqin Li, Albert Zomaya |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 452-459 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781728120584 |
| DOIs | |
| State | Published - Aug 2019 |
| Event | 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 - Zhangjiajie, China Duration: Aug 10 2019 → Aug 12 2019 |
Publication series
| Name | 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 |
|---|
Conference
| Conference | 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 |
|---|---|
| Country/Territory | China |
| City | Zhangjiajie |
| Period | 8/10/19 → 8/12/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Information Systems
- Information Systems and Management
- Energy Engineering and Power Technology
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