Abstract
In recent years, more and more researches are focusing on the field of disaster emergency management, especially in emergency resource dispatching. In a disaster scenario, a control center needs to obtain a large amount of real-time information at the scene to make decisions timely and accurately. Traditional Cloud Computing has many shortcomings in terms of delay and bandwidth, and Edge Computing (EC) will be more suitable for this scenario. We apply EC to the emergency rescue to cope with the problem of latency needs. First, we propose an edge-based emergency rescue architecture that consists of three layers: Cloud Layer, Edge Layer, and Resource Layer. Based on this, we give a resource scheduling model that requires the collaboration of Cloud and Edge Layers. The Cloud Layer gives a partition for these tasks, and all sub-tasks are assigning to the edge servers to get a locally optimal solution. Finally, these solutions from different edge servers are summarized to the Cloud Layer to get a globally optimal solution. We compare our algorithm with CS-GA and VRP. The simulation results show that RSE has good performance in scheduling time and cost.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhang, T.: Research on emergency resource scheduling in disaster emergency management. Hefei University of Technology (2015)
Chai, X.R.: Research on disaster emergency rescue material dispatching system. University of Science and Technology of China (2009)
Cai, J.M.: Research on time-varying and reliability related issues of earthquake disaster emergency logistics. Central South University (2012)
Zhao, T.: Research on optimization of emergency disaster material distribution system for sudden natural disasters in China. Dalian Maritime University (2011)
Xue, H., Cai, B., Jiang, C., Yuan, Y.: Research on the robust decision of emergency material distribution for chain retail supply chain. In: Chinese Control and Decision Conference (CCDC), Shenyang, pp. 1922–1927 (2018)
Gu, Y.: Study on scheduling model of emergency materials distribution after natural disaster. In: 2nd International Workshop on Intelligent Systems and Applications, Wuhan, pp. 1–4 (2010)
Sun, Q., Kong, F., Zhang, L., Dang, X.: Study on emergency distribution route decision making. In: International Conference on Mechatronic Science, Electric Engineering and Computer (MEC), Jilin, pp. 338–341 (2011)
Satria, D., Park, D., Jo, M.: Recovery for overloaded mobile edge computing. Future Gener. Comput. Syst. 70, 138–147 (2017)
Zhao, T., Zhou, S., Guo, X.: A cooperative scheduling scheme of l cloud and Internet cloud for delay-aware mobile cloud computing. In: Proceedings of IEEE GLOBECOM Workshops, pp. 1–6 (2015)
Flores, H., Hui, P., Tarkoma, S., Li, Y., Srirama, S., Buyya, R.: Mobile code offloading: from concept to practice and beyond. IEEE Commun. Mag. 53, 80–88 (2015)
Chen, X., Jiao, L., Li, W., Fu, X.: Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Netw. 24, 2795–2808 (2016)
You, C., Huang, K., Chae, H., Kim, B.H.: Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Trans. Wirel. Commun. 16, 1397–1411 (2017)
Sardellitti, S., Scutari, G., Barbarossa, S.: Joint optimization of radio and computational resources for multicell mobile-edge computing. IEEE Trans. Signal Inf. Process. Over Netw. 1, 89–103 (2015)
Taleb, T., Dutta, S., Ksentini, A., Iqbal, M., Flinck, H.: Mobile edge computing potential in making cities smarter. IEEE Commun. Mag. 55, 38–43 (2017)
Lin, S., Cheng, H.F., Li, W., Huang, Z., Hui, P., Peylo, C.: Ubii: physical world interaction through augmented reality. IEEE Trans. Mob. Comput. 16, 872–885 (2017)
Hu, Y., Patel, M., Sabella, D., et al.: Mobile edge computing: a key technology towards 5G. ETSI White Paper (2015)
Zhang, K., et al.: Energy-efficient offloading for mobile edge computing in 5G heterogeneous networks. IEEE Access J. 4, 5896–5907 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Zhong, S., He, T., Li, M., Rui, L., Xia, G., Zhu, Y. (2019). An Emergency Resource Scheduling Model Based on Edge Computing. In: Han, S., Ye, L., Meng, W. (eds) Artificial Intelligence for Communications and Networks. AICON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-030-22971-9_31
Download citation
DOI: https://doi.org/10.1007/978-3-030-22971-9_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-22970-2
Online ISBN: 978-3-030-22971-9
eBook Packages: Computer ScienceComputer Science (R0)