Multicloud-Based Evacuation Services for Emergency Management

A smart evacuation needs a scalable and flexible system to provide service in both emergency and normal situations. A single cloud service is usually limited to support scaling up requirements in an emergency, especially one with a large geographic scope. In this article, the authors propose MCES, a multicloud architecture that deploys smart evacuation services in multiple cloud providers and that can tolerant more pressure than single cloud-based services. This system maintains basic service to support monitoring, but during an emergency, visits to the service will scale up enormously, which means MDSE must support a rapid scaling up of service capacity in a short time. The authors use a three-layer cloud instance management to support rapid capacity scaling in MCES. By conducting extensive simulations, the authors demonstrate that their proposed MCES significantly outperforms single cloud solutions under various emergency settings.

[1]  N CalheirosRodrigo,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011 .

[2]  Mianxiong Dong,et al.  HVSTO: Efficient privacy preserving hybrid storage in cloud data center , 2014, 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[3]  Li-Chun Wang,et al.  Sensors-assisted rescue service architecture in mobile cloud computing , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[4]  Djamal Zeghlache,et al.  Cloud Service Delivery across Multiple Cloud Platforms , 2011, 2011 IEEE International Conference on Services Computing.

[5]  Rashid Mehmood,et al.  Intelligent disaster management system based on cloud-enabled vehicular networks , 2011, 2011 11th International Conference on ITS Telecommunications.

[6]  Calton Pu,et al.  Understanding Performance Interference of I/O Workload in Virtualized Cloud Environments , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[7]  Hannes Taubenböck,et al.  Emergency Preparedness in the Case of a Tsunami—Evacuation Analysis and Traffic Optimization for the Indonesian City of Padang , 2010 .

[8]  Shih-Jung Wu,et al.  An Integrated Building Fire Evacuation System with RFID and Cloud Computing , 2011, 2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[9]  Richard Han,et al.  RescueMe: An Indoor Mobile Augmented-Reality Evacuation System by Personalized Pedometry , 2011, 2011 IEEE Asia-Pacific Services Computing Conference.

[10]  Jan Broeckhove,et al.  Cost-Optimal Scheduling in Hybrid IaaS Clouds for Deadline Constrained Workloads , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[11]  Bu-Sung Lee,et al.  Optimal virtual machine placement across multiple cloud providers , 2009, 2009 IEEE Asia-Pacific Services Computing Conference (APSCC).

[12]  Jian Wang,et al.  Modeling and simulation for natural disaster contingency planning driven by high-resolution remote sensing images , 2014, Future Gener. Comput. Syst..

[13]  Johan Tordsson,et al.  Policy-Driven Service Placement Optimization in Federated Clouds , 2011 .

[14]  César A. F. De Rose,et al.  Server consolidation with migration control for virtualized data centers , 2011, Future Gener. Comput. Syst..

[15]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[16]  Jian Wang,et al.  Cloud Service-Oriented Modeling and Simulation of Regional Crowd Evacuation in Emergency , 2014, WAIM Workshops.