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Abstract-Aiming at the problems of the construction of the service platform for the comprehensive management of natural disasters in China, and combining the cloud computing technology, the idea of comprehensive management service platform based on cloud computing is proposed. The platform can be used as a unified service platform for the comprehensive management of natural disasters. The platform integrates the functions of natural disaster data collection and storage, risk management system, monitoring and warning system, emergency response and decision, disaster evaluation, disaster business development and customization. Realize the new integration of knowledge resources of natural disasters and provide a variety of disaster information service for all kinds of users according to the authority. Not only improve the service quality, but also reduce the cost of operation and maintenance, and effectively improve the information, digital and intelligent level of disaster management.Index Terms-Natural disaster, comprehensive management, cloud computing. I. INTRODUCTIONIn recent years, under the background of global warming and world economic integration, many kinds of natural disasters, such as landslides, earthquakes, tsunamis and floods occur frequently in the global scope. The natural disasters come without warning and are impossible to avoid. As a result, natural disasters cause much serious casualties and property losses. What's worse, the damage caused by natural disasters need a very long time to recover [1], [2]. The integrated management of natural disasters is the more effective and advanced means and ways for natural disaster prevention, mitigation and management. After the reform and opening up, China has carried out a lot of useful exploration work on the risk assessment and management of natural disasters. However, compared with the advanced comprehensive integrated management platform established by United States, Japan and other developed countries, our research on the service platform for the comprehensive management of natural disasters exists some deficiencies [3], [4]: a wide range of existing natural disaster management system cause a lot of waste of resources and bring many maintenance and updates difficulties; most of the disaster management system Manuscript received December 9, 2015; revised June 3, 2016. This work was supported in part by the Bulgarian National Science Fund for the support under the Grant № DFNI-I02/ 15 from 2014.Xuejun Zong, Qiang Li, Zhongjun Yang, Kan He are with the Shenyang University of Chemical Technology, Shenyang, China (syictauto@163.com, syict_lq@163.com, syict_yzj@163.com, 29409385@qq.com).D. Velev is with the University of National and World Economy, Sofia 1700, Bulgaria (e-mail: dgvelev@unwe.bg).developed by C/S framework, service scope is limited; can't provide the flexibility services based on the needs of users, etc.The vigorous development of cloud computing technology provides a solution to solve the above problems and this paper presents a prelimina...

Offloading to fog servers makes it possible to process heavy computational load tasks in local devices. However, since the generation problem of offloading decisions is an N-P problem, it cannot be solved optimally or traditionally, especially in multitask offloading scenarios. Hence, this paper has proposed a randomization-based dynamic programming offloading algorithm, based on genetic optimization theory, to solve the offloading decision generation problem in mobile fog computing. The algorithm innovatively designs a dynamic programming table-filling approach, i.e., iteratively generates a set of randomized offloading decisions. If some in these sets improve the decisions in the DP table, then they will be merged into the table. The iterated DP table is also used to improve the set of decisions generated in the iteration to obtain the optimal offloading approximate solution. Extensive simulations show that the proposed DPOA can generate decisions within 3 ms and the benefit is especially significant when users are in multitask offloading scenarios.

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