A Cloud Based Disaster Management System

The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.info:eu-repo/semantics/publishedVersio

Cloud Based Intelligent Decision Support System for Disaster Management Using Fuzzy Logic

Field of cloud computing is an emerging field in computer science. Computational intelligence and Decisions Supports Systems (DSS) have to gained concerns as a computing solution to planned and unplanned problems of organizations in order to progress decision-making tasks in a better way. In today era, Disaster management is a big problem. To overcome this problem, a real time computation is required. Cloud computing is a tool to offer promising support to decision support system in a real time environment. In this paper, a fuzzy based decision support system is proposed to meet all the requirements using fuzzy logic inference system

Cloud Based Intelligent Decision Support System for Disaster Management Using Fuzzy Logic

Field of cloud computing is an emerging field in computer science. Computational intelligence and Decision support systems (DSS) have to gain concern as a computing solution to planned and unplanned problems of organizations in order to progress decision-making tasks in a better way. In today era, Disaster management is a big problem. To overcome this problem, a real time computation is required. Cloud computing is a tool to offer promising support to decision support system in a real time environment. In this paper, a fuzzy based decision support system is proposed to meet all the requirements using fuzzy logic inference system

The Hydra: A layered, redundant configuration management approach for cloud-agnostic disaster recovery

This paper demonstrates a bottom-up approach to developing autonomic fault tolerance and disaster recovery on cloud-based deployments. We avoid lock-in to specific recovery features provided by the cloud itself, and instead show that tools used in system administration today can provide the foundation for recovery processes with few additions. The resulting system, Hydra, is capable of detecting failures in instances and can redeploy any instance at a new location without human intervention. The layered design of configuration management tools enables separation of recovery processes and the actual service, making the Hydra applicable to a wide range of scenarios. The implementation was tested and an analysis of the recovery time is provided, demonstrating that the Hydra is capable of completely rebuilding a new site in 15 minutes

Geo-Distance Based 2- Replica Maintaining Algorithm for Ensuring the Reliability forever Even During the Natural Disaster on Cloud Storage System

In today's digitalized and globalized scenario, everyone has moved to cloud computing for storing their information on cloud storage to access their data from anywhere at any time. The most significant feature of cloud storage is its high availability and reliability then it has the capability of reducing management factors as well as incurred lower storage cost compared with some other storing methods, it is most suitable for a high volume of data storage. In order to meet the requirements of high availability and reliability, the system adopts a replication system concept. In replicating systems, the objects are replicated many times, with each copy residing in a different geographical location. Though it is beneficial to the users, it leads to some issues like security, integrity, consistency and hidden storage and maintenance cost, etc. Therefore, it is exposed to a few threats to the Cloud Storage System (CSS) user and the provider as well. So, this research seeks to explore the mechanisms to rectify the above-mentioned issues. Thus, the predecessor of the research work has proposed an algorithm named as 2-Replica Placing (2RP) algorithm which is used to reduce the storage cost, maintenance cost; and maintenance overheads as well as increase the available storage spaces for the providers by placing the data files on two locations based on Geo-Distance. But it fails to address the recovery mechanism when a natural disaster happens because providing reliability with less than 2 replicas is a challenging task for the providers. Thus, the research proposed Geo-distance based 2-Replica Maintaining (2RM) algorithm which is used to consider that issue for ensuring reliability forever even during natural disaster

Event-Cloud Platform to Support Decision- Making in Emergency Management

The challenge of this paper is to underline the capability of an Event-Cloud Platform to support efficiently an emergency situation. We chose to focus on a nuclear crisis use case. The proposed approach consists in modeling the business processes of crisis response on the one hand, and in supporting the orchestration and execution of these processes by using an Event-Cloud Platform on the other hand. This paper shows how the use of Event-Cloud techniques can support crisis management stakeholders by automatizing non-value added tasks and by directing decision- makers on what really requires their capabilities of choice. If Event-Cloud technology is a very interesting and topical subject, very few research works have considered this to improve emergency management. This paper tries to fill this gap by considering and applying these technologies on a nuclear crisis use-case