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Efficacy of Power of Two Choices technique for Data Evacuation process in sensor networks for post-disaster relief operations

机译:灾后救援行动中传感器网络中数据疏散过程的两种选择方法的功效

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Disaster can occur in different forms-like earthquakes, flooding, tornadoes, oil spilling, mining accidents etc.; along with these natural calamities, a few disasters can be caused by human being-like sudden radiation of hazardous gas, explosion of hazardous gas tank, sudden leakage of polluted water etc. Disaster can affect human being directly or indirectly. All these disasters have not only the capability to destroy invaluable assets but also they can take plenty of lives. Post disaster information like damage level, any existence of life signal is very much essential for effective relief operations. To access post-disaster information, a few wireless sensor networks (WSNs) have already been proposed previously. However the proposed WSN solutions primarily assume that the deployed sensor network has the ability to tolerate any damage caused by different disaster and the sensor nodes of the network can maintain their connectivity and coverage, but practically a large portion of nodes can been easily destroyed by disasters. So practically, those assumptions taken by existing solutions are often invalid for different disaster scenario. One most practical and logical approach can be taking the advantage of survival time of sensor networks and sending critical data to any safe zone with in that time. In this paper we have proposed two techniques of data evacuation, i.e. modified Gradient based Data Evacuation (modified GRAD-DE) and Power of Two Choices based Data Evacuation (P2C-DE).
机译:灾难可能以不同形式发生,例如地震,洪水,龙卷风,漏油,采矿事故等;除这些自然灾害外,还可能由人类引起一些灾难,例如危险气体的突然辐射,危险气体罐的爆炸,污水的突然泄漏等。灾害可直接或间接地影响人类。所有这些灾难不仅具有销毁宝贵资产的能力,而且还可以夺走大量生命。灾后信息,如破坏程度,任何生命信号的存在对于有效的救援行动都是非常重要的。为了访问灾后信息,以前已经提出了一些无线传感器网络(WSN)。但是,提出的WSN解决方案主要假设已部署的传感器网络具有承受不同灾难造成的任何损害的能力,并且网络的传感器节点可以维持其连接性和覆盖范围,但是实际上,很大一部分节点很容易被灾难破坏。 。因此,实际上,现有解决方案采用的那些假设通常对于不同的灾难情况都是无效的。一种最实用且合乎逻辑的方法是,利用传感器网络的生存时间,然后在该时间内将关键数据发送到任何安全区域。在本文中,我们提出了两种数据疏散技术,即基于梯度的数据疏散改进(GRAD-DE改进)和基于两种选择的数据疏散的幂(P2C-DE)。

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