利用机会主义网络为灾后情况认识发展连贯的全球观点

Apratim Mukherjee, Souvik Basu, Siuli Roy, S. Bandyopadhyay
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引用次数: 8

摘要

在灾后恢复行动中,态势感知是评估受灾地区不同地区需求和确定可用资源的关键组成部分。这些资料反过来又可帮助救济机构适当地协调、管理和分配其资源。发展这种全球形势意识的一个主要障碍是救济工作人员的不统一的互动模式。某一特定地区的志愿者比其他地区的志愿者更了解当地情况。这种信息不对称导致对不同地区志愿者工作的认知出现偏差,从而影响资源的分配过程。因此,一个统一的整个受灾地区的全球情况视图对于弥合志愿者的认知差距并帮助他们对实际情况形成共同的理解至关重要。在本文中,我们提出了一种方案,在基于智能手机的延迟容忍点对点网络环境中,利用当地的情景信息来开发灾后情况的连贯全局视图。我们专注于生成一个全面的视图,无论他们的位置或流动性如何,它都是一致的。该方案考虑了人类活动的空间局部性和空间规律性,并采用“机会性知识注入”的概念,在没有显著网络开销的情况下,将当地的情景知识传播到其他偏远地区。在ONE仿真机上对该方案的有效性进行了评估。
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Developing a coherent global view for post disaster situation awareness using opportunistic network
Situational awareness is a critical component in a post-disaster recovery operation for assessment of needs and identification of available resources at different parts of a disaster-affected area. This information, in turn, may help the relief agencies to appropriately coordinate, manage and channelize their resources. A major hindrance in developing such global situational awareness is the non-uniform interaction pattern of relief workers. Volunteers in a particular region have much better knowledge of the local situation than those belonging to regions further away. This information asymmetry leads to deviation in perceptions of volunteers working in different regions, thereby affecting the resource distribution process. Thus, a unified global situational view of the entire disaster affected area is essential to bridge the perception gap of volunteers and to help them develop a common understanding of the actual scenario. In this paper, we propose a scheme for developing such a coherent global view of the post-disaster situation using local situational information in a smart-phone based delay tolerant peer-to-peer network environment.We focus on generating a comprehensive view which is consistent for all workers irrespective of their location or mobility. The proposed scheme takes into account the spatial locality and spatial regularity properties of human mobility and uses a concept of “opportunistic knowledge injection” to disseminate local situational knowledge to other remote areas without significant network overhead. The effectiveness of the proposal is evaluated on the ONE simulator.
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