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Disasters have long been a scourge for humanity. With the advances in technology (in terms of computing, communications, and the ability to process, and analyze big data), our ability to respond to disasters is at an inflection point. There is great optimism that big data tools can be leveraged to process large amounts of crisis-related data (in the form of user generated data in addition to traditional humanitarian data) to provide an insight into the fast-changing situation and help drive an effective disaster response. This article introduces the history and the future of big crisis data analytics, along with a discussion on its promise, enabling technologies, challenges, and pitfalls.

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With the explosion of social media sites and proliferation of digital computing devices and Internet access, massive amounts of public data is being generated on a daily basis. Efficient techniques/ algorithms to analyze this massive amount of data can provide near real-time information about emerging trends and provide early warning in case of an imminent emergency (such as the outbreak of a viral disease). In addition, careful mining of these data can reveal many useful indicators of socioeconomic and political events, which can help in establishing effective public policies. The focus of this study is to review the application of big data analytics for the purpose of human development. The emerging ability to use big data techniques for development (BD4D) promises to revolutionalize healthcare, education, and agriculture; facilitate the alleviation of poverty; and help to deal with humanitarian crises and violent conflicts. Besides all the benefits, the large-scale deployment of BD4D is beset with several challenges due to the massive size, fast-changing and diverse nature of big data. The most pressing concerns relate to efficient data acquisition and sharing, establishing of context (e.g., geolocation and time) and veracity of a dataset, and ensuring appropriate privacy. In this study, we provide a

Abstract-The Internet is inherently a multipath network-for an underlying network with only a single path connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity-through which a diverse collection of paths is resource pooled as a single resource-to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault-tolerance (through the use of multiple paths in backup/ redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be unmistakably multipath, including the use of multipath technology in datacenter computing; multi-interface, multi-channel, and multi-antenna trends in wireless; ubiquity of mobile devices that are multi-homed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as MP-TCP.The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely the control plane problem of how to compute and select the routes, and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work.