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Given an arbitrary viewpoint v and a terrain, the visibility map or viewshed of v is the set of points in the terrain that are visible from v. In this article we consider the problem of computing the viewshed of a point on a very large grid terrain in external memory. We describe algorithms for this problem in the cache-aware and cache-oblivious models, together with an implementation and an experimental evaluation. Our algorithms are a novel application of the distribution sweeping technique and use O(sort(n)) I/Os, where sort(n) is the complexity of sorting n items of data in the I/O-model. The experimental results demonstrate that our algorithm scales up and performs significantly better than the traditional internal-memory plane sweep algorithm and can compute visibility for terrains of 1.1 billion points in less than 4 hours on a low-cost machine compared to more than 32 hours with the internal-memory algorithm.

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Computed tomography image (CTI) sequence is essentially a time-series data that typically consists of a large amount of nearby and similar CTIs. Due to the high communication and computational costs, it is difficult to perform a progressive distributed similarity retrieval of the large CTI sequence (CTIS)s, particularly in resource-constraint mobile telemedicine network (MTN)s. In this paper, we present a Dprs method—progressive distributed and parallel similarity retrieval scheme for the CTISs in the MTN. To the best of our knowledge, there is little research on the Dprs processing, especially in the MTN. Four supporting techniques (i.e., (1) PCTI-based similarity measurement, (2) lightweight privacy-preserving strategy, (3) SSL-based data distribution scheme, and (4) the UDI framework) are developed. The experimental evaluation indicates that our proposed Dprs method is more progressive than the state of the art, with a significant reduction in response time.

When a disaster occurs, timely actions in response to urgent requests conveyed by critical messages (known as alerts) constitute a vital key to effectiveness. These actions include notifying potentially affected parties so that they can take precautionary measures, gathering additional information, and requesting remedial actions and resource allocation. However, there are different types of disasters such as epidemic outbreaks, natural disasters, major accidents, and terrorist attacks. At the same time, there are also many different parties involved such as governments, healthcare institutions, businesses, and individuals. To address these problems, we introduce a Disaster Notification and Resource Allocation System (DNRAS) based on an Alert Management System (AMS) implemented through Web services. This unified platform supports timely interactions among various parties, focusing on notification and monitoring, resource enquiry and allocation, as well as the mobility of information. We detail the mechanisms of these functions in our system, illustrating the Web services interface parameters for communications and interoperability. We illustrate the applicability of our approach with an example of an epidemic outbreak and discuss the advantage of our approach with respect to various stakeholders of our system.