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Spatio-temporal Networks: Modeling And Algorithms (springerbriefs In Computer Science) by Betsy George, Sangho Kim (auth.) is a nonfiction available to read on EtoBox.

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Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users. STN modeling and computations raise significant challenges. The model must meet the conflicting requirements of simplicity and adequate support for efficient algorithms. Another challenge is to address the change in the semantics of common graph operations, such as, shortest path computation assuming different semantics, or when temporal dimension is added. Also paradigms (e.g. dynamic programming) used in algorithm design may be ineffective since their assumptions (e.g. stationary ranking of candidates) may be violated by the dynamic nature of STNs. In recent years, STNs have attracted attention in research. New representations have been proposed along with algorithms to perform key STN operations, while accounting for their time dependence. Designing a STN database would require the development of data models, query languages, and indexing methods to efficiently represent, query, store, and manage time-variant prope

Who reads Spatio-temporal Networks: Modeling And Algorithms (springerbriefs In Computer Science)?

Author

Betsy George, Sangho Kim (auth.)

Publisher

Springer-Verlag New York

Published

2013

Language

EN

ISBN

9786613937117

Category

nonfiction

Subjects

Computer Science, Anthropology, Mathematics