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Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
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Decentralized Spatial Computing - Foundations of Geosensor Networks (Paperback, 2013 ed.)
Loot Price: R2,405
Discovery Miles 24 050
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Decentralized Spatial Computing - Foundations of Geosensor Networks (Paperback, 2013 ed.)
Expected to ship within 10 - 15 working days
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Computing increasingly happens somewhere, with that geographic
location important to the computational process itself. Many new
and evolving spatial technologies, such as geosensor networks and
smartphones, embody this trend. Conventional approaches to spatial
computing are centralized, and do not account for the inherently
decentralized nature of "computing somewhere": the limited, local
knowledge of individual system components, and the interaction
between those components at different locations. On the other hand,
despite being an established topic in distributed systems,
decentralized computing is not concerned with geographical
constraints to the generation and movement of information. In this
context, of (centralized) spatial computing and decentralized
(non-spatial) computing, the key question becomes: "What makes
decentralized spatial computing special?" In Part I of the book the
author covers the foundational concepts, structures, and design
techniques for decentralized computing with spatial and
spatiotemporal information. In Part II he applies those concepts
and techniques to the development of algorithms for decentralized
spatial computing, stepping through a suite of increasingly
sophisticated algorithms: from algorithms with minimal spatial
information about their neighborhoods; to algorithms with access to
more detailed spatial information, such as direction, distance, or
coordinate location; to truly spatiotemporal algorithms that
monitor environments that are dynamic, even using networks that are
mobile or volatile. Finally, in Part III the author shows how
decentralized spatial and spatiotemporal algorithms designed using
the techniques explored in Part II can be simulated and tested. In
particular, he investigates empirically the important properties of
a decentralized spatial algorithm: its computational efficiency and
its robustness to unavoidable uncertainty. Part III concludes with
a survey of the opportunities for connecting decentralized spatial
computing to ongoing research and emerging hot topics in related
fields, such as biologically inspired computing, geovisualization,
and stream computing. The book is written for students and
researchers of computer science and geographic information science.
Throughout the book the author's style is characterized by a focus
on the broader message, explaining the process of decentralized
spatial algorithm design rather than the technical details. Each
chapter ends with review questions designed to test the reader's
understanding of the material and to point to further work or
research. The book includes short appendices on discrete
mathematics and SQL. Simulation models written in NetLogo and
associated source code for all the algorithms presented in the book
can be found on the author's accompanying website.
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