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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 (Hardcover, 2013 ed.)
Loot Price: R1,566
Discovery Miles 15 660
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Decentralized Spatial Computing - Foundations of Geosensor Networks (Hardcover, 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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