Scalable distributed processing of k nearest neighbor queries over moving objects

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Scalable distributed processing of k nearest neighbor queries over moving objects Do Your Projects With Technology Experts To Get this projects Call : 9566355386 / 99625 88976 Web : http://www.lemenizinfotech.com Web : http://www.ieeemaster.com Mail : projects@lemenizinfotech.com Blog : http://ieeeprojectspondicherry.weebly.com Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/ Youtube:https://www.youtube.com/watch?v=eesBNUnKvws

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Mail : projects@lemenizinfotech.com
Scalable Distributed Processing of K Nearest
Neighbor Queries over Moving Objects
Abstract
Central to many applications involving moving objects is the task of
processing k-nearest neighbor (k-NN) queries. Most of the existing approaches to
this problem are designed for the centralized setting where query processing takes
place on a single server; it is difficult, if not impossible, for them to scale to a
distributed setting to handle the vast volume of data and concurrent queries that are
increasingly common in those applications. To address this problem, we propose a
suite of solutions that can support scalable distributed processing of k-NN queries.
We first present a new index structure called Dynamic Strip Index (DSI), which
can better adapt to different data distributions than exiting grid indexes. Moreover,
it can be naturally distributed across the cluster, therefore lending itself well to
distributed processing. We further propose a distributed k-NN search (DKNN)
algorithm based on DSI. DKNN avoids having an uncertain number of potentially
expensive iterations, and is thus more efficient and more predictable than existing
approaches. DSI and DKNN are implemented on Apache S4, an open-source
platform for distributed stream processing. We perform extensive experiments to
study the characteristics of DSI and DKNN, and compare them with three baseline
methods. Experimental results show that our proposal scales well and significantly
outperforms the alternative methods.

Do Your Projects With Domain Experts…
Copyright © 2015 LeMeniz Infotech. All rights reserved
Page number 2Page number 2
LeMeniz Infotech
36, 100 Feet Road, Natesan Nagar, Near Indira Gandhi Statue,
Pondicherry-605 005.
Call: 0413-4205444, +91 9566355386, 99625 88976.
Web : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
EXISTING SYSTEM
Moving objects is the task of processing k-nearest neighbor (k-NN) queries.
Single server can be processing the query to scale to a distributed setting to handle
the vast volume of data and concurrent queries that are increasingly common in
those applications.
DRAWBACK OF EXISTING SYSTEM
 The volume of data in the Internet scale, because they implicitly assume a
centralized setting.
 Light update.
 Query workload.
 No longer viable.
 Exceeds the capacity of a single server.
PROPOSED SYSTEM
Scalable distributed processing of k-NN query method used in proposed
system Dynamic Strip Index (DSI), adapt to different data distributions than
exiting grid indexes. Distributed cluster that consists of a single master and
multiple slaves. More predictable performance than existing grid-based
approaches.
ADVANTAGE OF PROPOSED SYSTEM
 More efficient and more predictable
 Updates can be handled quickly.

Do Your Projects With Domain Experts…
Copyright © 2015 LeMeniz Infotech. All rights reserved
Page number 3Page number 3
LeMeniz Infotech
36, 100 Feet Road, Natesan Nagar, Near Indira Gandhi Statue,
Pondicherry-605 005.
Call: 0413-4205444, +91 9566355386, 99625 88976.
Web : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
 Good load balancing
SYSTEM SPECIFICATION
Hardware Requirements
System : Pentium IV 2.4 GHz
Hard Disk : 40 GB
Floppy Drive : 1.44 Mb
Monitor : 15 VGA Colour
Mouse : Logitech
Ram : 512 Mb
Software Requirements
Operating system : Windows Family
Tools : eclipse
Technology Used : Java
Backend Used : SQLITE

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