Submit Articles A Collection of Informative and Interesting Articles  
 
HOME LOGIN SUBMIT ARTICLES TOP AUTHORS WANT AN ACCOUNT?
 

Reverse Nearest Neighbors Search in Wireless Broadcast Environment

BY: NILAMADHAB MISHRA | Category: Technology | Submitted: 2013-03-10 04:58:13
       Author Photo
Article Summary: "In this presentation, prof Liu highlighted initially the wireless data broadcasting and the access of data in mobile environment, which are described as pull based, push based, on demand push based and hybrid based. Data broadcasting is an effective way to distribute information to a large amount of mobile clients in wireless mo.."


Share with Facebook Share with Linkedin Share with Twitter Share with Pinterest Email this article




In this presentation, prof Liu highlighted initially the wireless data broadcasting and the access of data in mobile environment, which are described as pull based, push based, on demand push based and hybrid based. Data broadcasting is an effective way to distribute information to a large amount of mobile clients in wireless mobile environments. Many information services can use such a technique to serve the clients, including location-based services. The reverse nearest neighbor (RNN) search is one of the most important location-based services. In mobile broadcast model two methods are mainly used to spread information i.e. broadcasting only data and data broadcasting with index. The data broadcasting problem can be solved through single channel and multi-channel problem.

Prof Liu talked over about the location based service to incorporate different type's queries like point query, range query, kNN query and finally the Reverse nearest neighbors query. The Reverse nearest neighbors query uses single query point and multi-data points.

The prof also emphasized different broadcast schedules with the client k-NN search processing which makes different k-NN search protocols. The objectives of the protocols are to minimize the latency (i.e., the time elapsed between issuing and termination of the query), tuning time (i.e., the amount of time spent on listening to the channel), and the memory usage for k-NN search processing. At the end prof presented his experiments and the experiment results to achieve the objectives.

About Author / Additional Info:

Comments on this article: (0 comments so far)

Comment Comment By Comment Date

Leave a Comment   |   Article Views: 3991


Additional Articles:
•   Perceptual Mapping in Human Resource Management: An Insight

•   One of the Many Trends That Need a Change

•   POEM: Is Suzainna a Sinner?

•   Simple Definition of Caveat Loans


Latest Articles in "Technology" category:
•   Security Robots on Patrol

•   Apple Pay Overview

•   Enterprise Mobility - Overview Part 1

•   M-OTA: Mobile 'Over-The- Air' (OTA) Overview

•   MDM: Mobile Device Management Overview

•   3M MAC Protocol Review

•   Build, Deploy and Test - Advanced Software Development Practice - Part 1



Important Disclaimer: All articles on this website are for general information only and is not a professional or experts advice. We do not own any responsibility for correctness or authenticity of the information presented in this article, or any loss or injury resulting from it. We do not endorse these articles, we are neither affiliated with the authors of these articles nor responsible for their content. Please see our disclaimer section for complete terms.
Page copy protected against web site content infringement by Copyscape
Copyright © 2010 saching.com - Do not copy articles from this website.
| Home | Disclaimer | Xhtml |