Neighbours on a Grid

نویسندگان

  • Andrej Brodnik
  • J. Ian Munro
چکیده

We address the problem of a succinct static data structure representing points on anM M grid (M = 2m where m is size of a word) that permits to answer the question of finding the closest point to a query point under the L1 or L1 norm in constant time. Our data structure takes essentially minimum space. These results are extended to d dimensions underL1 .

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Scalable Geographic Routing Protocol for Mobile Ad Hoc Network with Grid Positioning System

This paper examine that the geographic routing protocols are used in the mobile ad hoc networks. In routing protocols defines that each node identify the position of one hop neighbours, and also the packets are forwarded to a neighbours that is closer to the destination. This forwarding strategy should prevent radio communications between node. However, inexpensive position devices do not provi...

متن کامل

Weighted codes in Lee metrics

Perfect weighted coverings of radius one have been often studied in the Hamming metric. In this paper, we study these codes in the Lee metric. To simplify the notation, we use a slightly different description, yet equivalent. Given two integers a and b , an (a, b)-code is a set of vertices such that vertices in the code have a neighbours in the code and other vertices have b neighbours in the c...

متن کامل

A Parallel Implementation of the K Nearest Neighbours Classifier in Three Levels: Threads, MPI Processes and the Grid

The work described in this paper tackles the problem of data mining and classification of large amounts of data using the K nearest neighbours classifier (KNN) [1]. The large computing demand of this process is solved with a parallel computing implementation specially designed to work in Grid environments of multiprocessor computer farms. The different parallel computing approaches (intra-node,...

متن کامل

On improving APIT algorithm for better localization in WSN

In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors to reduce PIT test errors (edge effect and non-uniform placement of neighbours) in APIT a...

متن کامل

Pseudo-Likelihood Inference Underestimates Model Uncertainty: Evidence from Bayesian Nearest Neighbours

When using the K-nearest neighbours (KNN) method, one often ignores the uncertainty in the choice of K. To account for such uncertainty, Bayesian KNN (BKNN) has been proposed and studied (Holmes and Adams 2002 Cucala et al. 2009). We present some evidence to show that the pseudo-likelihood approach for BKNN, even after being corrected by Cucala et al. (2009), still significantly underest...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1996