<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Carlos Baquero Moreno</style></author><author><style face="normal" font="default" size="100%">Nuno Lopes</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Implementing range queries with a decentralized balanced tree over distributed hash tables</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 1st international conference on Network-based information systems - Nbis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">November </style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://link.springer.com/chapter/10.1007%2F978-3-540-74573-0_21</style></url></web-urls><related-urls><url><style face="normal" font="default" size="100%">https://haslab.uminho.pt/sites/default/files/cbm/files/nbis07.pdf</style></url></related-urls></urls><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><volume><style face="normal" font="default" size="100%">4658</style></volume><pages><style face="normal" font="default" size="100%">197–206</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Range queries, retrieving all keys within a given range, is an important add-on for Distributed Hash Tables (DHTs), as they rely only on exact key matching lookup. In this paper we support range queries through a balanced tree algorithm, Decentralized Balanced Tree, that runs over any DHT system.&lt;/p&gt;
&lt;p&gt;Our algorithm is based on the B+-tree design that efficiently stores clustered data while maintaining a balanced load on hosts. The internal structure of the balanced tree is suited for range queries operations over many data distributions since it easily handles clustered data without losing performance.&lt;/p&gt;
&lt;p&gt;We analyzed, and evaluated our algorithm under a simulated environment, to show it's operation scalability for both insertions and queries. We will show that the system design imposes a fixed penalty over the DHT access cost, and thus inherits the scalability properties of the chosen underlying DHT.&lt;/p&gt;
</style></abstract></record></records></xml>