MIDAS: Multi-attribute indexing for distributed architecture systems

Tsatsanifos, G; Sacharidis, D; Sellis, T

dc.contributor.author	Tsatsanifos, G	en
dc.contributor.author	Sacharidis, D	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T02:53:21Z
dc.date.available	2014-03-01T02:53:21Z
dc.date.issued	2011	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36260
dc.subject	kd-trees	en
dc.subject	Peer-to-peer systems	en
dc.subject.other	Decentralized networks	en
dc.subject.other	Distributed architecture	en
dc.subject.other	Dynamic environments	en
dc.subject.other	Efficient algorithm	en
dc.subject.other	Experimental evaluation	en
dc.subject.other	Higher-dimensional	en
dc.subject.other	K-d tree	en
dc.subject.other	Multi-attributes	en
dc.subject.other	Overlay size	en
dc.subject.other	Partial knowledge	en
dc.subject.other	Peer to peer	en
dc.subject.other	Peer-to-peer systems	en
dc.subject.other	Prominent features	en
dc.subject.other	Range query	en
dc.subject.other	Algorithms	en
dc.subject.other	Fault tolerance	en
dc.subject.other	Indexing (of information)	en
dc.subject.other	Plant extracts	en
dc.subject.other	Distributed database systems	en
dc.title	MIDAS: Multi-attribute indexing for distributed architecture systems	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-22922-0_11	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-22922-0_11	en
heal.publicationDate	2011	en
heal.abstract	This work presents a pure multidimensional, indexing infrastructure for large-scale decentralized networks that operate in extremely dynamic environments where peers join, leave and fail arbitrarily. We propose a new peer-to-peer variant implementing a virtual distributed k-d tree, and develop efficient algorithms for multidimensional point and range queries. Scalability is enhanced as each peer has only partial knowledge of the network. The most prominent feature of our method, is that in expectance each peer maintains O(logn) state and requests are resolved in O(logn) hops with respect to the overlay size n. In addition, we provide mechanisms for handling peer failures and improving fault tolerance as well as balancing the load of peers. Finally, our work is complemented by an experimental evaluation, where MIDAS is shown to outperform existing methods in spatial as well as in higher dimensional settings. © 2011 Springer-Verlag.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-22922-0_11	en
dc.identifier.volume	6849 LNCS	en
dc.identifier.spage	168	en
dc.identifier.epage	185	en