Publications de Ivana Podnar | EPFL Graph Search

OpenIoT: Open Source Internet-of-Things in the Cloud

Karl Aberer, Manfred Hauswirth, Jean Paul Calbimonte Perez, Ivana Podnar, Mehdi Riahi

Despite the proliferation of Internet-of-Things (IoT) platforms for building and deploying IoT applications in the cloud, there is still no easy way to integrate heterogeneous geographically and administratively dispersed sensors and IoT services in a sema ...

Springer2015

Distributed processing of continuous sliding-window k-NN queries for data stream filtering

Karl Aberer, Ivana Podnar, Kresimir Pripuzic

A sliding-window k-NN query (k-NN/w query) continuously monitors incoming data stream objects within a sliding window to identify k closest objects to a query. It enables effective filtering of data objects streaming in at high rates from potentially distr ...

Springer Verlag2011

Query-Driven Indexing for Scalable Peer-to-Peer Text Retrieval

Karl Aberer, Martin Rajman, Gleb Skobeltsyn, Vinh Toan Luu, Ivana Podnar

In this paper, we present a query-driven indexing/retrieval strategy for efficient full text retrieval from large document collections distributed within a structured P2P network. Our indexing strategy is based on two important properties: (1) the generate ...

2009

Query-Driven Indexing for Scalable Peer-to-Peer Text Retrieval

Karl Aberer, Martin Rajman, Gleb Skobeltsyn, Vinh Toan Luu, Ivana Podnar

We present a query-driven algorithm for the distributed indexing of large document collections within structured P2P networks. To cope with bandwidth consumption that has been identified as the major problem for the standard P2P approach with single term i ...

2009

Top-k/w publish/subscribe: finding k most relevant publications in sliding time window w

Karl Aberer, Ivana Podnar, Kresimir Pripuzic

Existing content-based publish/subscribe systems are designed assuming that all matching publications are equally relevant to a subscription. As we cannot know in advance the distribution of publication content, the following two unwanted situations are hi ...

ACM2008

AlvisP2P: Scalable Peer-to-Peer Text Retrieval in a Structured P2P Network

Karl Aberer, Martin Rajman, Fabius Klemm, Vinh Toan Luu, Gleb Skobeltsyn, Ivana Podnar

In this paper we present the AlvisP2P IR engine, which enables efficient retrieval with multi-keyword queries from a global document collection available in a P2P network. In such a network, each peer publishes its local index and invests a part of its loc ...

2008

Web Text Retrieval with a P2P Query-Driven Index

Karl Aberer, Martin Rajman, Gleb Skobeltsyn, Vinh Toan Luu, Ivana Podnar

In this paper, we present a query-driven indexing/retrieval strategy for efficient full text retrieval from large document collections distributed within a structured P2P network. Our indexing strategy is based on two important properties: (1) the generate ...

2007

Query-Driven Indexing for Peer-to-Peer Text Retrieval

Karl Aberer, Martin Rajman, Gleb Skobeltsyn, Vinh Toan Luu, Ivana Podnar

We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks. To cope with the bandwidth consumption problem that has been identified as the major obstacle for full-text retrieval in P2P networks, we truncate posti ...

2007

Scalable Peer-to-Peer Web Retrieval with Highly Discriminative Keys

Karl Aberer, Martin Rajman, Fabius Klemm, Vinh Toan Luu, Ivana Podnar

The suitability of peer-to-peer (P2P) approaches for full-text Web retrieval has recently been questioned because of the claimed unacceptable bandwidth consumption induced by retrieval from very large document collections. In this contribution we formalize ...

IEEE2007

A Peer-to-Peer Architecture for Information Retrieval Across Digital Library Collections

Karl Aberer, Martin Rajman, Fabius Klemm, Vinh Toan Luu, Ivana Podnar

Peer-to-peer networks have been identified as promising architectural concept for developing search scenarios across digital library collections. Digital libraries typically offer sophisticated search over their local content, however, search methods invol ...

Springer2006