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3 results on '"Vlachos, Michail"'

1. Finding the K highest-ranked answers in a distributed network

Author

Zeinalipour-Yazdi, Constantinos D., Vagena, Zografoula, Kalogeraki, Vana, Gunopulos, Dimitrios, Tsotras, Vassilis J., Vlachos, Michail, Koudas, Nick, Srivastava, D., and Zeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]

Subjects
Sensor networks, Ad hoc networks, Theoretical computer science, Query processing, Computer Networks and Communications, Computer science, Join algorithms, Peer-to-peer, computer.software_genre, Network topology, Peer-to-peer networks, P2P networks, Electric network topology, Information retrieval, Test beds, Distributed Top-K query processing, Order of magnitudes, Network architecture, Vehicular ad hoc network, Testbed, Cost metric, Local area network, Arts computing, Network topologies, Shared resource, Distributed networks, Multi hops, Experimental methodologies, Non-uniform, Efficient algorithms, Metric (mathematics), Top-k queries, Experimental evaluations, Client server computer systems, computer, Algorithm, Wireless sensor network, Vehicular networks, Algorithms
Abstract

In this paper, we present an algorithm for finding the k highest-ranked (or Top-k) answers in a distributed network. A Top-K query returns the subset of most relevant answers, in place of all answers, for two reasons: (i) to minimize the cost metric that is associated with the retrieval of all answers and (ii) to improve the recall and the precision of the answer-set, such that the user is not overwhelmed with irrelevant results. Our study focuses on multi-hop distributed networks in which the data is accessible by traversing a network of nodes. Such a setting captures very well the computation framework of emerging Sensor Networks, Peer-to-Peer Networks and Vehicular Networks. We present the Threshold Join Algorithm (TJA), an efficient algorithm that utilizes a non-uniform threshold on the queried attribute in order to minimize the transfer of data when a query is executed. Additionally, TJA resolves queries in the network rather than in a centralized fashion which further minimizes the consumption of bandwidth and delay. We performed an extensive experimental evaluation of our algorithm using a real testbed of 75 workstations along with a trace-driven experimental methodology. Our results indicate that TJA requires an order of magnitude less communication than the state-of-the-art, scales well with respect to the parameter k and the network topology. © 2009 Elsevier B.V. All rights reserved. 53 9 1431 1449 Cited By :5

Published
2009

2. The threshold join algorithm for top-k queries in distributed sensor networks

Author

Zeinalipour-Yazdi, Constantinos D., Vagena, Zografoula, Gunopulos, Dimitrios, Kalogeraki, Vana, Tsotras, Vassilis J., Vlachos, Michail, Koudas, Nick, Srivastava, D., and Zeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]

Subjects
Similarity (geometry), Query processing, Querying nodes, Computer science, Distributed sensor networks, Communication medium, computer.software_genre, sensor networks, Transfer (computing), Similarity functions, Information retrieval, Top-k query processing, Join algorithm, TRACE (psycholinguistics), Nonuniform, distributed systems, Node (networking), Bandwidth (signal processing), top-K queries, Function (mathematics), Top-k query, Data mining, Tuple, Wireless sensor network, Algorithm, computer, Algorithms, Sensor network environment
Abstract

In this paper we present the Threshold Join Algorithm (TJA), which is an efficient TOP-k query processing algorithm for distributed sensor networks. The objective of a top-k query is to find the k highest ranked answers to a user defined similarity function. The evaluation of such a query in a sensor network environment is associated with the transfer of data over an extremely expensive communication medium. TJA uses a non-uniform threshold on the queried attribute in order to minimize the number of tuples that have to be transferred towards the querying node. Additionally, TJA resolves queries in the network rather than in a centralized fashion, which minimizes even more the consumption of bandwidth and delay. Our preliminary experimental results, using our trace driven simulator, show that TJA is both practical and efficient. Copyright 2005 ACM. 96 61 66 Sponsors: intel Conference code: 80982 Cited By :28

Published
2005

3. Right-Protected Data Publishing with Provable Distance-Based Mining.

Author

Zoumpoulis, Spyros I., Vlachos, Michail, Freris, Nikolaos M., and Lucchese, Claudio

Subjects
*DATA protection, *NEAREST neighbor analysis (Statistics), *DATA mining, *KNOWLEDGE management, *SPANNING trees, *ALGORITHMS
Abstract

Protection of one’s intellectual property is a topic with important technological and legal facets. We provide mechanisms for establishing the ownership of a dataset consisting of multiple objects. The algorithms also preserve important properties of the dataset, which are important for mining operations, and so guarantee both right protection and utility preservation. We consider a right-protection scheme based on watermarking. Watermarking may distort the original distance graph. Our watermarking methodology preserves important distance relationships, such as: the Nearest Neighbors (NN) of each object and the Minimum Spanning Tree (MST) of the original dataset. This leads to preservation of any mining operation that depends on the ordering of distances between objects, such as NN-search and classification, as well as many visualization techniques. We prove fundamental lower and upper bounds on the distance between objects post-watermarking. In particular, we establish a restricted isometry property, i.e., tight bounds on the contraction/expansion of the original distances. We use this analysis to design fast algorithms for NN-preserving and MST-preserving watermarking that drastically prune the vast search space. We observe two orders of magnitude speedup over the exhaustive schemes, without any sacrifice in NN or MST preservation. [ABSTRACT FROM PUBLISHER]

Published
2014
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