Karl Aberer

École Polytechnique Fédérale de Lausanne

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Manfred Hauswirth

Technische Universität Berlin

Philippe Cudré-Mauroux

University of Fribourg

Quoc Viet Hung Nguyen

Griffith University

Anwitaman Datta

Nanyang Technological University

Thanasis G. Papaioannou

Athens University of Economics and Business

Rémi Lebret

École Polytechnique Fédérale de Lausanne

Zoran Despotovic

Huawei Technologies (Germany)

Ivana Podnar Žarko

University of Zagreb

Tri Kurniawan Wijaya

Institut Seni Indonesia Yogyakarta

Matthias Weidlich

Humboldt-Universität zu Berlin

Cooperative Institutions

École Polytechnique Fédérale de Lausanne

186

Laboratoire d'Informatique Fondamentale de Lille

ETH Zurich

École Normale Supérieure - PSL

IBM (United States)

École Polytechnique

Georgia Institute of Technology

University of Lausanne

University of Michigan–Ann Arbor

Delft University of Technology

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More on Castor : the Scalable Secure Routing Protocol for Ad-hoc Networks

Wojciech Galuba Panos Papadimitratos Marcin Poturalski Karl Aberer Zoran Despotovic

Wireless ad hoc networks are inherently vulnerable,as any node can disrupt the communication of potentially anyother node in the network. Many solutions to this problem havebeen proposed. In this paper, we take a fresh and comprehen-sive approach, simultaneously addressing three aspects: security,scalability and adaptability to changing network conditions. Ourcommunication protocol, Castor, occupies a unique point in thedesign space: it does not use any control messages except simplepacket acknowledgements, and each node makes routing decisionslocally and independently of other nodes without exchangingrouting state with them. This novel design makes Castor resilientto a wide range of attacks and allows it to scale to large networksizes and to remain efficient under high mobility. We compareCastor against four representative protocols from the literature.Our protocol achieves up to two times higher packet deliveryrates, particularly in large and highly volatile networks, incursno or only limited additional overhead and it is able to survivemore severe attacks and recovers from them faster.

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Citations (2)

Answer validation for generic crowdsourcing tasks with minimal efforts

The VLDB Journal (2017)

Quoc Viet Hung Nguyen Chi Thang Duong Thành Tâm Nguyên Matthias Weidlich Karl Aberer

Crowdsourcing

Relevance

10.1007/s00778-017-0484-3

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Citations (17)

Requirements for workflow modeling in P2P - workflows derived from collaboration establishment

Proceedings. 15th International Workshop on Database and Expert Systems Applications, 2004. (2004)

Andreas Wombacher Karl Aberer

Web services advocate loosely coupled systems, although current applications are limited to centrally controlled structures. The reason for this limitation is the lack of a method for deciding collaboration consistency, that is deadlock freeness and boundedness, in a decentralized way. In particular, an intuitive approach classifies collaborations incorrectly being inconsistent due to the loss of information introduced by the decentralization. In this paper we identify loss of message ordering and message parameter value constraints caused by the decentralization to be the reasons for incorrect decision results. The proposed approach to overcome this issue is to explicate these constraints, which cannot represent in common workflow models.

10.1109/dexa.2004.1333613

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Citations (6)

The Semantic Web : 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007 : Proceedings

Springer eBooks (2007)

Karl Aberer

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From scattered sources to comprehensive technology landscape : A recommendation-based retrieval approach

World Patent Information (2023)

Chi Thang Duong Dimitri Perica David Ljiljana Dolamic Alain Mermoud Vincent Lenders

Mapping the technology landscape is crucial for market actors to take informed investment decisions. However, given the large amount of data on the Web and its subsequent information overload, manually retrieving information is a seemingly ineffective and incomplete approach. In this work, we propose an end-to-end recommendation based retrieval approach to support automatic retrieval of technologies and their associated companies from raw Web data. This is a two-task setup involving (i) technology classification of entities extracted from company corpus, and (ii) technology and company retrieval based on classified technologies. Our proposed framework approaches the first task by leveraging DistilBERT which is a state-of-the-art language model. For the retrieval task, we introduce a recommendation-based retrieval technique to simultaneously support retrieving related companies, technologies related to a specific company and companies relevant to a technology. To evaluate these tasks, we also construct a data set that includes company documents and entities extracted from these documents together with company categories and technology labels. Experiments show that our approach is able to return 4 times more relevant companies while outperforming traditional retrieval baseline in retrieving technologies.

Baseline (sea)

Information Overload

10.1016/j.wpi.2023.102198

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Citations (3)

ALVIS peers

Toan Luu Fabius Klemm Ivana Podnar Žarko Martin Rajman Karl Aberer

We present Alvis peers, a full-text P2P retrieval engine designed to offer retrieval performance comparable to centralized solutions while scaling to a very large number of peers. It is the result of our research efforts within the project Alvis1 European FP 6 STREP project ALVIS, http://www.alvis.info/ that aims at building a truly-distributed semantic search engine. To cope with problem of unscalable bandwidth consumption in the P2P network, the engine implements a novel retrieval model that indexes highly-discriminative keys (HDKs)---terms and term sets appearing in a limited number of collection documents. Our prototype is a fully-functional retrieval engine built over a structured P2P network. It includes a component for HDK based indexing and retrieval, and a distributed content-based ranking module. Such an integrated system represents a substantial contribution to the design and development of realistic P2P retrieval systems.

Discriminative model

10.1145/1183579.1183588

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Citations (40)

ACM/Springer Mobile Networks and Applications (MONET) Special Issue on “Collaborative Computing: Networking, Applications and Worksharing”

Mobile Networks and Applications (2012)

Songqing Chen Le Gruenwald James Joshi Karl Aberer

10.1007/s11036-012-0369-z

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

Lecture notes in computer science (2015)

John Soldatos Nikos Kefalakis Manfred Hauswirth Martín Serrano Jean-Paul Calbimonte

10.1007/978-3-319-16546-2_3

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Citations (264)

Enabling Query Technologies for the Semantic Sensor Web

International Journal on Semantic Web and Information Systems (2012)

Jean-Paul Calbimonte Hoyoung Jeung Óscar Corcho Karl Aberer

Sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this data, for other purposes than those for which they were originally set up. The authors propose an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. In this article, the authors describe the theoretical foundations and technologies that enable exposing semantically enriched sensor metadata, and querying sensor observations through SPARQL extensions, using query rewriting and data translation techniques according to mapping languages, and managing both pull and push delivery modes.

10.4018/jswis.2012010103

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Citations (142)

Online unsupervised state recognition in sensor data

Julien Eberle Tri Kurniawan Wijaya Karl Aberer

Smart sensors, such as smart meters or smart phones, are nowadays ubiquitous. To be "smart", however, they need to process their input data with limited storage and computational resources. In this paper, we convert the stream of sensor data into a stream of symbols, and further, to higher level symbols in such a way that common analytical tasks such as anomaly detection, forecasting or state recognition, can still be carried out on the transformed data with almost no loss of accuracy, and using far fewer resources. We identify states of a monitored system and convert them into symbols (thus, reducing data size), while keeping "interesting" events, such as anomalies or transition between states, as it is. Our algorithm is able to find states of various length in an online and unsupervised way, which is crucial since behavior of the system is not known beforehand. We show the effectiveness of our approach using real-world datasets and various application scenarios.

Streaming Data

Smart environment

10.1109/percom.2015.7146506

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Citations (7)