Hans-Arno Jacobsen

Professor

Department
Electrical and Computer Engineering
E-mail
jacobsen AT eecg DOT utoronto
Personal Home Page
http://www.eecg.utoronto.ca/~jacobsen
Biography
Hans-Arno Jacobsen holds the Bell University Laboratories Chair in Software, and he is a faculty member in the Department of Electrical and Computer Engineering and the Department of Computer Science at the University of Toronto, where he leads the Middleware Systems Research Group. His principal areas of research include the design and the development of middleware systems, distributed systems, and information systems. Arno's current research focuses on publish/subscribe, content-based routing, event processing, and aspect-orientation.

Arno received his Ph.D. degree from Humboldt University, Berlin in 1999 and his M.A.Sc. degree from the University of Karlsruhe, Germany in 1994. Between 1992 and 1998 Arno engaged in pre-doctoral research activities working at various research laboratories, world-wide. including LIFIA in Grenoble, France, ICSI in Berkeley, U.S., and LBNL in Berkeley, U.S. After completing his doctorate from 1998 to 1999, Arno engaged in post-doctoral research at INRIA in Rocquencourt, France, before joining the University of Toronto in 2001.

Arno has served as program committee member of various international conferences, including ICDCS, ICDE, Middleware, SIGMOD, OOPSLA and VLDB. He was the Program Chair of the 5th International Middleware Conference and the General Chair of the Inaugural International Conference on Distributed Event-Based Systems 2007. He is among the initiators of the DEBS conference series and the Event-based.org research portal.
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Publications
  • PS-Tree-Based Efficient Boolean Expression Matching for High-Dimensional and Dense Workloads.
    Shuping Ji and Hans-Arno Jacobsen.
    MSRG, November 2018.
    Technical Report: extended version PVLDB, 2018..
    Tags: publish/subscribe, matching, content-based publish/subscribe
  • Multi-client Transactions in Distributed Publish/Subscribe Systems.
    Martin Jergler, Kaiwen Zhang, and Hans-Arno Jacobsen.
    In ICDCS, 2018.
    Acceptance rate: 20%.
    Tags: publish/subscribe
  • EVA: Fair and Auditable Electric Vehicle Charging Service using Blockchain.
    Jelena Pacic, José Rivera, Kaiwen Zhang, and Hans-Arno Jacobsen.
    In DEBS, 2018.
    Tags: blockchains
  • Towards Dependable, Scalable, and Pervasive Distributed Ledgers with Blockchains.
    Kaiwen Zhang and Hans-Arno Jacobsen.
    In ICDCS, 2018.
    Tags: blockchains
  • Towards Dependable, Scalable, and Pervasive Distributed Ledgers with Blockchains.
    Kaiwen Zhang and Hans-Arno Jacobsen.
    University of Toronto, 03 2018.
    Tags: blockchains, bitcoin, distributed ledgers, dlt, ethereum, hyperledger
  • VIBES: Fast Blockchain Simulations for Large-scale Peer-to-Peer Networks.
    Lyubomir Stoykov, Kaiwen Zhang, and Hans-Arno Jacobsen.
    In Middleware Demos, 2017.
    Tags: bitcoin, blockchains, simulation
  • Combat State-Aware Interest Management for Online Games.
    Jing-Yi Wang, Kaiwen Zhang, and Hans-Arno Jacobsen.
    In Middleware Demos, 2017.
    Tags: online games, publish/subscribe, interest management
  • HyperPubSub: a Decentralized, Permissioned, Publish/Subscribe Service using Blockchains.
    Nejc Zupan, Kaiwen Zhang, and Hans-Arno Jacobsen.
    In Middleware Demos, 2017.
    Tags: hyperledger, kafka, publish/subscribe, blockchains
  • Multi-client Transactions in Distributed Publish/Subscribe Systems.
    Martin Jergler, Kaiwen Zhang, and Hans-Arno Jacobsen.
    TU-Munich, 2017.
    Tags: publish/subscribe, transactions, workflow management
  • Efficient Covering for Top-k Filtering in Content-Based Publish/Subscribe Systems.
    Kaiwen Zhang, Mohammad Sadoghi, Vinod Muthusamy, and Hans-Arno Jacobsen.
    In Middleware, 2017.
    Acceptance rate: 24.0%.
    Tags: publish/subscribe, top-k filtering
  • PopSub: Improving Resource Utilization in Distributed Content-based Publish/Subscribe Systems.
    Pooya Salehi, Kaiwen Zhang, and Hans-Arno Jacobsen.
    In DEBS, 2017.
    Acceptance rate: 23.0%.
    Tags: publish/subscribe, content-based, gossiping
  • + more