Essence: Pervasive Data Science & Distributed Computing

Pervasive Data Science & Distributed Computing

Essence Research Lab is affiliated with the Knowledge and Data Engineering Systems Group of the Research Section: Information, Data and Analysis (IDA), School of Computing Science. Essence brings together the fundamental research areas of Distributed Data Systems and Pervasive Data Science at the Edge.

Essence's strength lies in the spectrum of theoretical backgrounds and applications ranging from context-awareness and networked data systems, to distributed processing & machine learning at the Edge. Essence focuses on building innovative pervasive data management systems and applications. Essence undertakes research ubder the School's theme: Understandable Autonomous Systems.

Lab's members collaborate with the Inference, Dynamics and Interaction (IDI) as a source of Machine Learning expertise, the Networked Systems Research Laboratory (Netlab) as a source of Networking expertise, and the Intelligent Pervasive Systems (iPRISM) as a source of Intelligent Systems expertise.
Essence's Google Maps link

Research Areas

Essence in a Nutshell

  • Pervasive Data Science: large-scale inferential modeling and exploratory analytics; distributed and pervasive learning.

  • Distributed Data Systems: in-network contextual data processing; context-aware computing and data management.

  • Sequential Learning Systems: multi-armed bandit; sequential and on-line learning.

    • Projects

  • Pervasive Data Science at the Edge
  • Edge Computing Systems
    • Contextual data management; distributed decision making; adaptive information processing; optimal stopping theory. [Presentations & Tutorials]
  • Distributed Learning Systems

    • Check for Postgraduate Research & PhD Opportunities. Contact: Dr Christos (Chris) Anagnostopoulos

    NEWS



    • IEEEAccess

      Dr K Kolomvatsos is appointed as Associate Editor of the IEEE Access Journal

      [IEEE Access]
    • UoG

      Natascha's PhD Thesis is free online! 'Quality-Efficient Local Learning of Predictive Analytics at the Network Edge'. [Thesis Link]

    • UoG

      Ibrahim's PhD Thesis is free online! 'Computation offloading in mobile edge computing: an optimal stopping theory approach'. [Thesis Link]

    • IEEEAccess

      Dr C Anagnostopoulos is appointed as Associate Editor of the IEEE Access Journal

      [IEEE Access]
    • IEEE ICTAI 2021
      P Oikonomou, K Kolomvatsos, C Anagnostopoulos, N Tziritas, G Theodoropoulos, 'A Probabilistic Batch Oriented Proactive Workflow Management',

      33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

      [IEEE ICTAI 2021]
    • ACM ACML 2021
      S. P. Parambath, C. Anagnostopoulos, R. Murray-Smith, S. MacAvaney, E. Zervas, 'Max-Utility Based Arm Selection Strategy for Sequential Query Recommendations',

      13th Asian Conference on Machine Learning

      [ACM ACML 2021]
    • IEEE Access
      T. Anagnostopoulos, et al. (2021) 'Challenges and Solutions of Surveillance Systems in IoT-Enabled Smart Campus: A Survey', IEEE Access. [IEEE Access 2021]
    • EssenceTalkSeries

      Sham’s talk on Mon 28/07/21@13h00:

      'On-line Learning: Introduction to Multi-Armed Bandits'
    • IFIP

      F. Savva's paper TSMF: Network Latency Estimation Using Matrix Factorization and Time Series Forecasting published in Networking 2021 in YouTube [Video Link]

    • UoG

      PhD Viva Success: Ibrahim Alghamdi (2021) 'Computation Offloading in Mobile Edge Computing: An Optimal Stopping Theory Approach'. PhD Thesis Presentation, University of Glasgow. ' [LNK/PDF]

    • UoG

      PhD Viva Success: Natascha Harth (2021) 'Quality-Efficient Local Learning of Predictive Analytics at the Network Edge'. PhD Thesis Presentation, University of Glasgow. ' [LNK/PDF]

    • IFIP

      F. Savva, C. Anagnostopoulos, D. Pezaros'TSMF: Network Latency Estimation Using Matrix Factorization and Time Series Forecasting', IFIP Networking, June 21-24, 2021, AALTO UNIVERSITY, FINLAND(IFIP Networking 2021)

    • IFIP

      S. Madalena, A. Karanika, K. Kolomvatsos, C. Anagnostopoulos, G. Stamoulis'Intelligent Tasks Allocation at the Edge based on Machine Learning and Bio-Inspired Algorithms', Evolving Systems (2021), Springer

    • DaIS2021

      1st IEEE International Workshop on “Distributed and Intelligent Systems” (IEEE DaIS 2021)

      in conjunction with the 26th IEEE ISCC 2021, Athens, Greece, September 5, 2021
    • CDSR2021

      8th International Conference of Control, Dynamic Systems, and Robotics (CDSR'21)

      Keynote Talk: 'Pushing Intelligence at the Edge' C Anagnostopoulos; 23-25 May, 2021 @ Canada
    • FGCS

      Kolomvatsos, K., Anagnostopoulos, C. (2021)'Proactive, Uncertainty-Driven Queries Management at the Edge ', Elsevier, Future Generation Computer Systems (FGCS)

    • UoG

      PhD Thesis Document: F Savva (2021) 'Query-driven learning for automating exploratory analytics in large-scale data management systems. PhD thesis, University of Glasgow. ' [PhD Thesis LNK/PDF]

    • DS4CS

      2021 IEEE CSR Workshop on Data Science for Cyber Security (DS4CS)

      in conjunction with IEEE Cyber Security and Resilence [IEEE CSR 2021]
    • springer

      Advances in Integrations of Intelligent Methods book is online! [Springer]

      'Edge-Centric Queries Stream Management Based on an Ensemble Model' K. Kolomvatsos and C. Anagnostopoulos [Book Flyer]

    • ACM TOIT

      ACM Transactions on Internet Technology (ACM TOIT)

      • Panagidi, K., Anagnostopoulos, C. , Chalvatzaras, A. and Hadjietfthymiades, S. (2019) To transmit or not to transmit: controlling the communications in the mobile IoT domain. ACM Transactions on Internet Technology (TOITs)

    • SoCS

      We are recruiting!

        Permanent faculty openings (Lecturer, Senior Lecturer, Reader) at Glasgow's School of Computing Science: Advanced networking; Cyber Security; FinTech; Trustworthy Autonomous Systems

      • Deadline: 08.01.2020

    • SoCS

      IEEE WCCI/ECCI 2020

        Our First International Workshop on Edge Computing & Computational Intelligence (ECCI 2020) is held in conjunction with the IEEE WCCI 2020, 19 - 24 July 2020, Glasgow, UK

    • SoCS

      Recruiting: Research Associate/Fellow!

        EPSRC-funded Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics (Closes: 6th February 2020)

    • EU MSCA 2019

      European Research Council MSCA Meeting

      Join our talk in ERC/MSCA Brussels 17-18, June 2019: 'AI in Europe'.

      • Kolomvatsos, K., Anagnostopoulos, C., INNOVATE [PDF]

    • ACM SIGMOD 2019

      2019 ACM SIGMOD/POD; Amsterdam, NL

      Poster presentation at ACM SIGMOD 2019.

      • F. Savva Query-Driven Learning for Next Generation Predictive Modelling and Analytics [PDF]

    • SICSA PhD Conference 2019

      SICSA PhD Conference 2019

      Poster presentation at SICSA PhD Conference 2019, University of Stirling, 18-19 June 2019.

      • I. Alghamdi, C. Anagnostopoulos, D. Pezaros. Time-Optimized Task Offloading Decision Making in Mobile Edge Computing

    • Grenoble INP Ensimag

      Internship: Grenoble INP Ensimag

      We welcome Mr V Orru from U Grenoble Ensimag in Essence!

      • Internship Research Topic:Application of Optimal Stopping Time in Large-scale Data Streams

    • IEEE ISCC 2019

      2 x IEEE ISCC 2019 Papers

      Join our paper presentations at IEEE ISCC 2019 Conference, Barcelona, Spain 2019.

      • Sagkriotis, S., Anagnostopoulos, C., Pezaros, D. Energy Usage Profiling for Virtualized Single Board Computer Clusters.

      • Sagkriotis, S., Kolomvatsos, K., Anagnostopoulos, C., Pezaros, D., Hadjiefthymiades, S. Knowledge-centric Analytics Queries Allocation in Edge Computing Environments.

    • IEEE ISPDC 2019

      IEEE ISPDC 2019 Paper

      Join our paper presentations at IEEE ISPDC 2019 Conference, Amsterdam, 2019 (18th International Symposium on Parallel and Distributed Computing).

      • E. Aleksandrova, C. Anagnostopoulos, K. Kolomvatsos, Machine Learning Model Updates in Edge Computing: An Optimal Stopping Theory Approach Funded by: H2020/INNOVATE.

    • IEEE WD 2019

      IEEE WD 2019 Best Paper Runner Up Award

      In recognition of the technical merit and significance of our paper: Alghamdi, I., Anagnostopoulos, C., Pezaros, D., 'Time-optimized Task Offloading Decision Making in Mobile Edge Computing' @ 11th IEEE Wireless Days 2019, Manchester.

    • MobiUK 2019

      2nd MobiUK 2019

      We are presenting: Alghamdi, I., Anagnostopoulos, C., Pezaros, D., 'Time-optimized Task Offloading Decision Making in Mobile Edge Computing' @2nd UK Mobile, Wearable and Ubiquitous Systems Research Symposium 1st-2nd July 2019, Dept of Computer Science, University of Oxford, UK.

    • INFOCOM 2018

      IEEE INFOCOM

      Join our paper presentation at IEEE INFOCOM 2018 Conference, Honolulu, HI, USA.

      • R. Cziva, C. Anagnostopoulos, D. Pezaros 'Dynamic, Latency-Optimal vNF Placement at the Network Edge'.EPSRC,EU/COST;EU/GNFUV [paper]

    • Wirelss Days 2019

      2 x IEEE WD'19 Papers

      Join our paper presentations at IEEE WD'19 Conference, Manchester, UK, 24-24 April 2019.

      • Alghamdi, I., Anagnostopoulos, C., Pezaros, D. 'Time-Optimized Task Offloading Decision Making in Mobile Edge Computing'.

      • Nikolaou, S., Anagnostopoulos, C., Pezaros, D. In-network Predictive Analytics in Edge Computing.

    • Paper

      Journal article in J. Parallel and Distirbuted Computing

      Kolomvatsos, K. An efficient scheme for applying software updates in pervasive computing applications. Funded by: H2020/INNOVATE.

    • Paper

      Tutorial: K Aleksandrova; Title: Statistical Models Update in Edge Computing using Optimal Stopping Theory & Concept Drift

      Essence Research Group Tutorial [12th April 2019@SoCS/SAWB 303]



    • IEEE BigData 2018

      2 x IEEE BigData 2018 Papers

      Join our paper presentations at IEEE BigData 2018 Conference, Seattle, US; Dec 10-13, 2018. Submissions: 1100 papers; Acceptance rate 18%.

      • Cahsai, A. S., Anagnostopoulos, C. , Ntarmos, N. and Triantafillou, P. Revisiting Exact kNN Query Processing with Probabilistic Data Space Transformations.

      • Savva, F. , Anagnostopoulos, C. and Triantafillou, P. Explaining Aggregates for Exploratory Analytics.

    • Best Student Paper Award

      Best Student Paper Award @ IEEE BigData 2018

      Awarded Paper: Cahsai, A. S., Anagnostopoulos, C. , Ntarmos, N. and Triantafillou, P. Revisiting Exact kNN Query Processing with Probabilistic Data Space Transformations.

    • ACM SIGMOD 2019

      ACM SIGMOD SRC 2019 Award

      Awarded Paper: Savva, F. Query-Driven Learning for Next Generation Predictive Modeling & Analytics at SIGMOD 2019 ACM Student Research Competition (SRC) sponsored by Microsoft.

    • Paper

      Journal Article in J Data Science & Analytics

      Anagnostopoulos, C. and Triantafillou, P. Large-scale predictive modelling & analytics through regression queries in data management systems. Funded by: H2020/GNFUV.



    • IEEE WiMob 2018

      IEEE WiMob 2018

      Join our paper presentation at IEEE WiMob 2018 Conference, Cyprus, 2018.

      • Panagidi, K., Galanis, I., Anagnostopoulos, C., Hadjiefthymiades, S. Time-Optimized Contextual Information Flow on Unmanned Vehicles.; EU/RAWFIE;EU/GNFUV

    • IEEE ICTAI 2018

      Join our paper presentation at IEEE ICTAI 2018 Conference, Greece, 2018.

      • K. kolomvatsos, C. Anagnostopoulos An Edge-Centric Ensemble Scheme for Queries Assignment.; EU/INNOVATE

    • IEEE EDGE 2018

      Join our paper presentation at IEEE EDGE 2018 Conference, CA, USA, 2018.

      • N. Harth, C. Anagnostopoulos Edge-centric Efficient Regression Analytics.; EU/GNFUV

    • IEEE ICC 2018

      Join our paper presentation at IEEE ICC 2018 Conference, Kansas City, MO, USA, 2018.

      • A. Ali, C. Anagnostopoulos. D. Pezaros On the Optimality of Virtualized Security Function Placement in Multi-Tenant Data Centers .; EPSRC; EU/COST; EU/GNFUV



    • Journal article in Wireless Networks; H2020/RAWFIE

      T. Kontos, C. Anagnostopoulos, E. Zervas, S. Hadjiefthymiades, 'Adaptive epidemic dissemination as a finite-horizon optimal stopping problem'. [paper]

    • Journal article in Computer Communications; H2020/RAWFIE

      K.Panagidi, C.Anagnostopoulos, S.Hadjiefthymiades'Optimal Grouping-of-Pictures in IoT video streams'. [paper]

    • Journal article in Applied Intelligence; H2020/GNFUV

      C. Anagnostopoulos, K. Kolomvatsos, 'Predictive intelligence to the edge through approximate collaborative context reasoning'. [paper]

    • Journal article in Applied Intelligence; H2020/GNFUV

      C. Anagnostopoulos, F. Savva, P. Triantafillou, Scalable aggregation predictive analytics: A query-driven machine learning approach. [paper]