Essence: Pervasive & Distributed Intelligence

Pervasive & Distributed Intelligence

The Pervasive & Distributed Intelligence (Essence) Research Lab is affiliated with the Research Section Information, Data and Analysis (IDA) in the School of Computing Science. The lab brings together the fundamental research areas: (i) Predictive Computing, (ii) Network-centric Information Systems, and (iii) Distributed Intelligence.

The lab's strength lies in the spectrum of theoretical backgrounds and applications ranging from Context-awareness, Stochastic Optimization, Intelligent Systems, Distributed Statistical Learning to Mobile and Wireless Networking. Essence focuses on building innovative context-aware networked data systems and applications. Essence undertake research ubder the School's themes: Autonomous Systems and Data Science.

The Essence lab's members collaborate with the Inference, Dynamics and Interaction (IDI) group led by Prof Murray-Smith (IDA Section Head) as a source of Machine Learning expertise, and with the Networked Systems Research Laboratory (Netlab) group ley by Prof Pezaros (Glasgow Systems Section Head) as a source of Networking expertise.


Note: The Essence's logo is a regular dodecahedron, i.e., a polyhedron with twelve flat faces (Platonic solid), whose coordinates derive from the multiplicative inverse of Pythagora's golden ratio.

Research Areas & Outcome

Essence in a Nutshell

  • Network-centric Information Systems: in-network contextual data processing from information captured by wireless/mobile sensor networks and resource-constrained networks.

  • Predictive Computing: large-scale inferential analytics and predictive intelligence at the network edge.

  • Distributed Intelligence: distributed context-/situation-aware computing adopting real-time stochastic optimization.

    • Ongoing Projects

  • Predict the Answer: Large-scale Data-less Computing
  • Data Relevance: Thinning the Big Data
  • Edge Computing: Optimal Task Offload & Allocation
  • Edge-centric Analytics: Time-optimized Statistical Modelling
  • Bio-inspired Predictive Analytics: Swarm Intelligence in Large-scale Regression
  • Intelligent, Quelity-aware Data Partitioning in Edge Computing Environments

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

    NEWS



    • 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

    • 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]