ORCA-Lab

Self-adaptive systems dynamically modify their behavior such that they meet changing requirements in a changing environment while providing guarantees under uncertainty. Crucial application areas include self-management of power and performance in clouds, language runtimes and embedded systems.

Summary

The Oceania Researchers in Cloud and Adaptive-systems (ORCA) lab, which is also known as Ohu Rangahau Kapua Aunoa in Te Reo Māori, was formed in January 2019 at the Department of Computer Science, University of Waikato. Its mission is to facilitate excellent research in the fields of Self-Adaptive and Self-Organizing software systems focusing on Cloud, Language Runtime and Embedded Systems.

Self-Adaptive Software is an exciting new field merging ideas from traditional Software Engineering and Computer Systems, with Artificial Intelligence (AI), Machine Learning (ML), Control Theory, Data-Driven Control, Game Theory, Stochastic Processes etc. Its goal is to enable applications to satisfy dynamically changing requirements in a dynamically changing environment. Self-Organization studies how groups of potentially adaptive agents behave over time.

Email: orca-lab@waikato.ac.nz

Objectives

We are currently working on a number of projects in this field. In general, we aim in accomplishing the following:

  • Apply existing formalisms of continuous and discrete control-theory on a novel way on clouds, runtimes and embedded systems
  • Optimize existing and invent new control approaches, testing them on clouds, runtimes and embedded systems
  • Train highly qualified personnel in the field
  • Disseminate our research outcomes in a variety of forms

People

University of Waikato Academic Staff

  • Panos Patros (Head of ORCA lab)
  • Robi Malik
  • Michael Mayo
  • Abigail Koay
  • Eibe Frank
  • Vimal Kumar
  • Tony Smith

University of Waikato Research Staff

  • Aaron Zolnai-Lucas

University of Waikato Research Students

  • Martin van Zijl
  • Harry McCarthy
  • Neil Bradley
  • Stephen Burroughs
  • Rhys Compton
  • Christopher Symon
  • Elinor Tsen
  • Alex Lumsden
  • Joseph Hall

University of Waikato Interns

  • Rajneesh Kumar
  • Mahima Singh

University of New Brunswick

  • Kenneth B. Kent
  • Suprio Ray
  • Stephen McKay
  • Maria Patrou

Technical University of Munich

  • Vladimir Podolskiy
  • Michael Gerndt

University of Maryland, Baltimore County

  • Phil Feldman

ASRC Federal

  • Aaron Dant

Publications

  • Vladimir Podolskiy, Michael Mayo, Abigail Koay, Michael Gerndt and Panos Patros. “Maintaining SLOs of Cloud-native Applications via Self-Adaptive Resource Sharing.” To appear in the proceedings of the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2019), Umeå, Sweden on June 16 – 20, 2019.
  • Patros, Panagiotis, Kenneth B. Kent, and Michael Dawson. “Mitigating Garbage Collection Interference on Containerized Clouds.” 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO). IEEE, 2018.

Projects

  • Robust and Optimal Control of Cloud Resource Scaling
  • Self-Adaptive Benchmarking
  • Design- and Run-time Cloud-SLA Verification
  • Modeling Chaotic Systems
  • GC Interference Reduction for Clouds
  • Machine Learning for Optimization of the JVM
  • Benchmarking Parallel Execution of Legacy Programs
  • Self-Organized Decision-Consensus of Human-Agents
  • Self-Detection of Cloud Performance Interference