Towards evolution-based autonomy in large-scale systems

Damien Anderson, Paul Harvey, Yusaku Kaneta, Petros Papadopoulos, Philip Rodgers, Marc Roper

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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To achieve truly autonomous behaviour systems need to adapt to not only previously unseen circumstances but also previously unimagined ones. A hierarchical evolutionary system is proposed which is capable of displaying the emergent behaviour necessary to achieve this goal. This paper reports on the practical challenges encountered in implementing this proposed approach in a large-scale open-source system. In "Evolutionary Autonomous Networks"[3], Harvey et al. present their vision for an autonomous network utilising online evolution to achieve guided emergent behaviour. Their approach presents a radical strategy to improve a network's ability to cope with uncertainty and change. The aim of this paper is to present the initial steps we have taken towards realising this vision by examining how evolutionary-based autonomy may be introduced into an example large-scale system-a content delivery network (CDN). This goal is not without its challenges as there are significant hurdles imposed by the design and implementation of the CDN which must be overcome.

Original languageEnglish
Title of host publicationGECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference
Place of PublicationNew York
Number of pages2
ISBN (Electronic)9781450392686
Publication statusPublished - 9 Jul 2022
EventGECCO 2022: The Genetic and Evolutionary Computation Conference - Renaissance Boston Waterfront Hotel, Boston, United States
Duration: 9 Jul 202213 Jul 2022

Publication series

NameGECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference


ConferenceGECCO 2022
Country/TerritoryUnited States
Internet address


  • Evolutionary Autonomous Networks
  • content delivery networks
  • CDN
  • emergent behaviour


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