Embedded Social Insect-Inspired Intelligence Networks for System-level Runtime Management

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


Large-scale distributed computing architectures
such as, e.g. systems on chip or many-core devices, offer advantages
over monolithic or centralised single-core systems in
terms of speed, power/thermal performance and fault tolerance.
However, these are not implicit properties of such systems and
runtime management at software or hardware level is required
to unlock these features. Biological systems naturally present
such properties and are also adaptive and scalable. To consider
how these can be similarly achieved in hardware may be
beneficial. We present Social Insect behaviours as a suitable
model for enabling autonomous runtime management (RTM)
in many-core architectures. The emergent properties sought
to establish are self-organisation of task mapping and systemlevel
fault tolerance. For example, large social insect colonies
accomplish a wide range of tasks to build and maintain the
colony. Many thousands of individuals, each possessing relatively
little intelligence, contribute without any centralised control.
Hence, it would seem that social insects have evolved a scalable
approach to task allocation, load balancing and robustness that
can be applied to large many-core computing systems. Based on
this, a self-optimising and adaptive, yet fundamentally scalable,
design approach for many-core systems based on the emergent
behaviours of social-insect colonies are developed. Experiments
capture decision-making processes of each colony member to
exhibit such high-level behaviours and embed these decision
engines within the routers of the many-core system.
Original languageEnglish
Title of host publicationDesign, Automation and Test in Europe Conference
Subtitle of host publicationDATE2020
Place of PublicationGrenoble, France
Publication statusPublished - 9 Mar 2020


  • bio-inspired hardware, fault tolerance, social insects, adaptive system, many-core, runtime management

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