Using Signatures of Self-Organisation for Monitoring and Influencing Large Scale Autonomic Systems

Author(s):  
Martin Randles ◽  
A. Taleb-Bendiab ◽  
Philip Miseldine ◽  
David Lamb
Scientifica ◽  
2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Erin S. Gloag ◽  
Lynne Turnbull ◽  
Cynthia B. Whitchurch

The self-organisation of collective behaviours often manifests as dramatic patterns of emergent large-scale order. This is true for relatively “simple” entities such as microbial communities and robot “swarms,” through to more complex self-organised systems such as those displayed by social insects, migrating herds, and many human activities. The principle of stigmergy describes those self-organised phenomena that emerge as a consequence of indirect communication between individuals of the group through the generation of persistent cues in the environment. Interestingly, despite numerous examples of multicellular behaviours of bacteria, the principle of stigmergy has yet to become an accepted theoretical framework that describes how bacterial collectives self-organise. Here we review some examples of multicellular bacterial behaviours in the context of stigmergy with the aim of bringing this powerful and elegant self-organisation principle to the attention of the microbial research community.


2021 ◽  
Author(s):  
Romain Fiévet ◽  
Bettina Meyer ◽  
Jan Olaf Haerter

<p>Spontaneous aggregation of clouds is a puzzling phenomenon observed in field studies [Holloway et al. (2017)] and idealized simulations alike [Held et al. (1993), Bretherton et al. (2005)]. With its relevance to climate sensitivity and extreme events, aggregation continues to be heavily studied, [Wing et al., 2017 for a review], with radiative-convective feedbacks emerging as main drivers of simulated convective self-aggregation (CSA) [Mueller & Bony (2015)].</p><p>In state-of-the art cloud-resolving models, CSA finds itself consistently hampered by finer horizontal resolutions [Muller & Held (2012), Yanase et al. (2020)]. This feature was ascribed to the effect of cold pool (CP) gust fronts in opposing the positive moisture feedback underlying CSA [Jeevanjee & Romps (2013)]. In contrast, recent numerical experiments [Haerter et al. (2020)] with diurnally oscillating surface temperature highlights an orthogonal effect: stronger CPs, driven by small-scale density gradients, promote cloud field self-organization into mesoscale convective systems (MCS). Interestingly, this upscale growth, which we here term diurnal self-organisation (DSO), differs from classical CSA as it is driven by CPs rather than large-scale radiative imbalances. In stark contrast to CSA, strengthening CPs promotes this organization effect.</p><p>Hence, numerical simulations of CSA and DSO should go beyond the typical cloud-resolving paradigm and achieve cold pool-resolving capabilities. The current study systematically examines the impact of model resolution on CP effects. First, numerical convergence is probed in a 12km x 20km laterally periodic domain where a single CP propagates and self-collides at the domain's edges. As the spatial resolution is stepwise increased from 250 to 25m, it is shown that the initially coarsely resolved density current dissipates and collision and updraft effects are weak. As finer resolution is approached, we identify a cold pool resolving resolution D, which is deemed satisfactory for propagation and collision properties. Second, convergence for a (250km)2 domain under a diurnal radiative cycle is assessed at various spatial resolutions, including the scale D. This mesoscale configuration allows us to quantify the impact of resolution of cold pool dynamics on DSO.</p><p>Together, this work systematically lays out the numerical requirements to study mesoscale clustering by means of explicit numerical simulations.</p>


2021 ◽  
Vol 12 (1) ◽  
pp. 349
Author(s):  
Roberto Casadei ◽  
Danilo Pianini ◽  
Mirko Viroli ◽  
Danny Weyns

The engineering of large-scale cyber-physical systems (CPS) increasingly relies on principles from self-organisation and collective computing, enabling these systems to cooperate and adapt in dynamic environments. CPS engineering also often leverages digital twins that provide synchronised logical counterparts of physical entities. In contrast, sensor networks rely on the different but related concept of virtual device that provides an abstraction of a group of sensors. In this work, we study how such concepts can contribute to the engineering of self-organising CPSs. To that end, we analyse the concepts and devise modelling constructs, distinguishing between identity correspondence and execution relationships. Based on this analysis, we then contribute to the novel concept of “collective digital twin” (CDT) that captures the logical counterpart of a collection of physical devices. A CDT can also be “augmented” with purely virtual devices, which may be exploited to steer the self-organisation process of the CDT and its physical counterpart. We underpin the novel concept with experiments in the context of the pulverisation framework of aggregate computing, showing how augmented CDTs provide a holistic, modular, and cyber-physically integrated system view that can foster the engineering of self-organising CPSs.


2018 ◽  
Vol 161 ◽  
pp. 03024 ◽  
Author(s):  
Olga Melekhova ◽  
Jacques Malenfant ◽  
Roman Mescheriakov ◽  
Aleksandr Chueshev

In this paper, we address the large-scale coordination of decisions impacting the consumption of a common shared resource of limited capacity by managed elements. We propose a decentralised token-based scheme, where each token represents a share of the resource. Our token-based protocol is meant to provide statistical guarantees on the average total resource usage and the average lateness of node actions due to the coordination. Experiments with the coordination of 10.000 autonomic managers have shown very good results for large spectrum of parameter values and system’s regimes.


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