Self-organising Coordination Regions: A Pattern for Edge Computing

Casadei, Roberto; Pianini, Danilo; Viroli, Mirko; Natali, Antônio José

doi:10.1007/978-3-030-22397-7_11

Cited by 26 publications

(24 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Notice that an aggregate MAS can be collectively autonomous even if its overall behavior is highly determined by the deliberation of few individuals-if those individuals have been delegated for decision-making by the collective. Consider the Self-organising Coordination Regions (SCR) pattern [44], which is also exploited in Section 4; a general encoding in ScaFi is as follows:…”

Section: Collective Autonomy In Aggregate Computingmentioning

confidence: 99%

See 1 more Smart Citation

A Programming Approach to Collective Autonomy

Casadei

Aguzzi

Viroli

2021

JSAN

Self Cite

View full text Add to dashboard Cite

Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further opportunity lies in the collaboration of multiple agents or robots. Emerging macro-paradigms provide an approach to programming whole collectives towards global goals. Aggregate computing is one such paradigm, formally grounded in a calculus of computational fields enabling functional composition of collective behaviours that could be proved, under certain technical conditions, to be self-stabilising. In this work, we address the concept of collective autonomy, i.e., the form of autonomy that applies at the level of a group of individuals. As a contribution, we define an agent control architecture for aggregate multi-agent systems, discuss how the aggregate computing framework relates to both individual and collective autonomy, and show how it can be used to program collective autonomous behaviour. We exemplify the concepts through a simulated case study, and outline a research roadmap towards reliable aggregate autonomy.

show abstract

Section: Collective Autonomy In Aggregate Computingmentioning

confidence: 99%

“…An animal in danger needs a variable number of healers near to him to be rescued. The program follows the Self-organising Coordination Regions (SCR) pattern [44]:…”

Section: Experiments Setupmentioning

confidence: 99%

A Programming Approach to Collective Autonomy

Casadei

Aguzzi

Viroli

2021

JSAN

Self Cite

View full text Add to dashboard Cite

show abstract

“…1: we would like to update the crowd steering field only when there is a noticeable change in the perceived density of the surroundings. To do so, we first write a Protelis program leveraging the SCR pattern [8] to partition space in regions 300 meters wide and compute the average crowd density within them. Functions S (network partitioning at desired distance), summarize (aggregation of data over a spanning tree and partitionwide broadcast of the result), and distanceTo (computation of distance) come from the Protelis-lang library shipped with Protelis [11].…”

Section: Examplesmentioning

confidence: 99%

Time-Fluid Field-Based Coordination

Pianini

Mariani

Viroli

et al. 2020

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Emerging application scenarios, such as cyber-physical systems (CPSs), the Internet of Things (IoT), and edge computing, call for coordination approaches addressing openness, self-adaptation, heterogeneity, and deployment agnosticism. Field-based coordination is one such approach, promoting the idea of programming system coordination declaratively from a global perspective, in terms of functional manipulation and evolution in "space and time" of distributed data structures, called fields. More specifically, regarding time, in field-based coordination it is assumed that local activities in each device, called computational rounds, are regulated by a fixed clock, typically, a fair and unsynchronized distributed scheduler. In this work, we challenge this assumption, and propose an alternative approach where the round execution scheduling is naturally programmed along with the usual coordination specification, namely, in terms of a field of causal relations dictating what is the notion of causality (why and when a round has to be locally scheduled) and how it should change across time and space. This abstraction over the traditional view on global time allows us to express what we call "time-fluid" coordination, where causality can be finely tuned to select the event triggers to react to, up to to achieve improved balance between performance (system reactivity) and cost (usage of computational resources). We propose an implementation in the aggregate computing framework, and evaluate via simulation on a case study.

show abstract

“…Recent works promoted an approach to engineer complex field-based coordination algorithms by combination of basic building blocks [30], capturing key mechanisms of self-organisation such as spreading (block "G"), collection (block "C"), time evolution (block "T"), leader election and partitioning (block "S"), measuring centrality [7] and so on. For instance, self-organising coordination regions can be developed by a S-G-C-G composition [17].…”

Section: Self-stabilising Building Blocksmentioning

confidence: 99%

“…On the other hand, in the specific context of field-based coordination and aggregate computing framework [14], these algorithms provide an implementation for the fundamental "C block" as advocated in [30], coupling that of "G block" as of [6], and together forming a set of combinators effectively supporting construction of higher-level, self-stabilising coordination strategies in mobile distributed systems, such as e.g. the SCR pattern proposed in [17].…”

Section: Introductionmentioning

confidence: 99%

Resilient Distributed Collection Through Information Speed Thresholds

Audrito

Bergamini

Damiani

et al. 2020

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

One of the key coordination problems in physically-deployed distributed systems, such as mobile robots, wireless sensor networks, and IoT systems in general, is to provide notions of "distributed sensing" achieved by the strict, continuous cooperation and interaction among individual devices. An archetypal operation of distributed sensing is data summarisation over a region of space, by which several higher-level problems can be addressed: counting items, measuring space, averaging environmental values, and so on. A typical coordination strategy to perform data summarisation in a peer-to-peer scenario, where devices can communicate only with a neighbourhood, is to progressively accumulate information towards one or more collector devices, though this typically exhibits problems of reactivity and fragility, especially in scenarios featuring high mobility. In this paper, we propose coordination strategies for data summarisation involving both idempotent and arithmetic aggregation operators, with the idea of controlling the minimum information propagation speed, so as to improve the reactivity to input changes. Given suitable assumptions on the network model, and under the restriction of no data loss, these algorithms achieve optimal reactivity. By empirical evaluation via simulation, accounting for various sources of volatility, and comparing to other existing implementations of data summarisation algorithms, we show that our algorithms are able to retain adequate accuracy even in high-variability scenarios where all other algorithms are significantly diverging from correct estimations.

show abstract

Self-organising Coordination Regions: A Pattern for Edge Computing

Cited by 26 publications

References 40 publications

A Programming Approach to Collective Autonomy

A Programming Approach to Collective Autonomy

Time-Fluid Field-Based Coordination

Resilient Distributed Collection Through Information Speed Thresholds

Contact Info

Product

Resources

About