This is the presentation introducing the 6th eCAS workshop on Engineering Collective Adaptive Systems. It recaps its scope, provides data regarding this edition, provides an overview of the program and related initiatives.
Augmented Collective Digital Twins for Self-Organising Cyber-Physical SystemsRoberto Casadei
Context. Self-organising and collective computing
approaches are increasingly applied to large-scale cyber-physical
systems (CPS), enabling them to adapt and cooperate in dynamic
environments. Also, in CPS engineering, digital twins are often
leveraged to provide synchronised logical counterparts of physical
entities, whereas in sensor networks the different-but-related
concept of virtual device is used e.g. to abstract groups of sensors.
Vision. We envision the design concept of “augmented collective
digital twin” that captures digital twins at a collective level
extended with purely virtual devices. We argue that this concept
can foster the engineering of self-organising CPS by providing a
holistic, declarative, and integrated system view.
Method. From a review and proposed taxonomy of logical
devices comprehending both digital twins and virtual devices,
we reinterpret a meta-model for self-organising CPSs and discuss
how it can support augmented collective digital twins. We illus-
trate the approach in a crowd-aware navigation scenario, where
virtual devices are opportunistically integrated into the system
to enhance spatial coverage, improving navigation capabilities.
Conclusion. By integrating physical and virtual devices, the
novel notion of augmented collective digital twin paves the way
to self-improving system functionality and intelligent use of
resources in self-organising CPSs.
The next phase of Smart Network Convergence could be putting Deep Learning systems on the Internet. Deep Learning and Blockchain Technology might be combined in the smart networks of the future for automated identification (deep learning) and automated transaction (blockchain). Large scale future-class problems might be addressed with Blockchain Deep Learning nets as an advanced computational infrastructure, challenges such as million-member genome banks, energy storage markets, global financial risk assessment, real-time voting, and asteroid mining.
Blockchain Deep Learning nets and Smart Networks more generally are computing networks with intelligence built in such that identification and transfer is performed by the network itself through sophisticated protocols that automatically identify (deep learning), and validate, confirm, and route transactions (blockchain) within the network.
http://kkpradeeban.blogspot.com/2015/11/cassowary-middleware-platform-for.html
Abstract: Smart devices sense the environment through their sensors and leverage the contextual information derived from the sensor readings to satisfy system requirements such as energy and carbon efficiency and user preferences. Smart buildings compose of smart devices, and local sensors of the devices and device controllers in a coordinated network. Software-Defined Networking (SDN) offers a centralized view of the entire networking data plane elements to a logically centralized controller. While smart buildings and ubiquitous computing are heavily researched, later advancements in networking are not exploited in achieving tenant-aware smart buildings.
This paper describes the research for the design, prototype implementation, and preliminary assessments of Cassowary, a middleware platform for Context-Aware Smart Buildings with Software-Defined Sensor Networks. By extending SDN paradigm and leveraging the message oriented middleware protocols to seamlessly connect the smart devices of the buildings to the centralized SDN controller, Cassowary enables context-aware Software-Defined Smart Buildings.
Collective Abstractions and Platforms for Large-Scale Self-Adaptive IoTRoberto Casadei
On the way to the materialisation of the pervasive computing vision, the technological progress swelling from mobile computing and the Internet of Things (IoT) domain is already rich of missed opportunities. Firstly, coordinating large numbers of heterogeneous situated entities to achieve system-level goals in a resilient and self-adaptive way is complex and requires novel approaches to be seamlessly injected into mainstream distributed computing models. Secondly, achieving effective exploitation of computer resources is difficult, due to operational constraints resulting from current paradigms and uncomprehensive software infrastructures which hinder flexibility, adaptation, and smooth coordination of computational tasks execution. Indeed, building dynamic, context-oriented applications in small- or large-scale IoT with traditional abstractions is hard: even harder is to achieve opportunistic, QoS- and QoE-driven application task management across available hardware and networking infras- tructure. In this insight paper, we analyse by the collective adap- tation perspective the key directions of the impelling paradigm shift urged by forthcoming large-scale IoT scenarios. Specifically, we consider how collective abstractions and platforms can syner- gistically assist in such a transformation, by better capturing and enacting a notion of “collective service” as well as the dynamic, opportunistic, and context-driven traits of space-time-situated computations.
Augmented Collective Digital Twins for Self-Organising Cyber-Physical SystemsRoberto Casadei
Context. Self-organising and collective computing
approaches are increasingly applied to large-scale cyber-physical
systems (CPS), enabling them to adapt and cooperate in dynamic
environments. Also, in CPS engineering, digital twins are often
leveraged to provide synchronised logical counterparts of physical
entities, whereas in sensor networks the different-but-related
concept of virtual device is used e.g. to abstract groups of sensors.
Vision. We envision the design concept of “augmented collective
digital twin” that captures digital twins at a collective level
extended with purely virtual devices. We argue that this concept
can foster the engineering of self-organising CPS by providing a
holistic, declarative, and integrated system view.
Method. From a review and proposed taxonomy of logical
devices comprehending both digital twins and virtual devices,
we reinterpret a meta-model for self-organising CPSs and discuss
how it can support augmented collective digital twins. We illus-
trate the approach in a crowd-aware navigation scenario, where
virtual devices are opportunistically integrated into the system
to enhance spatial coverage, improving navigation capabilities.
Conclusion. By integrating physical and virtual devices, the
novel notion of augmented collective digital twin paves the way
to self-improving system functionality and intelligent use of
resources in self-organising CPSs.
The next phase of Smart Network Convergence could be putting Deep Learning systems on the Internet. Deep Learning and Blockchain Technology might be combined in the smart networks of the future for automated identification (deep learning) and automated transaction (blockchain). Large scale future-class problems might be addressed with Blockchain Deep Learning nets as an advanced computational infrastructure, challenges such as million-member genome banks, energy storage markets, global financial risk assessment, real-time voting, and asteroid mining.
Blockchain Deep Learning nets and Smart Networks more generally are computing networks with intelligence built in such that identification and transfer is performed by the network itself through sophisticated protocols that automatically identify (deep learning), and validate, confirm, and route transactions (blockchain) within the network.
http://kkpradeeban.blogspot.com/2015/11/cassowary-middleware-platform-for.html
Abstract: Smart devices sense the environment through their sensors and leverage the contextual information derived from the sensor readings to satisfy system requirements such as energy and carbon efficiency and user preferences. Smart buildings compose of smart devices, and local sensors of the devices and device controllers in a coordinated network. Software-Defined Networking (SDN) offers a centralized view of the entire networking data plane elements to a logically centralized controller. While smart buildings and ubiquitous computing are heavily researched, later advancements in networking are not exploited in achieving tenant-aware smart buildings.
This paper describes the research for the design, prototype implementation, and preliminary assessments of Cassowary, a middleware platform for Context-Aware Smart Buildings with Software-Defined Sensor Networks. By extending SDN paradigm and leveraging the message oriented middleware protocols to seamlessly connect the smart devices of the buildings to the centralized SDN controller, Cassowary enables context-aware Software-Defined Smart Buildings.
Collective Abstractions and Platforms for Large-Scale Self-Adaptive IoTRoberto Casadei
On the way to the materialisation of the pervasive computing vision, the technological progress swelling from mobile computing and the Internet of Things (IoT) domain is already rich of missed opportunities. Firstly, coordinating large numbers of heterogeneous situated entities to achieve system-level goals in a resilient and self-adaptive way is complex and requires novel approaches to be seamlessly injected into mainstream distributed computing models. Secondly, achieving effective exploitation of computer resources is difficult, due to operational constraints resulting from current paradigms and uncomprehensive software infrastructures which hinder flexibility, adaptation, and smooth coordination of computational tasks execution. Indeed, building dynamic, context-oriented applications in small- or large-scale IoT with traditional abstractions is hard: even harder is to achieve opportunistic, QoS- and QoE-driven application task management across available hardware and networking infras- tructure. In this insight paper, we analyse by the collective adap- tation perspective the key directions of the impelling paradigm shift urged by forthcoming large-scale IoT scenarios. Specifically, we consider how collective abstractions and platforms can syner- gistically assist in such a transformation, by better capturing and enacting a notion of “collective service” as well as the dynamic, opportunistic, and context-driven traits of space-time-situated computations.
Material of year-end seminar of Social Intelligence Research Team of artificial intelligence research center of National Institute of Advanced Industrial Science and Technology.
Technical Appraisal Tool, MICE - Acting on Change 2016PERICLES_FP7
This presentation was delivered by Jun Zhang (King’s College London), Patricia Falcao (Tate) and Maria Akritidou (DOTSOFT S.A.) at PERICLES final project conference 'Acting on Change: New Approaches and Future Practices in LTDP' (Wellcome Collection Conference Centre, London, 30 Nov -1 Dec 2016).
This 'PERICLES in practice' session aimed at demonstrating how risks to digital video artworks and archived space science experiments can be monitored, assessed and visualised.
The 'PERICLES in practice' sessions presented specific outcomes of the PERICLES project set in an example workflow, combining tools to accomplish a goal defined by practitioners and derived from real life challenges they experience in their field of work.
This lecture reviews methods that allow interpreting the outcomes of a deep convolutional neural network. It presents some of the techniques proposed in the literature.
In good olden days our predecessors have invented several ways of passing information in hidden form with other objects like papyrus scroll, cryptic etc. As generations crossed through earth's vein we are getting matured and invented several stenographic systems for message passing. The availability of internet in every corner of the universe forced the user of stenographic systems to invent and implement a better secured algorithm for encryption and decryption of text. Here framework will embed text string into digital colour images and the text that is embedded is perceptually invisible to Human Visual System (HVS). Many text stenographic systems are available that are passing the text with digital media as a form of message digest that can be hacked easily. Here this algorithm supplements the conventional algorithms. Instead of forming message digest first a 32-bit secret key will be provided by the encrypted and that is applied on the text with a hash function. On the other end if a snooper tries to perform the extraction of the text with a wrong secret key, he will not be succeeded. In the proposed framework the information of Red (R), Green (G) & Blue (B) values of the pixels of the host colour image are retrieved.
Prepared for the Geneva Centre for Security Policy (GCSP) Leadership in International Security Course (February 2021)
The International Security Implications of New Technologies
Panel: Autonomy & Control – Technological Surrogacy & Predictive Powers
Session 10 in module 3 from the Master in Computer Vision by UPC, UAB, UOC & UPF.
This lecture provides an overview of state of the art applications of convolutional neural networks to the problems in video processing: semantic recognition, optical flow estimation and object tracking.
Il deep learning ed una nuova generazione di AI - Simone ScardapaneData Driven Innovation
Il deep learning rappresenta una nuova famiglia di tecniche data-driven, che aprono nuovi orizzonti in quello che le macchine possono essere programmate a fare. In pochi anni abbiamo visto automobili che si guidano da sole, robot che imparano a muoversi, campioni di Go sconfitti, e molto altro ancora. Quali sono le sfide tecniche, sociali e scientifiche del prossimo futuro? E, soprattutto, queste tecnologie sono alla portata di tutti? In questo talk daremo una (brevissima) panoramica di queste questioni e delle loro possibili risposte.
Introduction to the 1st DISCOLI workshop on distributed collective intelligenceRoberto Casadei
The 1st DISCOLI workshop on DIStributed COLlective Intelligence is co-located with the 42nd IEEE International Conference on Distributed Computing Systems (ICDCS 2022) that will take place in Bologna, Italy, 10-13 July 2022.
Recent technological and scientific trends are promoting a vision where intelligence is more and more distributed and collective. Indeed, as computing and communication technologies are becoming increasingly pervasive, and complexity of systems is growing in terms of scale, heterogeneity, and interaction, hence the focus tends to shift from the intelligence of individual devices or agents to the collective intelligence (CI) emerging from a dynamic collection of diverse devices. Such intelligence would allow systems to address complex problems through proper coordination (e.g., cooperation or competition), to self-organise to promote functionality under changing environments, and to improve decision-making capabilities.
The workshop aims to provide a forum where researchers and practitioners can share and discuss fundamental concepts, models, and techniques for studying and implementing collectively intelligent distributed systems. Accordingly, it welcomes original research work providing ideas and technical contributions for promoting scientific discussion and practical adoption of CI mechanisms in engineered systems. As such, the workshop also welcomes cross-disciplinary contributions (e.g., extracting computational mechanisms from natural systems exhibiting forms of CI) and contributions from related research areas like coordination (the study of interaction), multi-agent systems (MAS), socio-technical systems, organisational paradigms, Wireless Sensor and Actuator Networks (WSANs), the Internet of Things (IoT), crowd computing, and swarm robotics.
The topics of interest include (but are not limited to) the following:
Algorithms for self-adaptive/self-organizing system behaviour
Algorithms of artificial collective intelligence (e.g., multi-agent reinforcement learning)
Techniques for task-specific collective intelligence
Extraction of collective knowledge in Internet of Things systems
Collaborations of humans and artificial agents in socio-technical systems
Formal models for computational collective intelligence
Design and verification of emergent properties in distributed systems
Coordination models and languages
Programming languages for distributed CI systems
Languages for multi-tier programming or macro-programming
CI for distributed wearable computing systems
Techniques for crowd computing systems and applications
Applications of distributed CI for smart environments (e.g., smart cities, smart buildings)
Tools for programming and simulation of multi-agent systems
Material of year-end seminar of Social Intelligence Research Team of artificial intelligence research center of National Institute of Advanced Industrial Science and Technology.
Technical Appraisal Tool, MICE - Acting on Change 2016PERICLES_FP7
This presentation was delivered by Jun Zhang (King’s College London), Patricia Falcao (Tate) and Maria Akritidou (DOTSOFT S.A.) at PERICLES final project conference 'Acting on Change: New Approaches and Future Practices in LTDP' (Wellcome Collection Conference Centre, London, 30 Nov -1 Dec 2016).
This 'PERICLES in practice' session aimed at demonstrating how risks to digital video artworks and archived space science experiments can be monitored, assessed and visualised.
The 'PERICLES in practice' sessions presented specific outcomes of the PERICLES project set in an example workflow, combining tools to accomplish a goal defined by practitioners and derived from real life challenges they experience in their field of work.
This lecture reviews methods that allow interpreting the outcomes of a deep convolutional neural network. It presents some of the techniques proposed in the literature.
In good olden days our predecessors have invented several ways of passing information in hidden form with other objects like papyrus scroll, cryptic etc. As generations crossed through earth's vein we are getting matured and invented several stenographic systems for message passing. The availability of internet in every corner of the universe forced the user of stenographic systems to invent and implement a better secured algorithm for encryption and decryption of text. Here framework will embed text string into digital colour images and the text that is embedded is perceptually invisible to Human Visual System (HVS). Many text stenographic systems are available that are passing the text with digital media as a form of message digest that can be hacked easily. Here this algorithm supplements the conventional algorithms. Instead of forming message digest first a 32-bit secret key will be provided by the encrypted and that is applied on the text with a hash function. On the other end if a snooper tries to perform the extraction of the text with a wrong secret key, he will not be succeeded. In the proposed framework the information of Red (R), Green (G) & Blue (B) values of the pixels of the host colour image are retrieved.
Prepared for the Geneva Centre for Security Policy (GCSP) Leadership in International Security Course (February 2021)
The International Security Implications of New Technologies
Panel: Autonomy & Control – Technological Surrogacy & Predictive Powers
Session 10 in module 3 from the Master in Computer Vision by UPC, UAB, UOC & UPF.
This lecture provides an overview of state of the art applications of convolutional neural networks to the problems in video processing: semantic recognition, optical flow estimation and object tracking.
Il deep learning ed una nuova generazione di AI - Simone ScardapaneData Driven Innovation
Il deep learning rappresenta una nuova famiglia di tecniche data-driven, che aprono nuovi orizzonti in quello che le macchine possono essere programmate a fare. In pochi anni abbiamo visto automobili che si guidano da sole, robot che imparano a muoversi, campioni di Go sconfitti, e molto altro ancora. Quali sono le sfide tecniche, sociali e scientifiche del prossimo futuro? E, soprattutto, queste tecnologie sono alla portata di tutti? In questo talk daremo una (brevissima) panoramica di queste questioni e delle loro possibili risposte.
Introduction to the 1st DISCOLI workshop on distributed collective intelligenceRoberto Casadei
The 1st DISCOLI workshop on DIStributed COLlective Intelligence is co-located with the 42nd IEEE International Conference on Distributed Computing Systems (ICDCS 2022) that will take place in Bologna, Italy, 10-13 July 2022.
Recent technological and scientific trends are promoting a vision where intelligence is more and more distributed and collective. Indeed, as computing and communication technologies are becoming increasingly pervasive, and complexity of systems is growing in terms of scale, heterogeneity, and interaction, hence the focus tends to shift from the intelligence of individual devices or agents to the collective intelligence (CI) emerging from a dynamic collection of diverse devices. Such intelligence would allow systems to address complex problems through proper coordination (e.g., cooperation or competition), to self-organise to promote functionality under changing environments, and to improve decision-making capabilities.
The workshop aims to provide a forum where researchers and practitioners can share and discuss fundamental concepts, models, and techniques for studying and implementing collectively intelligent distributed systems. Accordingly, it welcomes original research work providing ideas and technical contributions for promoting scientific discussion and practical adoption of CI mechanisms in engineered systems. As such, the workshop also welcomes cross-disciplinary contributions (e.g., extracting computational mechanisms from natural systems exhibiting forms of CI) and contributions from related research areas like coordination (the study of interaction), multi-agent systems (MAS), socio-technical systems, organisational paradigms, Wireless Sensor and Actuator Networks (WSANs), the Internet of Things (IoT), crowd computing, and swarm robotics.
The topics of interest include (but are not limited to) the following:
Algorithms for self-adaptive/self-organizing system behaviour
Algorithms of artificial collective intelligence (e.g., multi-agent reinforcement learning)
Techniques for task-specific collective intelligence
Extraction of collective knowledge in Internet of Things systems
Collaborations of humans and artificial agents in socio-technical systems
Formal models for computational collective intelligence
Design and verification of emergent properties in distributed systems
Coordination models and languages
Programming languages for distributed CI systems
Languages for multi-tier programming or macro-programming
CI for distributed wearable computing systems
Techniques for crowd computing systems and applications
Applications of distributed CI for smart environments (e.g., smart cities, smart buildings)
Tools for programming and simulation of multi-agent systems
Programming (and Learning) Self-Adaptive & Self-Organising Behaviour with Sca...Roberto Casadei
Large-scale and fully distributed cyber-physical sys-
tems (CPS), such as swarm robotics or IoT systems, pose
significant challenges for programming and design. These chal-
lenges include promoting the desired (emergent) collective and
self-organising behaviour, dealing with failures, enacting decen-
tralised coordination, and deploying efficient executions. Aggre-
gate computing is a promising approach that aims to simplify
the design of such systems by providing a high-level abstraction
for describing collective and self-organising behaviours. In this
tutorial, we introduce a toolchain that supports the development
of aggregate computing applications, based on ScaFi (a Scala-
based language and toolkit for aggregate computing) and Al-
chemist (a simulator for CPS scenarios). We will showcase the
toolchain by means of a series of examples, ranging from simple
collective behaviours to more complex self-adaptive and self-
organising ones. Finally, we provide several pointers to research
opportunities (e.g., related to learning collective behaviours
and adaptive large-scale deployments) and applications (e.g., in
swarm robotics, edge-cloud ecosystems, and more).
Invited talk at workshop "Exascale Computing in Astrophysics" held in Ascona, Switzerland, 8-13 September 2013.
http://www.itp.uzh.ch/exastro2013/Home.html
Recurrent Neural Networks (RNNs) represent the reference class of Deep Learning models for learning from sequential data. Despite the widespread success, a major downside of RNNs and commonly derived ‘gating’ variants (LSTM, GRU) is given by the high cost of the involved training algorithms. In this context, an increasingly popular alternative is the Reservoir Computing (RC) approach, which enables limiting the training algorithm to operate only on a restricted set of (output) parameters. RC is appealing for several reasons, including the amenability of being implemented in low-powerful edge devices, enabling adaptation and personalization in IoT and cyber-physical systems applications.
This webinar will introduce Reservoir Computing from scratch, covering all the fundamental design topics as well as good practices. It is targeted to both researchers and practitioners that are interested in setting up fastly-trained Deep Learning models for sequential data.
Collective Adaptive Systems as Coordination Media: The Case of Tuples in Spac...Roberto Casadei
Coordination is a fundamental problem in the
engineering of collective adaptive systems (CAS). Prominent
approaches in this context promote adaptivity and collective
behaviour by founding coordination on local, decentralised in-
teraction. This is usually enabled through abstractions such as
collective interfaces, neighbour-based interaction, and attribute-
based communication. Application designers, then, use such
coordination mechanisms to enact collective adaptive behaviour
in order to solve specific problems or provide specific services
while coping with dynamic environments. In this paper, we
consider the other way round: we argue that a CAS model can
be used to provide support for high-level coordination models,
simplifying their implementation and transferring to them the
self-* properties it emergently fosters. As a motivating example,
we consider the idea of supporting tuple-based coordination by
Linda primitives such that tuples and operations have a position
and extension in space and time. Then, we adopt an aggregate
perspective, by which space-time is logically represented by a
mobile ad-hoc network of devices, and show that coordination
primitives can be implemented as true collective adaptive pro-
cesses. We describe this model and a prototype implementation
in the ScaFi aggregate programming framework, which is rooted
in the so-called computational field paradigm.
Novel scenarios like IoT and smart cities promote
a vision of computational ecosystems whereby heterogeneous
collectives of humans, devices and computing infrastructure
interact to provide various services. There, autonomous agents
with different capabilities are expected to cooperate towards
global goals in dependable ways. This is challenging, as deployments are within unknown, changing and loosely connected environments characterized by lack of centralized control, where
components may come and go, or disruption may be caused by
failures. Key issues include (i) how to leverage, functionally and
non-functionally, forms of opportunistic computing and locality
that often underlie IoT scenarios; (ii) how to design and operate
large-scale, resilient ecosystems through suitable assumptions,
decentralized control, and adaptive mechanisms; and (iii) how
to capture and enact “global” behaviors and properties, when
the system consists of heterogeneous, autonomous entities. In
this paper, we propose a model for resilient, collaborative edge-
enabled IoT that leverages spatial locality, opportunistic agents,
and coordinator nodes at the edge. The engineering approach
is declarative and configurable, and works by dynamically
dividing the environment into collaboration areas coordinated
by edge devices. We provide an implementation as a collective, self-organizing workflow based on Aggregate Computing,
provide evaluation by means of simulation, and finally discuss
properties and general applicability of the approach.
Redes de sensores sem fio autonômicas: abordagens, aplicações e desafiosPET Computação
Este curso tem como principal objetivo apresentar aos ouvintes conceitos sobre redes de sensores sem fio (RSSF), protocolos de comunicação para RSSF e conceitos de computação autonômica. Além disso, aplicações focadas nas áreas de monitoramento ambiental, agricultura de precisão, segurança e defesa também serão apresentados.
Where are all the Semantic Web agents? There are billions of "machine readable" open facts on the Semantic Web, i.e. Linked Open Data (LOD), isn't that enough? It looks like it's not. We're still far from seeing Lucy's and Pete's agents brilliantly solving their tasks with the help of other Semantic Web agents they can trust (Tim Berners Lee et al., The Semantic Web, Scientific American (2001) ). Despite its technological impact on many applications and areas, the Semantic Web promised to cause a breakthrough that we didn't yet experience. One issue is that LOD ontologies are not as linked as they should be. Another issue is that formalising only semi-structured Web pages or databases is not enough for making them able to operate. They also need to reason with commonsense knowledge, the encoding of which is a long-standing challenge in Artificial Intelligence. A third consideration is that most existing commonsense knowledge bases lack formal semantics and situational constraints. In this talk I will advocate the role of the Semantic Web as a provider of a knowledge graph of commonsense to Artificial Intelligence, and discuss ways and obstacles towards the achievement of this goal.
eCAS 2021: Towards Pulverised Architectures for Collective Adaptive Systems t...Gianluca Aguzzi
Engineering large-scale Cyber-Physical Systems–like robot swarms, augmented crowds, and smart cities – is challenging, for many issues have to be addressed, including specifying their collective adaptive behaviour and managing the connection of the digital and physical parts. In particular, some approaches propose self-organising mechanisms to actually program global behaviour while fostering decentralised, asynchronous execution. However, most of these approaches couple behavioural specifications to specific network architectures (e.g.,peer-to-peer), and therefore do not promote flexible exploitation of the underlying infrastructure. Conversely, pulverisation is a recent approach that enables self-organising behaviour to be defined independently of the available infrastructure while retaining functional correctness. Currently, however, no tools are available to formally specify and verify concrete architectures for pulverised applications. Therefore, in this work we propose to combine pulverisation with multi-tier programming, a paradigm that supports the specification of the architecture of distributed systems in a single code base, and enables static checks for the correctness of actual deployments. The approach can be seamlessly implemented by combining the ScaFi aggregate computing tool-chain with the ScalaLoci multi-tier programming language, paving the path fora coherent support to the development of self-organising cyber-physical systems, addressing both functional (behaviour) and non-functional concerns (deployment) in a single code base and modular fashion.
Self-Organisation Programming: a Functional Reactive Macro Approach (FRASP) [...Roberto Casadei
Engineering self-organising systems – e.g., robot
swarms, collectives of wearables, or distributed infrastructures
– has been investigated and addressed through various kinds
of approaches: devising algorithms by taking inspiration from
nature, relying on design patterns, using learning to synthesise
behaviour from expectations of emergent behaviour, and exposing
key mechanisms and abstractions at the level of a programming
language. Focussing on the latter approach, most of the state-
of-the-art languages for self-organisation leverage a round-based
execution model, where devices repeatedly evaluate their context
and control program fully: this model is simple to reason about
but limited in terms of flexibility and fine-grained management
of sub-activities. By inspiration from the so-called functional
reactive paradigm, in this paper we propose a reactive self-
organisation programming approach that enables to fully decouple
the program logic from the scheduling of its sub-activities.
Specifically, we implement the idea through a functional reactive
implementation of aggregate programming in Scala, based on
the functional reactive library Sodium. The result is a functional
reactive self-organisation programming model, called FRASP,
that maintains the same expressiveness and benefits of aggregate
programming, while enabling significant improvements in terms
of scheduling controllability, flexibility in the sensing/actuation
model, and execution efficiency.
Programming Distributed Collective Processes for Dynamic Ensembles and Collec...Roberto Casadei
Recent trends like the Internet of Things (IoT) suggest a vi-
sion of dense and multi-scale deployments of computing devices in nearly
all kinds of environments. A prominent engineering challenge revolves
around programming the collective adaptive behaviour of such compu-
tational ecosystems. This requires abstractions able to capture concepts
like ensembles (dynamic groups of cooperating devices) and collective
tasks (joint activities carried out by ensembles). In this work, we con-
sider collections of devices interacting with neighbours and that execute
in nearly-synchronised sense–compute–interact rounds, where the com-
putation is given by a single control program. To support programming
whole computational collectives, we propose the abstraction of a dis-
tributed collective process (DCP), which can be used to define at once
the ensemble formation logic and its collective task. We implement the
abstraction in the eXchange Calculus (XC), a core language based on
neighbouring values (maps from neighbours to values) where state man-
agement and interaction is handled through a single primitive, exchange.
Then, we discuss the features of the abstraction, its suitability for differ-
ent kinds of distributed computing applications, and provide a proof-of-
concept implementation of a wave-like process propagation.
Towards Automated Engineering for Collective Adaptive Systems: Vision and Res...Roberto Casadei
The opportunities and challenges of recent and
forthcoming distributed computing scenarios have been promot-
ing research on languages and paradigms aimed at modelling the
macro/collective behaviour of systems as well as mechanisms to
endow them with self-* capabilities. One example is the aggregate
computing paradigm, which supports the development of self-
organising systems (e.g., robot swarms, computational ecosys-
tems, and crowd-based services) through various formalisms and
tools developed over a decade. However, very limited work has
been done by a methodological and automation perspective. In
this paper, we explore the issue of organising the development
process of aggregate computing systems. Accordingly, we outline
novel research directions that arise from careful analysis of
the peculiar issues in collective and self-organising systems, the
cornerstones of effective software engineering practices, and
recent scientific trends and insights.
Aggregate computing is a research topic that is addressed by multiple perspectives: computational models, programming languages, distributed adaptive algorithms, middleware architectures, formal analysis, tools.
Digital Twins, Virtual Devices, and Augmentations for Self-Organising Cyber-P...Roberto Casadei
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.
FScaFi: A Core Calculus for Collective Adaptive Systems ProgrammingRoberto Casadei
A recently proposed approach to the rigorous engineering of collective adaptive systems is the aggregate computing paradigm, which operationalises the idea of expressing collective adaptive behaviour by a global perspective as a functional composition of dynamic computational fields (i.e., structures mapping a collection of individual devices of a collective to computational values over time). In this paper, we present FScaFi, a core language that captures the essence of exploiting field computations in mainstream functional languages, and which is based on a semantic model for field computations leveraging the novel notion of “computation against a neighbour”. Such a construct models expressions whose evaluation depends on the same evaluation that occurred on a neighbour, thus abstracting communication actions and, crucially, enabling deep and straightforward integration in the Scala programming language, by the ScaFi incarnation. We cover syntax and informal semantics of FScaFi, provide examples of collective adaptive behaviour development in ScaFi, and delineate future work.
Tuple-Based Coordination in Large-Scale Situated SystemsRoberto Casadei
Space and time are key elements for many computer-based systems and often elevated to first-class abstractions. In tuple-based coordination, Linda primitives have been independently extended with space (with tuples and queries spanning spatial regions) or time information (mostly for tuple scoping). However, recent works in collective adaptive systems and aggregate computing show that space and time can naturally be considered as two intertwined facets of a common coordination abstraction for situated distributed systems. Accordingly, we introduce the Spatiotemporal Tuples model, a natural adaptation of Linda model for physically deployed large-scale networks. Unlike prior research, spatiotemporal properties – expressing where and when a tuple should range and has to be deposited/retrieved – naturally turn into specifications of collective adaptive processes, to be carried on in cooperation by the devices filling the computational environment, and sustaining tuple operations in a resilient way, possibly even in mobile and faulty environments. Additionally, the model promotes decentralised implementations where tuples actually reside where they are issued, which is good for supporting peer-to-peer and mobile ad-hoc networks as well as privacy. In this paper, we (i) present and formalise the Spatiotemporal Tuples model, based on the unifying notion of computational space-time structure, (ii) provide an implementation in the ScaFi aggregate computing framework, turning tuple operations into aggregate processes, and finally (iii) provide evaluation through simulation and a rescue case study.
Testing: an Introduction and Panorama
- what testing is
- perspectives on testing
- xUnit, TDD, acceptance testing
- pointers to more stuff about testing
On Context-Orientation in Aggregate ProgrammingRoberto Casadei
Context-awareness plays a central role in self-
adaptive software. By a programming perspective, context is
often used implicitly, and context-aware code is fragmented
in the codebase. In Context-Oriented Programming, instead,
context is considered a first-class citizen and is explicitly used
to modularise context-sensitive functionality and behavioural
variability. In this paper, we reflect on the role of context in
collective adaptive systems, by a discussion from the special
perspective of a macro paradigm, Aggregate Programming,
which supports the specification of collective behaviour by a
global perspective through functional compositions of field com-
putations. In particular, we consider the abstractions exposed in
Context-Oriented and Aggregate Programming, suggest potential
synergies in both directions, and accordingly take the first steps
towards a combined design.
Engineering distributed applications and services in emerg-
ing and open computing scenarios like the Internet of Things, cyber-physical systems and pervasive computing, calls for identifying proper abstractions to smoothly capture collective behaviour, adaptivity, and dynamic injection and execution of concurrent distributed activities. Accordingly, we introduce a notion of “aggregate process” as a concurrent
field computation whose execution and interactions are sustained by a dynamic team of devices, and whose spatial region can opportunistically vary over time. We formalise this notion by extending the Field Calculus with a new primitive construct, spawn, used to instantiate a set of field
computations and regulate key aspects of their life-cycle. By virtue of an open-source implementation in the ScaFi framework, we show basic programming examples and benefits via two case studies of mobile ad-hoc networks and drone swarm scenarios, evaluated by simulation.
Coordinating Computation at the Edge: a Decentralized, Self-organizing, Spati...Roberto Casadei
Presentation of a paper accepted at the 4th Internetional Conference on Fog and Mobile Edge Computing (FMEC).
It discusses a decentralised, self-organising, spatial, collective approach to the development of edge-clouds/edge computing ecosystems.
Brief overview of the Rust system programming language. Provides a concise introduction of its basic features, with an emphasis on its memory safety features (ownership, moves, borrowing) and programming style with generic functions, structures, and traits.
A Programming Framework for Collective Adaptive EcosystemsRoberto Casadei
On the thrust of recent technological trends, we can
envision a future where dense ecosystems of digitally empowered devices
continuously adapt and operate in our environments to provide services
both to humans and other systems. To achieve that, we arguably need to
move beyond what an individual device can provide and rather focus on
what collectives of devices can offer as a system. Aggregate Computing
is a recent, promising framework generalising over spatial computing
approaches that supports the development of collective adaptive systems
by global specifications. It builds on the framework of the field
calculus to bridge the local and global perspectives, express
collective computations in a compositional way, and formally analyse
them to derive guarantees.
In this presentation, we describe the key concepts and results, take a
look at the practical support for Aggregate Computing on the JVM
provided by scafi, and consider the main research directions on the topic.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
6th eCAS workshop on Engineering Collective Adaptive Systems
1. 6th eCAS Workshop on
Engineering Collective Adaptive Systems
Introduction to the workshop
Roberto Casadei1
, Lukas Esterle2
1
ALMA MATER STUDIORUM–Università di Bologna, Cesena, Italy
2
Aarhus University, Denmark
October 1, 2021
Co-located with ACSOS 2021
http://ecas2021.apice.unibo.it/
2. Welcome to the eCAS workshop!
The workshop on engineering collective adaptive systems (CAS)
goal: foster discussion and collaboration within the community of researchers on CASs
(and related fields: CPSs, IoT, MAS, CCI...)
R.C., L.E. 1/7
3. On collective adaptive systems (1/2)
Motivation
fact: collectives are everywhere
pervasive/ubiquitous computing → more and more devices
autonomic computing → management complexity demands autonomy
then: emphasis shift from individual to collective behaviour
ú opportunities & challenges
What is a CAS?
system: a collection of interacting entities
adaptive: the system adapts to handle new situations
collective: the collection consists of (a large and possibly dynamic number of) members
kept together by some purpose or cause
∠ often congeneric (of related nature—e.g., agent-like)
∠ scale & reliability demand decentralisation
o various definitions and assumptions (on communication, agency, etc.)
R.C., L.E. 2/7
4. On collective adaptive systems (2/2)
From understanding to engineering
CASs have been observed in nature and social contexts
∠ cf. insect societies; human markets
Engineering draws inspiration from nature but also comes with new concepts, methods,
and techniques
∠ Key problem: how to build collective adaptive behaviour by designing individuals (behaviours,
interactions, structural connections)?
R.C., L.E. 3/7
5. eCAS 2021: data
6th edition!
12 submissions (+4 wrt 2020 edition; best result after eCAS’17)
∠ 11 full papers
∠ 1 position paper
geography of authors
∠ Germany: 14
∠ USA: 9
∠ Italy: 8
∠ UK: 3
∠ Belgium: 2
∠ Switzerland: 1
30 reviews (≈ 3 per paper)
R.C., L.E. 4/7
6. Special issue on Mobile Cyber-Physical Collectives W
eCAS authors and attendees are encouraged to contribute to the Frontiers Research
Topic on Mobile Cyber-Physical Collectives
∠ Essentially, a special issue on eCAS topics in the Robotics and AI journal (Scimago rank Q2)
∠ Editors: Roberto Casadei, Lukas Esterle, Paul Harvey, Rose Gamble, Elizabeth Wanner
∠ Abstract deadline: 26 November 2021
∠ Manuscript deadline: 25 February 2022
See the eCAS website & SI website for more information
R.C., L.E. 5/7
7. eCAS 2021: program
SESSION 1 - on principles for the design of CASs (session chair: Lukas Esterle) ≈ 1h
1) Christian Kröher, Klaus Schmid, Simon Paasche and Christian Sauer. Combining Central
Control with Collective Adaptive Systems
2) Giorgio Audrito, Roberto Casadei and Gianluca Torta. Fostering resilient execution of
multi-agent plans through self-organisation
3) Sebastian Schmid, Daniel Schraudner and Andreas Harth. Performance Comparison of
Simple Reflex Agents Using Stigmergy with Model-Based Agents in Self-Organizing
Transportation
SESSION 2 - on formal design of CASs (session chair: Roberto Casadei) ≈ 1h
1) Hunza Zainab, Giorgio Audrito, Soura Dasgupta and Jacob Beal. Effect of Monotonic
Filtering on Graph Collection Dynamics
2) Joseph Hirsch, Martin Neumayer, Hella Ponsar, Oliver Kosak and Wolfgang Reif. Distributed
Constraint Optimization for Task Allocation in Self-Adaptive Manufacturing Systems
3) Ian Riley and Rose Gamble. Employing Stochastic Multiplayer Games to Support
Self-Organization over Ad Hoc Networks
DINNER (LUNCH) BREAK: 19:00 – 20:00 CEST (13:00 – 14:00 EST)
SESSION 3 - approaches to CAS design (session chair: Giorgio Audrito) ≈ 1h20m
1) Gianluca Aguzzi, Roberto Casadei, Danilo Pianini, Guido Salvaneschi and Mirko Viroli. Towards
Pulverised Architectures for Collective Adaptive Systems through Multi-tier Programming
2) Emad Eldeen Elakehal and Joost Vennekens. A Logic-based Multiagent Product
Configuration Model
3) Paul Akiki, Andrea Zisman and Amel Bennaceur. Work With What You’ve Got: An Approach
for Resource-driven Adaptation
4) Daniel Palmer, Ryan Houghtaling, Marc Kirschenbaum and Morgan Might. Interactive
Methodology to Iteratively Add Functionality to Swarm Programs
discussion on CAS research directions + workshop closing ≤ 1h30m
∠ aspects raised during discussions
∠ meta-reflections on CASs as a research field
∠ mobile cyber-physical CASs
R.C., L.E. 6/7
8. Warm-up
Talks: 15’ presentation + 5’ Q&A
In the next 5 minutes (or next breaks), introduce yourself on the #workshop-ecas Slack
channel in the ACSOS-2021 space
∠ Mention what specific aspects of CASs your research focusses on (e.g., principles, optimisation,
programming, design, algorithms, specific case studies...) or interest you the most
R.C., L.E. 7/7