1,913 research outputs found
Engineering environment-mediated coordination via nature-inspired laws
SAPERE is a general multiagent framework to support the development of self-organizing pervasive computing services. One of the key aspects of the SAPERE approach is to have all interactions between agents take place in an indirect way, via a shared spatial environment. In such environment, a set of nature-inspired coordination laws have been defined to rule the coordination activities of the application agents and promote the provisioning of adaptive and self-organizing services
Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies, Multiagent System Paradigm, and Natural Ecosystems
Wireless sensor networks (WSNs) are key components in the emergent cyber physical systems (CPSs). They may include hundreds of spatially distributed sensors which interact to solve complex tasks going beyond their individual capabilities. Due to the limited capabilities of sensors, sensor actions cannot meet CPS requirements while controlling and coordinating the operations of physical and engineered systems. To overcome these constraints, we explore the ecosystem metaphor for WSNs with the aim of taking advantage of the efficient adaptation behavior and communication mechanisms of living organisms. By mapping these organisms onto sensors and ecosystems onto WSNs, we highlight shortcomings that prevent WSNs from delivering the capabilities of ecosystems at several levels, including structure, topology, goals, communications, and functions. We then propose an agent-based architecture that migrates complex processing tasks outside the physical sensor network while incorporating missing characteristics of autonomy, intelligence, and context awareness to the WSN. Unlike existing works, we use software agents to map WSNs to natural ecosystems and enhance WSN capabilities to take advantage of bioinspired algorithms. We extend our architecture and propose a new intelligent CPS framework where several control levels are embedded in the physical system, thereby allowing agents to support WSNs technologies in enabling CPSs
Engineering Resilient Collective Adaptive Systems by Self-Stabilisation
Collective adaptive systems are an emerging class of networked computational
systems, particularly suited in application domains such as smart cities,
complex sensor networks, and the Internet of Things. These systems tend to
feature large scale, heterogeneity of communication model (including
opportunistic peer-to-peer wireless interaction), and require inherent
self-adaptiveness properties to address unforeseen changes in operating
conditions. In this context, it is extremely difficult (if not seemingly
intractable) to engineer reusable pieces of distributed behaviour so as to make
them provably correct and smoothly composable.
Building on the field calculus, a computational model (and associated
toolchain) capturing the notion of aggregate network-level computation, we
address this problem with an engineering methodology coupling formal theory and
computer simulation. On the one hand, functional properties are addressed by
identifying the largest-to-date field calculus fragment generating
self-stabilising behaviour, guaranteed to eventually attain a correct and
stable final state despite any transient perturbation in state or topology, and
including highly reusable building blocks for information spreading,
aggregation, and time evolution. On the other hand, dynamical properties are
addressed by simulation, empirically evaluating the different performances that
can be obtained by switching between implementations of building blocks with
provably equivalent functional properties. Overall, our methodology sheds light
on how to identify core building blocks of collective behaviour, and how to
select implementations that improve system performance while leaving overall
system function and resiliency properties unchanged.Comment: To appear on ACM Transactions on Modeling and Computer Simulatio
Of fixes and glitches:Mixing metaphors for platform urbanism
The growing influence of digital platforms on cities has captured the attention of urban scholars, marking a ‘platform pivot’ in digital geography and urban research. This article reviews emerging literature on platform urbanism, using the metaphors of the fix and the glitch as starting points from which to discuss two contrasting perspectives on the phenomenon. Rooted in Marxist political economy, fix-thinking highlights how platforms generate new opportunities for value-extraction through processes of disembedding, datafication and deregulation. Influenced by feminist, queer and Black media studies, glitch-thinking performatively underscores the breakdowns and openings in the working of platforms. Where fix-thinking highlights the role of platforms in furthering urban capitalism, glitch-thinking encourages us to envision how things could be otherwise. The review leads to two original insights that may further knowledge on this phenomenon. First, it points to a gap in research investigating instances when breakdown and disruptions turn into organised action and sustained social change. Second, it underscores the citational politics that limit engagements between the two strands, and the potential usefulness of drawing on earlier scholarship that softens or challenge the ‘fix-glitch divide’. © 2023 The Autho
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