14,072 research outputs found
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
Parallel and Distributed Simulation from Many Cores to the Public Cloud (Extended Version)
In this tutorial paper, we will firstly review some basic simulation concepts
and then introduce the parallel and distributed simulation techniques in view
of some new challenges of today and tomorrow. More in particular, in the last
years there has been a wide diffusion of many cores architectures and we can
expect this trend to continue. On the other hand, the success of cloud
computing is strongly promoting the everything as a service paradigm. Is
parallel and distributed simulation ready for these new challenges? The current
approaches present many limitations in terms of usability and adaptivity: there
is a strong need for new evaluation metrics and for revising the currently
implemented mechanisms. In the last part of the paper, we propose a new
approach based on multi-agent systems for the simulation of complex systems. It
is possible to implement advanced techniques such as the migration of simulated
entities in order to build mechanisms that are both adaptive and very easy to
use. Adaptive mechanisms are able to significantly reduce the communication
cost in the parallel/distributed architectures, to implement load-balance
techniques and to cope with execution environments that are both variable and
dynamic. Finally, such mechanisms will be used to build simulations on top of
unreliable cloud services.Comment: Tutorial paper published in the Proceedings of the International
Conference on High Performance Computing and Simulation (HPCS 2011). Istanbul
(Turkey), IEEE, July 2011. ISBN 978-1-61284-382-
Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems
There is a trend towards using wireless technologies in networked control
systems. However, the adverse properties of the radio channels make it
difficult to design and implement control systems in wireless environments. To
attack the uncertainty in available communication resources in wireless control
systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS)
scheme is developed, which takes advantage of the co-design of control and
wireless communications. By exploiting cross-layer design, CLAFS adjusts the
sampling periods of control systems at the application layer based on
information about deadline miss ratio and transmission rate from the physical
layer. Within the framework of feedback scheduling, the control performance is
maximized through controlling the deadline miss ratio. Key design parameters of
the feedback scheduler are adapted to dynamic changes in the channel condition.
An event-driven invocation mechanism for the feedback scheduler is also
developed. Simulation results show that the proposed approach is efficient in
dealing with channel capacity variations and noise interference, thus providing
an enabling technology for control over WLAN.Comment: 17 pages, 12 figures; Open Access at
http://www.mdpi.org/sensors/papers/s8074265.pd
Nature-Inspired Interconnects for Self-Assembled Large-Scale Network-on-Chip Designs
Future nano-scale electronics built up from an Avogadro number of components
needs efficient, highly scalable, and robust means of communication in order to
be competitive with traditional silicon approaches. In recent years, the
Networks-on-Chip (NoC) paradigm emerged as a promising solution to interconnect
challenges in silicon-based electronics. Current NoC architectures are either
highly regular or fully customized, both of which represent implausible
assumptions for emerging bottom-up self-assembled molecular electronics that
are generally assumed to have a high degree of irregularity and imperfection.
Here, we pragmatically and experimentally investigate important design
trade-offs and properties of an irregular, abstract, yet physically plausible
3D small-world interconnect fabric that is inspired by modern network-on-chip
paradigms. We vary the framework's key parameters, such as the connectivity,
the number of switch nodes, the distribution of long- versus short-range
connections, and measure the network's relevant communication characteristics.
We further explore the robustness against link failures and the ability and
efficiency to solve a simple toy problem, the synchronization task. The results
confirm that (1) computation in irregular assemblies is a promising and
disruptive computing paradigm for self-assembled nano-scale electronics and (2)
that 3D small-world interconnect fabrics with a power-law decaying distribution
of shortcut lengths are physically plausible and have major advantages over
local 2D and 3D regular topologies
Seven properties of self-organization in the human brain
The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) functional plasticity, 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
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