8,050 research outputs found
INDEMICS: An Interactive High-Performance Computing Framework for Data Intensive Epidemic Modeling
We describe the design and prototype implementation of Indemics (_Interactive; Epi_demic; _Simulation;)—a modeling environment utilizing high-performance computing technologies for supporting complex epidemic simulations. Indemics can support policy analysts and epidemiologists interested in planning and control of pandemics. Indemics goes beyond traditional epidemic simulations by providing a simple and powerful way to represent and analyze policy-based as well as individual-based adaptive interventions. Users can also stop the simulation at any point, assess the state of the simulated system, and add additional interventions. Indemics is available to end-users via a web-based interface.
Detailed performance analysis shows that Indemics greatly enhances the capability and productivity of simulating complex intervention strategies with a marginal decrease in performance. We also demonstrate how Indemics was applied in some real case studies where complex interventions were implemented
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Ontology engineering for simulation component reuse
Commercial-off-the-shelf (COTS) simulation packages (CSPs) are widely used in industry, although they have yet to operate across organizational boundaries. Reuse across organizations is restricted by the same semantic issues that restrict the inter-organizational use of web services. The current representations of web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging semantic web. Semantic models, in the form of ontology, utilized by web service discovery and deployment architectures provide one approach to support simulation model reuse. Semantic interoperation is achieved through the use of simulation component ontologies to identify required components at varying levels of granularity (including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The paper presents the development of an ontology, connector software and web service discovery architecture. The ontology is extracted from simulation scenarios involving airport, restaurant and kitchen service suppliers. The ontology engineering framework and discovery architecture provide a novel approach to inter-organizational simulation, adopting a less intrusive interface between participants. Although specific to CSPs the work has wider implications for the simulation community
How Resilient Are Our Societies? Analyses, Models, and Preliminary Results
Traditional social organizations such as those for the management of
healthcare and civil defence are the result of designs and realizations that
matched well with an operational context considerably different from the one we
are experiencing today: A simpler world, characterized by a greater amount of
resources to match less users producing lower peaks of requests. The new
context reveals all the fragility of our societies: unmanageability is just
around the corner unless we do not complement the "old recipes" with smarter
forms of social organization. Here we analyze this problem and propose a
refinement to our fractal social organizations as a model for resilient
cyber-physical societies. Evidence to our claims is provided by simulating our
model in terms of multi-agent systems.Comment: Paper submitted for publication in the Proc. of SERENE 2015
(http://serene.disim.univaq.it/2015/
Delay Tolerant Networking over the Metropolitan Public Transportation
We discuss MDTN: a delay tolerant application platform built on top of the Public Transportation System (PTS) and able to provide service access while exploiting opportunistic connectivity. Our solution adopts a carrier-based approach where buses act as data collectors for user requests requiring Internet access. Simulations based on real maps and PTS routes with state-of-the-art routing protocols demonstrate that MDTN represents a viable solution for elastic nonreal-time service delivery. Nevertheless, performance indexes of the considered routing policies show that there is no golden rule for optimal performance and a tailored routing strategy is required for each specific case
The Living Application: a Self-Organising System for Complex Grid Tasks
We present the living application, a method to autonomously manage
applications on the grid. During its execution on the grid, the living
application makes choices on the resources to use in order to complete its
tasks. These choices can be based on the internal state, or on autonomously
acquired knowledge from external sensors. By giving limited user capabilities
to a living application, the living application is able to port itself from one
resource topology to another. The application performs these actions at
run-time without depending on users or external workflow tools. We demonstrate
this new concept in a special case of a living application: the living
simulation. Today, many simulations require a wide range of numerical solvers
and run most efficiently if specialized nodes are matched to the solvers. The
idea of the living simulation is that it decides itself which grid machines to
use based on the numerical solver currently in use. In this paper we apply the
living simulation to modelling the collision between two galaxies in a test
setup with two specialized computers. This simulation switces at run-time
between a GPU-enabled computer in the Netherlands and a GRAPE-enabled machine
that resides in the United States, using an oct-tree N-body code whenever it
runs in the Netherlands and a direct N-body solver in the United States.Comment: 26 pages, 3 figures, accepted by IJHPC
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation
State-of-the-art emergency navigation approaches are designed to evacuate
civilians during a disaster based on real-time decisions using a pre-defined
algorithm and live sensory data. Hence, casualties caused by the poor decisions
and guidance are only apparent at the end of the evacuation process and cannot
then be remedied. Previous research shows that the performance of routing
algorithms for evacuation purposes are sensitive to the initial distribution of
evacuees, the occupancy levels, the type of disaster and its as well its
locations. Thus an algorithm that performs well in one scenario may achieve bad
results in another scenario. This problem is especially serious in
heuristic-based routing algorithms for evacuees where results are affected by
the choice of certain parameters. Therefore, this paper proposes a
simulation-based evacuee routing algorithm that optimises evacuation by making
use of the high computational power of cloud servers. Rather than guiding
evacuees with a predetermined routing algorithm, a robust Cognitive Packet
Network based algorithm is first evaluated via a cloud-based simulator in a
faster-than-real-time manner, and any "simulated casualties" are then re-routed
using a variant of Dijkstra's algorithm to obtain new safe paths for them to
exits. This approach can be iterated as long as corrective action is still
possible.Comment: Submitted to PerNEM'15 for revie
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