113,214 research outputs found
A Multicomponent Distributed Framework for Smart Production System Modeling and Simulation
In order to control manufacturing systems, managers need risk and performance evaluation methods and simulation tools. However, these simulation techniques must evolve towards being multiperformance, multiactor, and multisimulation tools, and this requires interoperability between those distributed components. This paper presents an integrated platform that brings interoperability to several simulation components. This work expands the process modeling tool Papyrus to allow it to communicate with external components through both distributed simulation and cosimulation standards. The distributed modeling and simulation framework (DMSF) platform takes its environment into consideration in order to evaluate the sustainability of the system while integrating external heterogeneous components. For instance, a DMSF connection with external IoT devices has been implemented. Moreover, the orchestration of different smart manufacturing components and services is achieved through configurable business models. As a result, an automotive industry case study has successfully been tested to demonstrate the sustainability of smart supply chains and manufacturing factories, allowing better connectivity with their real environments
Virtual Communication Stack: Towards Building Integrated Simulator of Mobile Ad Hoc Network-based Infrastructure for Disaster Response Scenarios
Responses to disastrous events are a challenging problem, because of possible
damages on communication infrastructures. For instance, after a natural
disaster, infrastructures might be entirely destroyed. Different network
paradigms were proposed in the literature in order to deploy adhoc network, and
allow dealing with the lack of communications. However, all these solutions
focus only on the performance of the network itself, without taking into
account the specificities and heterogeneity of the components which use it.
This comes from the difficulty to integrate models with different levels of
abstraction. Consequently, verification and validation of adhoc protocols
cannot guarantee that the different systems will work as expected in
operational conditions. However, the DEVS theory provides some mechanisms to
allow integration of models with different natures. This paper proposes an
integrated simulation architecture based on DEVS which improves the accuracy of
ad hoc infrastructure simulators in the case of disaster response scenarios.Comment: Preprint. Unpublishe
BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations
Objective: The advent of High-Performance Computing (HPC) in recent years has
led to its increasing use in brain study through computational models. The
scale and complexity of such models are constantly increasing, leading to
challenging computational requirements. Even though modern HPC platforms can
often deal with such challenges, the vast diversity of the modeling field does
not permit for a single acceleration (or homogeneous) platform to effectively
address the complete array of modeling requirements. Approach: In this paper we
propose and build BrainFrame, a heterogeneous acceleration platform,
incorporating three distinct acceleration technologies, a Dataflow Engine, a
Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform.
As a challenging proof of concept, we analyze the performance of BrainFrame on
different instances of a state-of-the-art neuron model, modeling the Inferior-
Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley
representation. The model instances take into account not only the neuronal-
network dimensions but also different network-connectivity circumstances that
can drastically change application workload characteristics. Main results: The
synthetic approach of three HPC technologies demonstrated that BrainFrame is
better able to cope with the modeling diversity encountered. Our performance
analysis shows clearly that the model directly affect performance and all three
technologies are required to cope with all the model use cases.Comment: 16 pages, 18 figures, 5 table
Integrated Design Tools for Embedded Control Systems
Currently, computer-based control systems are still being implemented using the same techniques as 10 years ago. The purpose of this project is the development of a design framework, consisting of tools and libraries, which allows the designer to build high reliable heterogeneous real-time embedded systems in a very short time at a fraction of the present day costs. The ultimate focus of current research is on transformation control laws to efficient concurrent algorithms, with concerns about important non-functional real-time control systems demands, such as fault-tolerance, safety,\ud
reliability, etc.\ud
The approach is based on software implementation of CSP process algebra, in a modern way (pure objectoriented design in Java). Furthermore, it is intended that the tool will support the desirable system-engineering stepwise refinement design approach, relying on past research achievements Âż the mechatronics design trajectory based on the building-blocks approach, covering all complex (mechatronics) engineering phases: physical system modeling, control law design, embedded control system implementation and real-life realization. Therefore, we expect that this project will result in an\ud
adequate tool, with results applicable in a wide range of target hardware platforms, based on common (off-theshelf) distributed heterogeneous (cheap) processing units
A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing
The emergence of cloud computing based on virtualization technologies brings
huge opportunities to host virtual resource at low cost without the need of
owning any infrastructure. Virtualization technologies enable users to acquire,
configure and be charged on pay-per-use basis. However, Cloud data centers
mostly comprise heterogeneous commodity servers hosting multiple virtual
machines (VMs) with potential various specifications and fluctuating resource
usages, which may cause imbalanced resource utilization within servers that may
lead to performance degradation and service level agreements (SLAs) violations.
To achieve efficient scheduling, these challenges should be addressed and
solved by using load balancing strategies, which have been proved to be NP-hard
problem. From multiple perspectives, this work identifies the challenges and
analyzes existing algorithms for allocating VMs to PMs in infrastructure
Clouds, especially focuses on load balancing. A detailed classification
targeting load balancing algorithms for VM placement in cloud data centers is
investigated and the surveyed algorithms are classified according to the
classification. The goal of this paper is to provide a comprehensive and
comparative understanding of existing literature and aid researchers by
providing an insight for potential future enhancements.Comment: 22 Pages, 4 Figures, 4 Tables, in pres
- …