Parallel and distributed simulation from many cores to the public cloud

D’Angelo, Gabriele

doi:10.1109/hpcsim.2011.5999802

Cited by 51 publications

(40 citation statements)

References 30 publications

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“…D'Angelo [4] describes a Simulation-as-a-Service schema in which parallel and distributed simulations could be executed transparently, which requires dealing with model partitioning, data distribution and synchronization. He concludes that the potential challenges concerning hardware, performance, usability and cost that could arise could be overcome and optimized with the proper simulation model partitioning.…”

Section: Related Workmentioning

confidence: 99%

A Cloudification Methodology for Numerical Simulations

Caíno‐Lores

Garcı́a

Garcı́a-Carballeira

et al. 2014

Lecture Notes in Computer Science

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Abstract. Many scientific areas make extensive use of computer simulations to study complex real-world processes. These computations are typically very resource-intensive and present scalability issues as experiments get larger, even in dedicated clusters since they are limited by their own hardware resources. Cloud computing raises as an option to move forward into the ideal unlimited scalability by providing virtually infinite resources, yet applications must be adapted to this new paradigm. We propose a generalist cloudification method based in the MapReduce paradigm to migrate numerical simulations into the cloud to provide greater scalability. We analysed its viability by applying it to a realworld simulation and running the resulting implementation on Hadoop YARN over Amazons EC2. Our tests show that the cloudified application is highly scalable and there is still a large margin to improve the theoretical model and its implementations, and also to extend it to a wider range of simulations.

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Section: Related Workmentioning

confidence: 99%

A Cloudification Methodology for Numerical Simulations

Caíno‐Lores

Garcı́a

Garcı́a-Carballeira

et al. 2014

Lecture Notes in Computer Science

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“…With emergent trends such as the Cloud, studies have evaluated the effectiveness of deploying simulation runs on Cloud environments [18], [19]. When the project first started, the main distributed technologies involved MapReduce and Hadoop at that time.…”

Section: B Parallel Simulationsmentioning

confidence: 99%

Data management and simulation support accelerating carbon capture through computing

Cheah

Boverhof

Elbashandy

et al. 2016

2016 IEEE 12th International Conference on E-Science (E-Science)

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“…A multitude of mobile users' terminals, sensors, RFID devices, and "things" in general has been (and it is going to be) designed to offer novel services in smart cities and territories [4,5,6]. All these devices vary in terms of hardware and software characteristics.…”

Section: Introductionmentioning

confidence: 99%

Multi-level simulation of Internet of Things on smart territories

D’Angelo

Ferretti

Ghini

2017

Simulation Modelling Practice and Theory

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In this paper, a methodology is presented and employed for simulating the Internet of Things (IoT). The requirement for scalability, due to the possibly huge amount of involved sensors and devices, and the heterogeneous scenarios that might occur, impose resorting to sophisticated modeling and simulation techniques. In particular, multi-level simulation is regarded as a main framework that allows simulating large-scale IoT environments while keeping high levels of detail, when it is needed. We consider a use case based on the deployment of smart services in decentralized territories. A two level simulator is employed, which is based on a coarse agent-based, adaptive parallel and distributed simulation approach to model the general life of simulated entities. However, when needed a finer grained simulator (based on OMNeT++) is triggered on a restricted portion of the simulated area, which allows considering all issues concerned with wireless communications. Based on this use case, it is confirmed that the ad-hoc wireless networking technologies do represent a principle tool to deploy smart services over decentralized countrysides. Moreover, the performance evaluation confirms the viability of utilizing multi-level simulation for simulating large scale IoT environments.Keywords: Simulation, Smart cities, Internet of Things, Multi-level Simulation, Parallel And Distributed Simulation (PADS) 0 Some parts of the research work described in this paper previously appeared in [1,2,3]. This paper is an extensively revised and extended version of the previous work in which more than 30% is new material. Please note that, some parts of the performance evaluation appeared in the extended version of [2] that is available in https://arxiv.org/abs/1604.07076 but not included in the official conference proceedings.

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Parallel and distributed simulation from many cores to the public cloud

Cited by 51 publications

References 30 publications

A Cloudification Methodology for Numerical Simulations

A Cloudification Methodology for Numerical Simulations

Data management and simulation support accelerating carbon capture through computing

Multi-level simulation of Internet of Things on smart territories

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