Distributed hybrid simulation of the Internet of things and smart territories

D’Angelo, Gabriele; Ferretti, Stefano; Ghini, Vittorio

doi:10.1002/cpe.4370

Cited by 14 publications

(11 citation statements)

References 75 publications

(201 reference statements)

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“…In [10], D'Angelo, Feretti and Ghini extended their approach to focus a Parallel and Distributed Simulation (PADS) to achieve performance gain. To this end, they chose a hybrid simulation approach coupled with PADS since they found out conventional monolithic simulators are not scalable enough.…”

Section: S 3 and Omnet++mentioning

confidence: 99%

“…Furthermore, the authors stated that it is of course in the realm of possibility that the hybrid simulation introduces additional approximation error in analysis. Before presenting their implementation of a case study, they specified the following general problems arising in parallel and distributed computing [10]:…”

Section: S 3 and Omnet++mentioning

confidence: 99%

“…Subsequently, D'Angelo, Feretti and Ghini continued testing with a parallel and distributed approach. While Level 0 (S 3 ) and Level 1b (OMNeT++) reside on a Linux host as described above, Level 1a (ADVISOR) is created on a windows host whose detailed specifications can be reviewed in [10]. The two hosts are interconnected by fast ethernet LAN.…”

Section: S 3 and Omnet++mentioning

confidence: 99%

“…The possibility to employ parallel and distributed simulations: Based on the observations in [10], the developed framework should provide either out of the box parallel and distributed capabilities, or at least be built in a way that facilitates later adaption of these principles to further support the aforementioned requirements.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Simulation-Based Performance Validation of Homomorphic Encryption Algorithms in the Internet of Things

Kolsch¹,

Heinz²,

Ratzke³

et al. 2019

Future Internet

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IoT systems consist of Hardware/Software systems (e.g., sensors) that are embedded in a physical world, networked and that interact with complex software platforms. The validation of such systems is a challenge and currently mostly done by prototypes. This paper presents the virtual environment for simulation, emulation and validation of an IoT platform and its semantic model in real life scenarios. It is based on a decentralized, bottom up approach that offers interoperability of IoT devices and the value-added services they want to use across different domains. The framework is demonstrated by a comprehensive case study. The example consists of the complete IoT “Smart Energy” use case with focus on data privacy by homomorphic encryption. The performance of the network is compared while using partially homomorphic encryption, fully homomorphic encryption and no encryption at all.As a major result, we found that our framework is capable of simulating big IoT networks and the overhead introduced by homomorphic encryption is feasible for VICINITY.

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Section: S 3 and Omnet++mentioning

confidence: 99%

Section: S 3 and Omnet++mentioning

confidence: 99%

Section: S 3 and Omnet++mentioning

confidence: 99%

mentioning

confidence: 99%

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Simulation-Based Performance Validation of Homomorphic Encryption Algorithms in the Internet of Things

Kolsch¹,

Heinz²,

Ratzke³

et al. 2019

Future Internet

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“…PDES Frameworks for Internet of Things -Gabriel et al [18] use hybrid simulation models for large complex scenarios. The models are capable of exploiting network diversity, which is the case for IoT devices.…”

Section: Related Workmentioning

confidence: 99%

Toward Distributed Heterogeneous Simulation Using Internet of Things

Haseeb

Malik

Rahman

et al. 2019

IEEE Internet Things J.

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HPC & Co strike back: Where are distributed paradigms heading toward?

Limet

Merlo

Spalazzi

2018

Concurrency and Computation

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From the dawn of parallelization, the diffusion of High-Performance Computing (HPC) has grown exponentially until nowadays, thereby leading to the birth and development of a huge research community in this field. During the last decades, the important research results have led to extend the domain of HPC into three different dimensions, namely Architectures, Research Topics, and Application Domains. ArchitecturesTraditional HPC architectures have been sided with several wide-area distributed paradigms such as Peer-to-Peer (P2P), Grid, Cloud, Fog and PervasiveComputing. 1-3 Each of them aims new specific objectives along with the original goal of improving performance and reliability. In this paper, the different declinations of the traditional HPC are grouped into three macro-categories, namely SIMD, Multi- * , and Cluster.• SIMD. It stands for "single instruction, multiple data" according to the Flynn taxonomy. 4 This refers to computing systems where a single instruction stream operates on multiple data streams in order to perform operations that may be naturally parallelized (eg, array processors, GPUs, GPGPUs, etc). This category also includes many specialized processing units, as vector extensions of modern processors like Streaming SIMD Extensions (SSE) 5 or Advanced Vector Extensions (AVX). 6• Multi- * . It refers to many-core, multi-core, and multi-processor architectures. They are all architectures characterized by the presence of multiple instruction streams operating on multiple data streams. What distinguishes this type of architectures from other MIMD architectures ("multiple instructions, multiple data" always according to the Flynn taxonomy 4 ) is the sharing of the central memory.• Cluster. It refers to Cluster Computing, namely a group of cost-effective linked commercial off-the-shelf computers working together so closely that they act as a single machine. What distinguishes this type of architecture from other MIMD-like architectures is the absence of central memory sharing (each processing unit has its own private memory) but the presence of mass memory sharing. As a matter of fact, the current Top500 supercomputers 7 are mostly clusters.Regarding wide-area distributed paradigms, all of them are included in the MIMD category (according to the Flynn's taxonomy). What distinguishes this type of architecture from other MIMD architectures is the lack of sharing of both the central memory and the mass memory. This paper takes into consideration the main four distributed paradigms that arose from traditional HPC, namely Grid Computing, Ubiquitous Computing, Peer-to-Peer Computing, Cloud, and the emerging Fog Computing. In brief:• Grid Computing 8-10 denotes a distributed architecture that enables coordinated resource sharing for problem-solving within dynamic organizations consisting of individuals, institutions, and resources.• Ubiquitous Computing (also known as Pervasive Computing or UbiComp) 11,12 refers to making available to users computational resources, which provide information and servi...

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Distributed hybrid simulation of the Internet of things and smart territories

Cited by 14 publications

References 75 publications

Simulation-Based Performance Validation of Homomorphic Encryption Algorithms in the Internet of Things

Simulation-Based Performance Validation of Homomorphic Encryption Algorithms in the Internet of Things

Toward Distributed Heterogeneous Simulation Using Internet of Things

HPC & Co strike back: Where are distributed paradigms heading toward?

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