Modeling the Internet of Things: a simulation perspective

This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the heterogeneity of scenarios seriously complicates this task. This imposes the use of sophisticated modeling and simulation techniques. We discuss novel approaches for the provision of scalable simulation scenarios, that enable the real-time execution of massively populated IoT environments. Attention is given to novel hybrid and multi-level simulation techniques that, when combined with agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches, can provide means to perform highly detailed simulations on demand. To support this claim, we detail a use case concerned with the simulation of vehicular transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High Performance Computing and Simulation (HPCS 2017

Influence of Interfacial Dynamics and Multi-Dimensional Coupling from Isolator Brackets on Exhaust Isolation System Performance

An automotive exhaust structure is a primary structure-borne noise path by which vibratory forces from the powertrain are transmitted to the vehicle body. The exhaust structure is typically connected to the vehicle body through a system of brackets containing elastomeric isolators, serving as the principal means of vibration isolation. In exhaust isolator system design, the isolator brackets are often modeled as simple springs. This approach neglects the effects of interfacial dynamics and multi-dimensional coupling, which result from distributed mass and stiffness throughout the isolator brackets. Accordingly, the objective of this research is to better understand how the interfacial dynamics and multi-dimensional coupling of the isolator brackets affect the exhaust isolation system performance in the 0-100 Hz range. Therefore, models with a proper representation of these interfacial dynamics and multi-dimensional coupling are created using finite element analysis (FEA) and then parameterized into multi-dimensional lumped parameter models through correlation of static and modal testing on the components and assembled system. The dynamic responses from the models for the exhaust structure and isolator brackets are then combined into a system-level model through a frequency-response-function-based substructuring method. A design study is conducted on the system-level model by systematically changing component parameters and evaluating the effect on the transmitted vertical body forces. The results show that the inclusion of these interfacial dynamics have nominal influence on isolation performance; however, the coupling terms show an observable influence, typically increasing the force transmitted to the vehicle body. In addition, the study identified additional design modifications that could improve isolation performance, such as an increase in isolator material loss factor and an increase in the isolator fore-aft stiffness. Although the results are specific to this isolation system design, the modeling procedure outlined has the potential to be used early in the vehicle design process to identify improvements to other baseline designs.NSF I/UCRC Smart Vehicle Concepts CenterTenneco, Inc.A three-year embargo was granted for this item.Academic Major: Mechanical Engineerin

Integrated Simulation Platform for Quantifying the Traffic-Induced Environmental and Health Impacts

Air quality and human exposure to mobile source pollutants have become major concerns in urban transportation. Existing studies mainly focus on mitigating traffic congestion and reducing carbon footprints, with limited understanding of traffic-related health impacts from the environmental justice perspective. To address this gap, we present an innovative integrated simulation platform that models traffic-related air quality and human exposure at the microscopic level. The platform consists of five modules: SUMO for traffic modeling, MOVES for emissions modeling, a 3D grid-based dispersion model, a Matlab-based concentration visualizer, and a human exposure model. Our case study on multi-modal mobility on-demand services demonstrates that a distributed pickup strategy can reduce human cancer risk associated with PM2.5 by 33.4% compared to centralized pickup. Our platform offers quantitative results of traffic-related air quality and health impacts, useful for evaluating environmental issues and improving transportation systems management and operations strategies.Comment: 35 pages, 11 figure

A Hierarchical Context-aware Modeling Approach for Multi-aspect and Multi-granular Pronunciation Assessment

Automatic Pronunciation Assessment (APA) plays a vital role in Computer-assisted Pronunciation Training (CAPT) when evaluating a second language (L2) learner's speaking proficiency. However, an apparent downside of most de facto methods is that they parallelize the modeling process throughout different speech granularities without accounting for the hierarchical and local contextual relationships among them. In light of this, a novel hierarchical approach is proposed in this paper for multi-aspect and multi-granular APA. Specifically, we first introduce the notion of sup-phonemes to explore more subtle semantic traits of L2 speakers. Second, a depth-wise separable convolution layer is exploited to better encapsulate the local context cues at the sub-word level. Finally, we use a score-restraint attention pooling mechanism to predict the sentence-level scores and optimize the component models with a multitask learning (MTL) framework. Extensive experiments carried out on a publicly-available benchmark dataset, viz. speechocean762, demonstrate the efficacy of our approach in relation to some cutting-edge baselines.Comment: Accepted to Interspeech 202

An Expanded Multi-scale Monte Carlo Simulation Method for Personalized Radiobiological Effect Estimation in Radiotherapy: a feasibility study

A novel and versatile “bottom-up� approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy

A Fuzzy Multi Criteria Approach for Sustainable Manufacturing Evaluation in Cement Industry

The cement industry has remarked as an intensive consumer of natural raw materials, fossil fuels, energy, and a major source of multiple pollutants. Therefore, it is a need to evaluate sustainable manufacturing in this industry. This paper aims to propose a fuzzy multi criteria approach for evaluating sustainable manufacturing in cement industry which integrated the Interpretive Structural Modeling (ISM) and the Fuzzy Analytic Network Process (FANP) methodology. The network relationship model is constructed using ISM methodology. Importance weights of indicators are assigned by pairwise comparisons and calculated using fuzzy ANP methodology. A case study is also presented to demonstrate implementation of the evaluation model. The results show the existing performance level on company's strengths and weaknesses, and where improvements need to be made. It is hoped the proposed evaluation model can aid the cement industry to achieve the higher performance in sustainable manufacturing

Interval simulation: raising the level of abstraction in architectural simulation

Detailed architectural simulators suffer from a long development cycle and extremely long evaluation times. This longstanding problem is further exacerbated in the multi-core processor era. Existing solutions address the simulation problem by either sampling the simulated instruction stream or by mapping the simulation models on FPGAs; these approaches achieve substantial simulation speedups while simulating performance in a cycle-accurate manner This paper proposes interval simulation which rakes a completely different approach: interval simulation raises the level of abstraction and replaces the core-level cycle-accurate simulation model by a mechanistic analytical model. The analytical model estimates core-level performance by analyzing intervals, or the timing between two miss events (branch mispredictions and TLB/cache misses); the miss events are determined through simulation of the memory hierarchy, cache coherence protocol, interconnection network and branch predictor By raising the level of abstraction, interval simulation reduces both development time and evaluation time. Our experimental results using the SPEC CPU2000 and PARSEC benchmark suites and the MS multi-core simulator show good accuracy up to eight cores (average error of 4.6% and max error of 11% for the multi-threaded full-system workloads), while achieving a one order of magnitude simulation speedup compared to cycle-accurate simulation. Moreover interval simulation is easy to implement: our implementation of the mechanistic analytical model incurs only one thousand lines of code. Its high accuracy, fast simulation speed and ease-of-use make interval simulation a useful complement to the architect's toolbox for exploring system-level and high-level micro-architecture trade-offs