scholarly journals DeepFogSim: A Toolbox for Execution and Performance Evaluation of the Inference Phase of Conditional Deep Neural Networks with Early Exits Atop Distributed Fog Platforms

2021 ◽  
Vol 11 (1) ◽  
pp. 377
Author(s):  
Michele Scarpiniti ◽  
Enzo Baccarelli ◽  
Alireza Momenzadeh ◽  
Sima Sarv Ahrabi
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Future Internet ◽  
Operating Conditions ◽  
Graphic User Interface ◽  
Energy Aware ◽  
Internet Applications ◽  
The Real ◽  
Delay Performance ◽  
Hard Constraints

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.

scholarly journals VirtFogSim: A Parallel Toolbox for Dynamic Energy-Delay Performance Testing and Optimization of 5G Mobile-Fog-Cloud Virtualized Platforms

2019 ◽  
Vol 9 (6) ◽  
pp. 1160 ◽  
Author(s):  
Michele Scarpiniti ◽  
Enzo Baccarelli ◽  
Alireza Momenzadeh
Keyword(s):  
Effective Means ◽  
Performance Testing ◽  
Future Internet ◽  
Building Blocks ◽  
Field Trials ◽  
Parallel Execution ◽  
Graphic User Interface ◽  
Energy Aware ◽  
Internet Applications ◽  
Delay Performance

It is expected that the pervasive deployment of multi-tier 5G-supported Mobile-Fog-Cloudtechnological computing platforms will constitute an effective means to support the real-time execution of future Internet applications by resource- and energy-limited mobile devices. Increasing interest in this emerging networking-computing technology demands the optimization and performance evaluation of several parts of the underlying infrastructures. However, field trials are challenging due to their operational costs, and in every case, the obtained results could be difficult to repeat and customize. These emerging Mobile-Fog-Cloud ecosystems still lack, indeed, customizable software tools for the performance simulation of their computing-networking building blocks. Motivated by these considerations, in this contribution, we present VirtFogSim. It is a MATLAB-supported software toolbox that allows the dynamic joint optimization and tracking of the energy and delay performance of Mobile-Fog-Cloud systems for the execution of applications described by general Directed Application Graphs (DAGs). In a nutshell, the main peculiar features of the proposed VirtFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the placement of the application tasks and the allocation of the needed computing-networking resources under hard constraints on acceptable overall execution times; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall system; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operational environments, as those typically featuring mobile applications; (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering; and (v) its MATLAB code is optimized for running atop multi-core parallel execution platforms. To check both the actual optimization and scalability capabilities of the VirtFogSim toolbox, a number of experimental setups featuring different use cases and operational environments are simulated, and their performances are compared.

Power Test System Development and Dynamic Performance State Estimation Based on Hub Motor Vehicle

2020 ◽  
Vol 13 (2) ◽  
pp. 126-140
Author(s):  
Jing Gan ◽  
Xiaobin Fan ◽  
Zeng Song ◽  
Mingyue Zhang ◽  
Bin Zhao
Keyword(s):  
Real Time ◽  
Dynamic Performance ◽  
Test System ◽  
Operating Conditions ◽  
Motor Vehicles ◽  
Maximum Speed ◽  
Performance Parameters ◽  
Power Performance ◽  
Power Test ◽  
The Real

Background: The power performance of an electric vehicle is the basic parameter. Traditional test equipment, such as the expensive chassis dynamometer, not only increases the cost of testing but also makes it impossible to measure all the performance parameters of an electric vehicle. Objective: A set of convenient, efficient and sensitive power measurement system for electric vehicles is developed to obtain the real-time power changes of hub-motor vehicles under various operating conditions, and the dynamic performance parameters of hub-motor vehicles are obtained through the system. Methods: Firstly, a set of on-board power test system is developed by using virtual instrument (Lab- VIEW). This test system can obtain the power changes of hub-motor vehicles under various operating conditions in real-time and save data in real-time. Then, the driving resistance of hub-motor vehicles is analyzed, and the power performance of hub-motor vehicles is studied in depth. The power testing system is proposed to test the input power of both ends of the driving motor, and the chassis dynamometer is combined to test so that the output efficiency of the driving motor can be easily obtained without disassembly. Finally, this method is used to carry out the road test and obtain the vehicle dynamic performance parameters. Results: The real-time current, voltage and power, maximum power, acceleration time and maximum speed of the vehicle can be obtained accurately by using the power test system in the real road experiment. Conclusion: The maximum power required by the two motors reaches about 9KW, and it takes about 20 seconds to reach the maximum speed. The total power required to maintain the maximum speed is about 7.8kw, and the maximum speed is 62km/h. In this article, various patents have been discussed.

scholarly journals Mixed-mode Operating System for Real-time Performance

2017 ◽  
Vol 26 (1) ◽  
pp. 43-56
Author(s):  
M.M. Hasan ◽  
S. Sultana ◽  
C.K. Foo
Keyword(s):  
Operating System ◽  
Real Time ◽  
Mixed Mode ◽  
Graphic User Interface ◽  
The Real ◽  
Practical Applications ◽  
Windows Nt ◽  
Time Systems ◽  
Realtime System ◽  
Load Tolerance

The purpose of the mixed-mode system research is to handle devices with the accuracy of real-time systems and at the same time, having all the benefits and facilities of a matured Graphic User Interface (GUI) operating system which is typically nonreal-time. This mixed-mode operating system comprising of a real-time portion and a non-real-time portion was studied and implemented to identify the feasibilities and performances in practical applications (in the context of scheduled the real-time events). In this research an i8751 microcontroller-based hardware was used to measure the performance of the system in real-time-only as well as non-real-time-only configurations. The real-time portion is an 486DX-40 IBM PC system running under DOS-based realtime kernel and the non-real-time portion is a Pentium III based system running under Windows NT. It was found that mixed-mode systems performed as good as a typical realtime system and in fact, gave many additional benefits such as simplified/modular programming and load tolerance.

Fuzzy Logics Associated with Neural Networks in the Real Time for Better World

2017 ◽  
Vol 4 (8) ◽  
pp. 8507-8516
Author(s):  
G. Prabhakar Reddy ◽  
Y. Deepika ◽  
K. Sai Prasad ◽  
G. Kiran Kumar
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Fuzzy Logics ◽  
The Real
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