scholarly journals An Assessment of the Performance of the Secure Remote Update Protocol in Simulated Real-World Conditions

IoT ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 549-563
Author(s):  
Andrew John Poulter ◽  
Simon J. Cox
Keyword(s):  
Power Consumption ◽  
Real World ◽  
Relative Performance ◽  
Experimental Measurements ◽  
Secure Protocol ◽  
Additional Processing ◽  
Processing Delay

This paper assesses the relative performance of the MQTT protocol in comparison to the Secure Remote Update Protocol (SRUP) in a number of simulated real-world conditions, and describes an experiment that has been conducted to measure the processing delay associated with the use of the more secure protocol. Experimental measurements for power consumption of the devices and the size of comparable TCP packets were also made. Analysis shows that the use of the SRUP protocol added an additional processing delay of between 42.92 ms and 51.60 ms—depending on the specific hardware in use. There was also shown to be a 55.47% increase in power consumption when running the secure SRUP protocol, compared with an MQTT implementation.

scholarly journals Towards Optimal Parallelism-Aware Service Chaining and Embedding

2021 ◽  
Author(s):  
Danyang Zheng ◽  
Gangxiang Shen ◽  
Xiaojun Cao ◽  
Biswanath Mukherjee
Keyword(s):  
Propagation Delay ◽  
Approximate Algorithm ◽  
Network Function Virtualization ◽  
Network Function ◽  
Propagation Delays ◽  
Additional Processing ◽  
Processing Delay ◽  
End To End ◽  
Multiple Network ◽  
Service Latency

<div>Emerging 5G technologies can significantly reduce end-to-end service latency for applications requiring strict quality of service (QoS). With network function virtualization (NFV), to complete a client’s request from those applications, the client’s data can sequentially go through multiple service functions (SFs) for processing/analysis but introduce additional processing delay. To reduce the processing delay from the serially-running SFs, network function parallelism (NFP) that allows multiple SFs to run in parallel is introduced. In this work, we study how to apply NFP into the SF chaining and embedding process such that the latency, including processing and propagation delays, can be jointly minimized. We introduce a novel augmented graph to address the parallel relationship constraint among the required SFs. Considering parallel relationship constraints, we propose a novel problem called parallelism-aware service function chaining and embedding (PSFCE). For this problem, we propose a near-optimal maximum parallel block gain (MPBG) first optimization algorithm when computing resources at each physical node are enough to host the required SFs. When computing resources are limited, we propose a logarithm-approximate algorithm, called parallelism-aware SFs deployment (PSFD), to jointly optimize processing and propagation delays. We conduct extensive simulations on multiple network scenarios to evaluate the performances of our schemes. Accordingly, we find that (i) MPBG is near-optimal, (ii) the optimization of end-to-end service latency largely depends on the processing delay in small networks and is impacted more by the propagation delay in large networks, and (iii) PSFD outperforms the schemes directly extended from existing works regarding end-to-end latency.</div>

Real-World Evaluation of Power Consumption and Performance of NB-IoT in Malaysia

2021 ◽  
pp. 1-1
Author(s):  
Haider A.H. Alobaidy ◽  
J. S. Mandeep ◽  
Rosdiadee Nordin ◽  
Nor Fadzilah Abdullah ◽  
Cheong Gze Wei ◽  
...  
Keyword(s):  
Power Consumption ◽  
Real World ◽  
And Performance

scholarly journals Development of a Wireless Temperature Sensor Using Polymer-Derived Ceramics

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Ran Zhao ◽  
Gang Shao ◽  
Ni Li ◽  
Chengying Xu ◽  
Linan An
Keyword(s):  
High Temperature ◽  
Power Consumption ◽  
Embedded System ◽  
Real World ◽  
Temperature Sensor ◽  
Wireless Transmission ◽  
Low Power Consumption ◽  
Compact Size ◽  
Real World Applications ◽  
The Embedded System

A temperature sensor has been developed using an embedded system and a sensor head made of polymer-derived SiAlCN ceramics (PDCs). PDC is a promising material for measuring high temperature and the embedded system features low-power consumption, compact size, and wireless transmission. The developed temperature sensor has been experimentally tested to demonstrate the possibility of using such sensors for real world applications.

scholarly journals Thwarting Nonintrusive Occupancy Detection Attacks from Smart Meters

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Dapeng Man ◽  
Wu Yang ◽  
Shichang Xuan ◽  
Xiaojiang Du
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Real World ◽  
Side Effect ◽  
Smart Meter ◽  
Smart Meters ◽  
Occupancy Detection ◽  
Load Monitoring ◽  
Privacy Issues ◽  
Statistical Metrics

Occupancy information is one of the most important privacy issues of a home. Unfortunately, an attacker is able to detect occupancy from smart meter data. The current battery-based load hiding (BLH) methods cannot solve this problem. To thwart occupancy detection attacks, we propose a framework of battery-based schemes to prevent occupancy detection (BPOD). BPOD monitors the power consumption of a home and detects the occupancy in real time. According to the detection result, BPOD modifies those statistical metrics of power consumption, which highly correlate with the occupancy by charging or discharging a battery, creating a delusion that the home is always occupied. We evaluate BPOD in a simulation using several real-world smart meter datasets. Our experiment results show that BPOD effectively prevents the threshold-based and classifier-based occupancy detection attacks. Furthermore, BPOD is also able to prevent nonintrusive appliance load monitoring attacks (NILM) as a side-effect of thwarting detection attacks.

scholarly journals Multi-Step Short-Term Power Consumption Forecasting with a Hybrid Deep Learning Strategy

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3089 ◽  
Author(s):  
Ke Yan ◽  
Xudong Wang ◽  
Yang Du ◽  
Ning Jin ◽  
Haichao Huang ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Power Consumption ◽  
Real World ◽  
Electricity Market ◽  
Moving Average ◽  
Short Term ◽  
Auto Regressive ◽  
Short Term Forecasting ◽  
Deep Learning Neural Network

Electric power consumption short-term forecasting for individual households is an important and challenging topic in the fields of AI-enhanced energy saving, smart grid planning, sustainable energy usage and electricity market bidding system design. Due to the variability of each household’s personalized activity, difficulties exist for traditional methods, such as auto-regressive moving average models, machine learning methods and non-deep neural networks, to provide accurate prediction for single household electric power consumption. Recent works show that the long short term memory (LSTM) neural network outperforms most of those traditional methods for power consumption forecasting problems. Nevertheless, two research gaps remain as unsolved problems in the literature. First, the prediction accuracy is still not reaching the practical level for real-world industrial applications. Second, most existing works only work on the one-step forecasting problem; the forecasting time is too short for practical usage. In this study, a hybrid deep learning neural network framework that combines convolutional neural network (CNN) with LSTM is proposed to further improve the prediction accuracy. The original short-term forecasting strategy is extended to a multi-step forecasting strategy to introduce more response time for electricity market bidding. Five real-world household power consumption datasets are studied, the proposed hybrid deep learning neural network outperforms most of the existing approaches, including auto-regressive integrated moving average (ARIMA) model, persistent model, support vector regression (SVR) and LSTM alone. In addition, we show a k-step power consumption forecasting strategy to promote the proposed framework for real-world application usage.

Statistical approach to compute a surrogate input for building physics CFD simulations through experimental measurements

2020 ◽  
Vol 20 (3) ◽  
pp. 909-936
Author(s):  
Fabio Rizzo ◽  
Paolo Zazzini ◽  
Antonio Pasculli ◽  
Alessandro Di Crescenzo
Keyword(s):  
Real World ◽  
Statistical Approach ◽  
Cfd Simulation ◽  
Hermite Polynomials ◽  
Experimental Measurements ◽  
Real World Data ◽  
Cfd Simulations ◽  
Human Errors ◽  
The Real ◽  
Building Physics

Computational Fluid Dynamics (CFD) simulations are sensitive to input uncertainties and human errors. Using real-world data as an input for CFD simulations is not rare for building physics simulations and it is still an open topic. In most cases, computer simulations using CFD are for design purposes and they aim to represent the situations occur in the real-world. The real-world parameters are commonly set based on experimental measurements. However, it is known that experimental measurements are affected by uncertainties; hence the experimental values have to be processed to calibrate numerical simulations. This paper investigates the CFD simulation calibration through experimental measurements. In particular, a statistical approach is employed to study the experimental data of inlet-outlet velocities for ten non successive days in a test-room with the purpose of assuming a surrogate day input that is the most significant of the dataset. Moreover, five different input methods on the boundary conditions of inlet velocity obtained from the experimental measurements are implemented and the accuracy of the predicted results through CFD simulations is presented. For the first input, the actual measurements of one particular day were chosen among the ten available days. For the other four, the numerical input relating to each second of the synthetic day was constructed by means of a statistical assessment of the actual measures obtained at each corresponding second of the ten actual days. The Hermite polynomial chaos expansion was selected for the last approach. Results have shown a significant variability of airflow for both experimentally measured input and output signals. By using the experimental signal expansion through Hermite polynomials the experimental and numerical values give satisfactory results.

Compact Active Quenching Circuit for Single Photon Avalanche Diodes Arrays

2017 ◽  
Vol 26 (10) ◽  
pp. 1750149
Author(s):  
Lixia Zheng ◽  
Huan Hu ◽  
Ziqing Weng ◽  
Qun Yao ◽  
Jin Wu ◽  
...  
Keyword(s):  
Power Consumption ◽  
Small Area ◽  
Single Photon ◽  
Low Power Consumption ◽  
Cmos Process ◽  
Experimental Measurements ◽  
Avalanche Diode ◽  
Avalanche Diodes ◽  
Area Occupation ◽  
Sensing Time

A compact quenching circuit for Single Photon Avalanche Diode (SPAD) arrays is presented. The proposed circuit preserves the advantages of small area occupation and low power consumption, since it mainly adopts the junction capacitance of the detector to sense the avalanche current. The sensing time is now limited more by the detector rather than the circuit itself. Fabricated in TSMC standard 0.35[Formula: see text][Formula: see text]m CMOS process, the proposed circuit only occupies an area of 20[Formula: see text][Formula: see text]m[Formula: see text][Formula: see text][Formula: see text]31[Formula: see text][Formula: see text]m and can operate properly with the detector biased up to 5[Formula: see text]V above breakdown. The circuit functionality has been verified by experimental measurements, operating with 64[Formula: see text][Formula: see text][Formula: see text]64 InGaAs/InP single photon avalanche diode arrays for time-of-flight-based applications.

A Comprehensive Survey on Edge Computing for the IoT

2019 ◽  
pp. 37-45 ◽  
Author(s):  
Pravin A. ◽  
Prem Jacob ◽  
G. Nagarajan
Keyword(s):  
Cloud Computing ◽  
Power Consumption ◽  
Response Time ◽  
Real World ◽  
Data Security ◽  
Edge Computing ◽  
Consumption Data ◽  
Real World Applications ◽  
Comprehensive Survey ◽  
Overall Performance

The IoT concept is used in various applications and it uses different devices for collecting data and processing the data. Various sets of devices such as sensors generate a large amount of data and the data will be forwarded to the appropriate devices for processing. The devices used will range from small devices to larger devices. The edge computing becomes the major role in overcoming the difficulties in cloud computing, the nearby devices are used as servers for providing better services. Most of the issues such as power consumption, data security, and response time will be addressed. The IoT plays a major role in many real-world applications. In this chapter, the basics and the use of the Edge computing concept in different applications are discussed. Edge computing can be used to increase the overall performance of the IoT. The performance of various applications in terms of edge computing and other methodologies are analyzed.

Modeling the Effect of Power Consumption in Automated Driving Systems on Vehicle Energy Efficiency for Real-World Driving in California

2019 ◽  
Vol 2673 (4) ◽  
pp. 339-347
Author(s):  
Karim Hamza ◽  
John Willard ◽  
Kang-Ching Chu ◽  
Kenneth P. Laberteaux
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Real World ◽  
Travel Demand ◽  
Survey Study ◽  
Automated Driving ◽  
Simulation Code ◽  
Transportation Energy ◽  
Minimal Impact ◽  
The Impact

Vehicle automation has drawn much attention in recent years, as it is perceived to usher in new levels of safety, convenience, and energy efficiency in transportation. Much uncertainty and speculation still exist regarding how automated driving (AD) would affect the overall transportation energy, as a result of some factors that are difficult to predict, such as changes in driving patterns and induced travel demand. There is also much speculation about the optimum vehicle powertrain for which AD systems are to be mounted. This study focuses on a less discussed, less speculative issue that pertains to both transportation energy efficiency and powertrain suitability. The impact of the power consumption in an AD system (for sensors, data processing, and vehicle controls) is analyzed for various powertrains via a publicly open-source simulation code, for more than 59,000 real-world vehicle trips obtained from the California Household Travel Survey. Study of scenarios of power consumption in the AD system that range from present-day values (about 3 kW) to future targets (0.5 kW) reveal interesting trends in vehicle energy efficiency. At 0.5 kW power consumption, the AD system can be of minimal impact to vehicle efficiency; however, at present-day levels of AD power consumption, the electric driving range (for electric vehicles and plug-in hybrids) could be shortened by 27–47% and fuel consumption could increase by up to 37% compared with the same vehicle model with no AD system.

scholarly journals Modeling Real-World Flexibility of Residential Power Consumption

2018 ◽  
Author(s):  
Nasrin Sadeghianpourhamami ◽  
Dries F. Benoit ◽  
Dirk Deschrijver ◽  
Chris Develder
Keyword(s):  
Power Consumption ◽  
Real World
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