Pub Date : 2024-01-15DOI: 10.1109/LES.2024.3354179
Lucas A. Rabioglio;M. C. Cebedio;L. Arnone;L. De Micco;J. Castiñeira Moreira
This letter focuses on the field-programmable gate array (FPGA) implementation of a Class A Middleton noise estimator, aiming to enhance its efficiency and performance. The inherent algorithm of the estimator undergoes strategic enhancements, leveraging median approximations. This endeavor leads to the development of a more streamlined and expeditious architecture. The research not only introduces the refined architecture but also conducts a comparative analysis of its attributes. The outcomes of this investigation show the benefits of algorithmic optimization, as the execution times achieved in hardware significantly surpass those attainable through software-based implementation. This underscores the practicality of the algorithmic refinement and also the notable advantages of the FPGA-based execution in terms of computational speed.
这封信的重点是现场可编程门阵列（FPGA）的 A 类 Middleton 噪声估计器的实现，旨在提高其效率和性能。利用中值近似对估计器的固有算法进行了战略性改进。这一努力导致开发出一种更精简、更快速的架构。研究不仅介绍了改进后的架构，还对其属性进行了比较分析。研究结果表明了算法优化的好处，因为在硬件上实现的执行时间大大超过了通过软件实现的执行时间。这凸显了算法改进的实用性，以及基于 FPGA 的执行在计算速度方面的显著优势。
{"title":"Middleton Class A Noise Median Estimator: FPGA and Software Implementation","authors":"Lucas A. Rabioglio;M. C. Cebedio;L. Arnone;L. De Micco;J. Castiñeira Moreira","doi":"10.1109/LES.2024.3354179","DOIUrl":"10.1109/LES.2024.3354179","url":null,"abstract":"This letter focuses on the field-programmable gate array (FPGA) implementation of a Class A Middleton noise estimator, aiming to enhance its efficiency and performance. The inherent algorithm of the estimator undergoes strategic enhancements, leveraging median approximations. This endeavor leads to the development of a more streamlined and expeditious architecture. The research not only introduces the refined architecture but also conducts a comparative analysis of its attributes. The outcomes of this investigation show the benefits of algorithmic optimization, as the execution times achieved in hardware significantly surpass those attainable through software-based implementation. This underscores the practicality of the algorithmic refinement and also the notable advantages of the FPGA-based execution in terms of computational speed.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139954509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-10DOI: 10.1109/les.2024.3352540
Mohd. Tasleem Khan, Jinti Hazarika
{"title":"An Area and Energy Efficient Serial-Multiplier","authors":"Mohd. Tasleem Khan, Jinti Hazarika","doi":"10.1109/les.2024.3352540","DOIUrl":"https://doi.org/10.1109/les.2024.3352540","url":null,"abstract":"","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139954453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-04DOI: 10.1109/LES.2023.3348705
Bashra Kadhim Oleiwi;Ahmad H. Sabry
As per literature, there is a potential for energy savings of (5% to 20%) using building embedded control systems. This letter aims to control a house air-conditioning system using model predictive control (MPC) with a neural state space prediction (NSSP) Model to maintain interior temperature set-point and reduce energy consumption. Here, we present a high-fidelity model that is validated by an experimental prototype of a house air-conditioning system that is controlled using a nonlinear MPC. The house air-conditioning system models the air-conditioner and the thermal dynamics of the house. The outdoor temperature is modeled by simulated signals and real measurements. The controller problem is to maintain a house temperature within 20 °C to 22 °C and to minimize energy costs. Compared with the generic nonlinear MPC controller, multistage nonlinear MPC provides a more flexible and efficient way to implement MPC with staged costs and constraints.
根据文献记载，使用楼宇嵌入式控制系统可节约能源（5% 至 20%）。这封信旨在利用神经状态空间预测模型（NSSP）对室内空调系统进行模型预测控制（MPC），以保持室内温度设定点并降低能耗。在此，我们提出了一个高保真模型，并通过使用非线性 MPC 控制的房屋空调系统的实验原型进行了验证。室内空调系统以空调和室内热动态为模型。室外温度由模拟信号和实际测量数据建模。控制器的问题是将室内温度控制在 20 °C 至 22 °C 之间，并最大限度地降低能源成本。与一般的非线性 MPC 控制器相比，多级非线性 MPC 提供了一种更灵活、更高效的方法来实现具有分阶段成本和约束条件的 MPC。
{"title":"Controlling a House’s Air-Conditioning Using Nonlinear Model Predictive Control","authors":"Bashra Kadhim Oleiwi;Ahmad H. Sabry","doi":"10.1109/LES.2023.3348705","DOIUrl":"10.1109/LES.2023.3348705","url":null,"abstract":"As per literature, there is a potential for energy savings of (5% to 20%) using building embedded control systems. This letter aims to control a house air-conditioning system using model predictive control (MPC) with a neural state space prediction (NSSP) Model to maintain interior temperature set-point and reduce energy consumption. Here, we present a high-fidelity model that is validated by an experimental prototype of a house air-conditioning system that is controlled using a nonlinear MPC. The house air-conditioning system models the air-conditioner and the thermal dynamics of the house. The outdoor temperature is modeled by simulated signals and real measurements. The controller problem is to maintain a house temperature within 20 °C to 22 °C and to minimize energy costs. Compared with the generic nonlinear MPC controller, multistage nonlinear MPC provides a more flexible and efficient way to implement MPC with staged costs and constraints.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139954502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-29DOI: 10.1109/les.2023.3348499
Arya Motamedhashemi, Bardia Safaei, Amir Mahdi Hosseini Monazzah, Alireza Ejlali
Fog devices in fog computing frameworks are responsible for fetching and executing the tasks submitted by the deployed resource-constraint embedded edge devices. Based on the availability of resources, tasks are offloaded to the virtual machines hosted by the fog devices. These tasks may then get scheduled to guarantee a number of efficiency-related metrics. While throughput has a decisive impact on the timely execution of tasks, the appropriate utilization of this metric has not been considered in the existing mechanisms. In this letter, we first discuss the proper use of this objective in the fitness function of meta-heuristic algorithms. Then, we explain that adopting throughput by the fitness functions in the form of two conventionally used weighted-sum, and fractional techniques may ignore solutions with a better guarantee ratio. Consequently, we propose a novel approach called DATA to be replaced with these two old approaches. DATA is a throughput, and deadline-aware task scheduling mechanism for time-sensitive fog frameworks, which its fitness function utilizes genetic optimization by encoding the solutions into chromosomes. It uses single gene mutation and two-point crossover. In this approach, two populations are considered to search the problem space. The main population is evaluated based on the guarantee ratio, while the helper population is evaluated based on the throughput. Furthermore, the helper population uses weighted-sum. The initial population is generated randomly by the uniform distribution, to provide a load-balancing. Based on our extensive evaluations, the selected solution by DATA provides the highest guarantee ratio, while having the lowest possible makespan.
雾计算框架中的雾设备负责获取和执行已部署的资源受限嵌入式边缘设备提交的任务。根据资源的可用性，任务会被卸载到由雾设备托管的虚拟机上。然后，这些任务会得到调度，以保证一系列与效率相关的指标。虽然吞吐量对任务的及时执行有决定性影响，但现有机制并未考虑如何合理利用这一指标。在这封信中，我们首先讨论了在元启发式算法的拟合函数中如何正确使用这一目标。然后，我们解释说，采用加权求和和分数技术这两种传统形式的拟合函数来计算吞吐量，可能会忽略保证率更高的解决方案。因此，我们提出了一种名为 DATA 的新方法来取代这两种旧方法。DATA 是一种吞吐量和截止日期感知任务调度机制，适用于对时间敏感的雾框架，其适配函数利用遗传优化将解决方案编码成染色体。它使用单基因突变和两点交叉。在这种方法中，考虑了两个种群来搜索问题空间。主种群根据保证率进行评估，而辅助种群则根据吞吐量进行评估。此外，辅助种群使用加权和。初始种群由均匀分布随机生成，以提供负载平衡。根据我们的广泛评估，DATA 选出的解决方案提供了最高的保证率，同时具有尽可能低的时间跨度。
{"title":"DATA: Throughput and Deadline-Aware Genetic Approach for Task Scheduling in Fog Networks","authors":"Arya Motamedhashemi, Bardia Safaei, Amir Mahdi Hosseini Monazzah, Alireza Ejlali","doi":"10.1109/les.2023.3348499","DOIUrl":"https://doi.org/10.1109/les.2023.3348499","url":null,"abstract":"Fog devices in fog computing frameworks are responsible for fetching and executing the tasks submitted by the deployed resource-constraint embedded edge devices. Based on the availability of resources, tasks are offloaded to the virtual machines hosted by the fog devices. These tasks may then get scheduled to guarantee a number of efficiency-related metrics. While throughput has a decisive impact on the timely execution of tasks, the appropriate utilization of this metric has not been considered in the existing mechanisms. In this letter, we first discuss the proper use of this objective in the fitness function of meta-heuristic algorithms. Then, we explain that adopting throughput by the fitness functions in the form of two conventionally used weighted-sum, and fractional techniques may ignore solutions with a better guarantee ratio. Consequently, we propose a novel approach called DATA to be replaced with these two old approaches. DATA is a throughput, and deadline-aware task scheduling mechanism for time-sensitive fog frameworks, which its fitness function utilizes genetic optimization by encoding the solutions into chromosomes. It uses single gene mutation and two-point crossover. In this approach, two populations are considered to search the problem space. The main population is evaluated based on the guarantee ratio, while the helper population is evaluated based on the throughput. Furthermore, the helper population uses weighted-sum. The initial population is generated randomly by the uniform distribution, to provide a load-balancing. Based on our extensive evaluations, the selected solution by DATA provides the highest guarantee ratio, while having the lowest possible makespan.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-27DOI: 10.1109/LES.2023.3347607
Atul Kumar;Shirshendu Das;Basant Subba
Modern chipmultiprocessors (CMPs) use third-party intellectual properties (IPs) to reduce design costs and meet deadlines. The cores in the CMP has their own private cache memories and all the cores share a common large sized last level cache (LLC). All the components of CMP, including cores and cache memories, are connected through a network-on-chip (NoC). Most of the NoC components have third-party IPs. Some of these IPs may be malicious and act as Hardware Trojan (HT). In this letter, we propose an HT-base attack that targets the LLC resizing techniques. The LLC resizing techniques are used to reduce the energy consumption of the LLC by shutting down unused parts of the LLC. The proposed attack can misuse the properties of these resizing techniques to reduce their energy saving up to 58%. The proposed attack can also reduce the system performance up to 18%.
{"title":"HTree: Hardware Trojan Attack on Cache Resizing Policies","authors":"Atul Kumar;Shirshendu Das;Basant Subba","doi":"10.1109/LES.2023.3347607","DOIUrl":"https://doi.org/10.1109/LES.2023.3347607","url":null,"abstract":"Modern chipmultiprocessors (CMPs) use third-party intellectual properties (IPs) to reduce design costs and meet deadlines. The cores in the CMP has their own private cache memories and all the cores share a common large sized last level cache (LLC). All the components of CMP, including cores and cache memories, are connected through a network-on-chip (NoC). Most of the NoC components have third-party IPs. Some of these IPs may be malicious and act as Hardware Trojan (HT). In this letter, we propose an HT-base attack that targets the LLC resizing techniques. The LLC resizing techniques are used to reduce the energy consumption of the LLC by shutting down unused parts of the LLC. The proposed attack can misuse the properties of these resizing techniques to reduce their energy saving up to 58%. The proposed attack can also reduce the system performance up to 18%.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142091015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-15DOI: 10.1109/LES.2023.3343641
M. Coelho;L. Santiago;D. Araújo;A. Navarro;N. B. Carvalho
Emergency alert systems (EASs) have been deployed in some countries in order to broadcast emergency alerts and warning messages to the public. In this letter, we describe an innovative electronic embedded solution, named Firetec switch, intended to be placed in the FM radio stations. This switch will be supported by a server placed at the authorized officials, with the capability to generate the audio alerting messages. One interesting challenge is to deliver the messages only to the local public, in the catastrophe neighborhood, by using FM radio stations. This letter focuses on the description of the Firetec switch hardware and software.
{"title":"A Low-Cost Embedded System to Support Broadcasting Emergency Messages Through FM Radio Stations","authors":"M. Coelho;L. Santiago;D. Araújo;A. Navarro;N. B. Carvalho","doi":"10.1109/LES.2023.3343641","DOIUrl":"https://doi.org/10.1109/LES.2023.3343641","url":null,"abstract":"Emergency alert systems (EASs) have been deployed in some countries in order to broadcast emergency alerts and warning messages to the public. In this letter, we describe an innovative electronic embedded solution, named Firetec switch, intended to be placed in the FM radio stations. This switch will be supported by a server placed at the authorized officials, with the capability to generate the audio alerting messages. One interesting challenge is to deliver the messages only to the local public, in the catastrophe neighborhood, by using FM radio stations. This letter focuses on the description of the Firetec switch hardware and software.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142091007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1109/LES.2023.3343293
Xochitl Maya;Adrián E. Soto;Ángel A. Vázquez;Juan G. Avalos;Giovanny Sanchez;Juan C. Sánchez
In realistic sound scenarios, cutting-edge active noise control (ANC) systems still suffer critical instabilities since these systems works under impulsive noise signals. To decrease the negative impact of this noise, several authors have made extraordinary efforts to develop efficient algorithms in terms of convergence speed and misadjustment. However, these algorithms still exhibits limited convergence capabilities. In this letter, we present for the first time, the development of a switching algorithm based on the maximum versoria criterion (MVC) algorithm. Our results demonstrate that the proposed switching algorithm exhibits good convergence properties while maintaining a lower-computational cost when compared with existing algorithms.
{"title":"A New Switching MVC Algorithm for Active Impulsive Noise Control","authors":"Xochitl Maya;Adrián E. Soto;Ángel A. Vázquez;Juan G. Avalos;Giovanny Sanchez;Juan C. Sánchez","doi":"10.1109/LES.2023.3343293","DOIUrl":"https://doi.org/10.1109/LES.2023.3343293","url":null,"abstract":"In realistic sound scenarios, cutting-edge active noise control (ANC) systems still suffer critical instabilities since these systems works under impulsive noise signals. To decrease the negative impact of this noise, several authors have made extraordinary efforts to develop efficient algorithms in terms of convergence speed and misadjustment. However, these algorithms still exhibits limited convergence capabilities. In this letter, we present for the first time, the development of a switching algorithm based on the maximum versoria criterion (MVC) algorithm. Our results demonstrate that the proposed switching algorithm exhibits good convergence properties while maintaining a lower-computational cost when compared with existing algorithms.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1109/LES.2023.3343030
Romina Soledad Molina;Iván René Morales;Maria Liz Crespo;Veronica Gil Costa;Sergio Carrato;Giovanni Ramponi
Machine learning (ML) models have demonstrated discriminative and representative learning capabilities over a wide range of applications, even at the cost of high-computational complexity. Due to their parallel processing capabilities, reconfigurability, and low-power consumption, systems on chip based on a field programmable gate array (SoC/FPGA) have been used to face this challenge. Nevertheless, SoC/FPGA devices are resource-constrained, which implies the need for optimal use of technology for the computation and storage operations involved in ML-based inference. Consequently, mapping a deep neural network (DNN) architecture to a SoC/FPGA requires compression strategies to obtain a hardware design with a good compromise between effectiveness, memory footprint, and inference time. This letter presents an efficient end-to-end workflow for deploying DNNs on an SoC/FPGA by integrating hyperparameter tuning through Bayesian optimization (BO) with an ensemble of compression techniques.
机器学习（ML）模型已在广泛的应用中展示出辨别和代表性学习能力，即使代价是高计算复杂性。基于现场可编程门阵列（SoC/FPGA）的片上系统具有并行处理能力、可重新配置性和低功耗等特点，因此被用来应对这一挑战。然而，SoC/FPGA 设备的资源有限，这意味着需要在基于 ML 的推理所涉及的计算和存储操作中优化使用技术。因此，将深度神经网络（DNN）架构映射到 SoC/FPGA 需要采用压缩策略，以获得在有效性、内存占用和推理时间之间取得良好折衷的硬件设计。本文介绍了一种高效的端到端工作流程，通过贝叶斯优化（BO）将超参数调整与一系列压缩技术相结合，在 SoC/FPGA 上部署 DNN。
{"title":"An End-to-End Workflow to Efficiently Compress and Deploy DNN Classifiers on SoC/FPGA","authors":"Romina Soledad Molina;Iván René Morales;Maria Liz Crespo;Veronica Gil Costa;Sergio Carrato;Giovanni Ramponi","doi":"10.1109/LES.2023.3343030","DOIUrl":"https://doi.org/10.1109/LES.2023.3343030","url":null,"abstract":"Machine learning (ML) models have demonstrated discriminative and representative learning capabilities over a wide range of applications, even at the cost of high-computational complexity. Due to their parallel processing capabilities, reconfigurability, and low-power consumption, systems on chip based on a field programmable gate array (SoC/FPGA) have been used to face this challenge. Nevertheless, SoC/FPGA devices are resource-constrained, which implies the need for optimal use of technology for the computation and storage operations involved in ML-based inference. Consequently, mapping a deep neural network (DNN) architecture to a SoC/FPGA requires compression strategies to obtain a hardware design with a good compromise between effectiveness, memory footprint, and inference time. This letter presents an efficient end-to-end workflow for deploying DNNs on an SoC/FPGA by integrating hyperparameter tuning through Bayesian optimization (BO) with an ensemble of compression techniques.","PeriodicalId":56143,"journal":{"name":"IEEE Embedded Systems Letters","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142091036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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