2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)最新文献_第2页

JSEVAsync: An Asynchronous Event-based Framework to Energy Saving on IoT Devices JSEVAsync:基于异步事件的物联网设备节能框架

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9965063

Fernando L. Oliveira, J. Mattos

{"title":"JSEVAsync: An Asynchronous Event-based Framework to Energy Saving on IoT Devices","authors":"Fernando L. Oliveira, J. Mattos","doi":"10.1109/SBESC56799.2022.9965063","DOIUrl":"https://doi.org/10.1109/SBESC56799.2022.9965063","url":null,"abstract":"Typically the Internet of Things devices are constrained in terms of processing, memory, and energy consumption. Energy consumption is a critical aspect of these devices, being heavily impacted by how programs are developed, and it becomes more evident in interpreted languages that naturally demand more resources. Commonly embedded software development uses Time-triggered (TT) and Event-triggered (ET) architectures to design embedded projects. However, the TT strategy can consume more energy due to the polling method; in contrast, the ET approach can be energy-efficient but cannot deal with multiple events. This paper introduces JSEVAsync, a framework to help developers to design applications using JavaScript language for IoT devices that combine the best parts of TT and ET architectures. This approach uses JavaScript's non-blocking concept as a development interface to structure the algorithms into asynchronous events. To validate it, we compare C- and JavaScript-based applications and analyze the results from the energy consumption perspective. We found that writing code through JSEVAsync can be up to 21% more energy efficient than the traditional method. Moreover, JavaScript can improve design-time aspects such as readability, maintainability, and code reuse.","PeriodicalId":130479,"journal":{"name":"2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134111946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Load Balancing Based on Multimedia Task Division for Reactive WSNs: Case Study for Pest Management 基于多媒体任务划分的响应式wsn负载均衡:害虫管理案例研究

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9965097

Weslen Souza, L. Brisolara, P. Ferreira

{"title":"Load Balancing Based on Multimedia Task Division for Reactive WSNs: Case Study for Pest Management","authors":"Weslen Souza, L. Brisolara, P. Ferreira","doi":"10.1109/SBESC56799.2022.9965097","DOIUrl":"https://doi.org/10.1109/SBESC56799.2022.9965097","url":null,"abstract":"Wireless Sensor Networks have been widely used for monitoring and data collection. Technological advances allowed the integration of multimedia devices into these networks, giving rise to new possible applications. The nodes that make up these networks are commonly located in external environments where they are exclusively powered by batteries, thus the network lifetime depends on the charge of these batteries. To maximize the useful life of the network as a whole, load balancing techniques are proposed with the aim of promoting a more homogeneous energy consumption by all the nodes, preventing only a few nodes from working in excess and dying prematurely. Most of the studies identified in the literature for reactive WSN only address networks with overlapping sensing, making the decision of which of the nodes that detected this same event should process it. In this work, networks without sensing overlap are addressed, where a load balancing strategy based on task division is proposed. An event is split into several smaller multimedia processing subtasks, which are distributed to neighboring nodes that are able to perform the processing. Through experiments, we show the improvements of around 29% achieved by the proposed approach, when compared to a WSN that does not use any load balancing technique.","PeriodicalId":130479,"journal":{"name":"2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122181815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrating Autonomous Vehicle Simulation Tools using SmartData 使用SmartData集成自动驾驶汽车仿真工具

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9964834

José Luís Conradi Hoffmann, Leonardo Passig Horstmann, A. A. Fröhlich

{"title":"Integrating Autonomous Vehicle Simulation Tools using SmartData","authors":"José Luís Conradi Hoffmann, Leonardo Passig Horstmann, A. A. Fröhlich","doi":"10.1109/SBESC56799.2022.9964834","DOIUrl":"https://doi.org/10.1109/SBESC56799.2022.9964834","url":null,"abstract":"This work proposes a SmartData-based middleware to integrate Autonomous Systems Simulators and external tools. The interface models the data used on a simulator and creates an intermediary layer between the simulator and the external tools by defining the inputs and outputs as SmartData. A message bus is used for communication between SmartData following their interest relations. Messages are exchanged following a specific protocol such as CAN, TSTP, and EtherCat. However, the architecture presented is agnostic of protocol. The presented interface eases the integration of the autonomous system simulation with other simulators (e.g., Network Simulators), Cloud services, fault injection mechanisms, Digital Twins, and Hardware-in-the-loop scenarios. Moreover, this interface allows transparent, runtime component replacement and time synchronization, the modularization of the components of the system, and the addition of security aspects in the simulation. After presenting the interface proposed, we present a case-study application with an autonomous vehicle simulation using CARLA and measure the end-to-end delay and overhead incurred in the simulation.","PeriodicalId":130479,"journal":{"name":"2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114250301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

On the Effect of Heterogeneous Robot Fleets on Smart Warehouses' Order Time, Energy, and Operating Costs 异构机器人车队对智能仓库订单时间、能源和运营成本的影响

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9964584

George S. Oliveira, J. T. Carvalho, P. Plentz

引用次数: 0

Feature Selection in Machine Learning for Knocking Noise detection 敲敲噪声检测的机器学习特征选择

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9964726

Maria Eduarda Rosa da Silva, G. Gracioli, G. Araújo

{"title":"Feature Selection in Machine Learning for Knocking Noise detection","authors":"Maria Eduarda Rosa da Silva, G. Gracioli, G. Araújo","doi":"10.1109/SBESC56799.2022.9964726","DOIUrl":"https://doi.org/10.1109/SBESC56799.2022.9964726","url":null,"abstract":"The search for effective methods to obtain an accurate detection of faults in cyber-physical systems grows constantly. Usually, a considerable amount of data generated by sensors is the source of any data-based analysis. In this context, the application of Machine Learning algorithms to identify faults has gained popularity and acceptance due to the high performance and low cost compared to other techniques. To improve the performance of such anomaly detection algorithms and have greater accuracy for failure identification, some strategies can be addressed, such as selecting the features that best describe the failure. For this, Features Selection is performed to identify significant features in a dataset. In this paper we present a comparison of 6 feature selection algorithms that are used to select the best features to detect the knocking noise fault in automotive combustion engines. By collecting and using data from an engine electronic control unit (ECU), we show that features selection can reduce the number of selected features in a failure classifier by 55% (from 9 to 5) with an improvement of the detection precision by 2%.","PeriodicalId":130479,"journal":{"name":"2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125066481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Adaptive TDMA Approach for Improving Reliability and Performance in WBAN under Heterogeneous Traffic and Interference 一种提高异构业务和干扰下WBAN可靠性和性能的自适应TDMA方法

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9964592

Jorge F. Herculano, Willians de P. Pereira, A. S. Sá

引用次数: 2

Assessment and Optimization of 1D CNN Model for Human Activity Recognition 用于人体活动识别的1D CNN模型评估与优化

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9964520

Rafael Schild Reusch, L. Juracy, Fernando Gehm Moraes

{"title":"Assessment and Optimization of 1D CNN Model for Human Activity Recognition","authors":"Rafael Schild Reusch, L. Juracy, Fernando Gehm Moraes","doi":"10.1109/SBESC56799.2022.9964520","DOIUrl":"https://doi.org/10.1109/SBESC56799.2022.9964520","url":null,"abstract":"Artificial Intelligence (AI) solves complex tasks like human activity and speech recognition. Accuracy-driven AI models introduced new challenges related to their applicability in resource-scarce systems. In Human Activity Recognition (HAR), state-of-the-art presents proposals using complex multi-layer LSTM networks. The literature states that LSTM networks are suitable for treating temporal-series data, a key feature for HAR. Most works in the literature seek the best possible accuracy, with few evaluating the overall computational cost to run the inference phase. In HAR, low-power IoT devices such as wearable sensors are widely used as data-gathering devices, but little effort is made to deploy AI technology in these devices. Most studies suggest an approach using edge devices or cloud computing architectures, where the end-device task is to gather and send data to the edge/cloud device. Most voice assistants, such as Amazon's Alexa and Google, use this architecture. In real-life applications, mainly in the healthcare industry, relying only on edge/cloud devices is not acceptable since these devices are not always available or reachable. The objective of this work is to evaluate the accuracy of convolutional networks with a simpler architecture, using 1D convolution, for HAR. The motivation for using networks with simpler network architectures is the possibility of embedding them in power- and memory-constrained devices.","PeriodicalId":130479,"journal":{"name":"2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123173119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Comparison of Different Adaptable Cache Bypassing Approaches 不同自适应缓存绕过方法的比较

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9965178

Mariana Carmin, L. A. Ensina, M. Alves

{"title":"Comparison of Different Adaptable Cache Bypassing Approaches","authors":"Mariana Carmin, L. A. Ensina, M. Alves","doi":"10.1109/SBESC56799.2022.9965178","DOIUrl":"https://doi.org/10.1109/SBESC56799.2022.9965178","url":null,"abstract":"Most modern microprocessors have a deep cache hierarchy to hide the latency of accessing the main memory. Thus, with the increase in the number of cores, the shared Last-Level Cache (LLC) also increases, which consumes a large portion of the chip's total power and area. The same cache hierarchy can represent an extra latency barrier for applications with poor temporal and spatial locality. Therefore, sophisticated solutions should ensure optimal resource utilization to mitigate cache problems. In this scenario, an adaptive cache mechanism can benefit such applications, improving general system performance and decreasing energy consumption. When multiple programs are running, adapting the use of the LLC for each application avoids cache conflicts and cache pollution, increasing system performance. In this paper, we assess two approaches based on regression and classification models to adapt the use of the LLC during run-time, both using hardware counters. Analyzing the efficiency and overhead of each model through SPEC CPU 2006 and 2017, we observe a better performance for the classification model based on the Random Forest algorithm for both single and multi-program workloads.","PeriodicalId":130479,"journal":{"name":"2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121699973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing a Multiple-User Wearable Edge AI system towards Human Activity Recognition 面向人类活动识别的多用户可穿戴边缘人工智能系统设计

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9964915

M. C. Silva, A. G. Bianchi, R. A. R. Oliveira, S. Ribeiro

引用次数: 0

Distributed Learning using Consensus on Edge AI 基于边缘AI共识的分布式学习

2022 XII Brazilian Symposium on Computing Systems Engineering (SBESC) Pub Date : 2022-11-21 DOI: 10.1109/SBESC56799.2022.9965153

Samuel Amico Fidelis, Márcio Castro, Frank Siqueira

引用次数: 0