Sustainable Computing-Informatics & Systems最新文献_第5页

Occupancy prediction: A comparative study of static and MOTIF time series features using WiFi Syslog data 占用预测：利用 WiFi 系统日志数据对静态和 MOTIF 时间序列特征进行比较研究

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-10-04 DOI: 10.1016/j.suscom.2024.101040

Bassam A. Abdelghani, Ahlam Al Mohammad, Jamal Dari, Mina Maleki, Shadi Banitaan

Occupancy prediction has been the subject of ongoing research, employing various methods and data sources to improve occupancy prediction accuracy and energy efficiency in buildings. Precise occupancy prediction is crucial for optimizing energy usage, ensuring occupant comfort, and enhancing building management. With the increasing demand for intelligent building management systems, robust and accurate occupancy prediction models are becoming more critical. This study aims to predict building occupancy using WiFi Syslog files from three different datasets: an open-source dataset from the University of Massachusetts Dartmouth, a new locally collected dataset from the dental school at the University of Detroit Mercy, and finally, a dataset from an office building in Berkeley, California. Two types of features, static features, and MOTIF time series features, were extracted from the datasets to process and compare their performance in occupancy prediction.

The first step of the proposed framework consisted of selecting the most suitable time range to compare occupancy prediction models between different datasets. It was concluded that this analysis was best conducted semester by semester. Multiple regression algorithms, such as random forest and LightGBM, were applied in the following step, along with advanced ensemble techniques, including stacking and blending, to assess the model. The stacking regression showed the best results for static features across all datasets. It achieved a Coefficient of Determination (

R^{2}

) of 0.9540 in the first dataset, 0.9482 in the second, and 0.9977 in the third. For MOTIF features, however, the best algorithm depended on the dataset. All algorithms performed similarly in the first dataset, with

R^{2}

of 0.956. In contrast, LightGBM and the Stacking Regressor had better results than the others in the second dataset, with a low

R^{2}

of 0.531 due to dataset-specific differences. The stacking regression once again delivered the best results in the last dataset with an

R^{2}

of 0.9967.

占用率预测一直是持续研究的主题，它采用各种方法和数据源来提高占用率预测的准确性和建筑物的能源效率。精确的占用预测对于优化能源使用、确保居住舒适度和加强楼宇管理至关重要。随着对智能楼宇管理系统的需求日益增长，稳健而准确的占用预测模型变得越来越重要。本研究旨在利用来自三个不同数据集的 WiFi 系统日志文件预测楼宇占用情况：一个来自马萨诸塞大学达特茅斯分校的开源数据集，一个来自底特律梅西大学牙科学院的本地收集的新数据集，以及一个来自加利福尼亚州伯克利办公楼的数据集。从数据集中提取了两种类型的特征，即静态特征和 MOTIF 时间序列特征，以处理和比较它们在占用率预测中的性能。得出的结论是，这种分析最好按学期进行。在接下来的步骤中，应用了随机森林和 LightGBM 等多重回归算法，以及包括堆叠和混合在内的高级集合技术来评估模型。在所有数据集的静态特征方面，堆叠回归显示出最佳结果。第一个数据集的判定系数（R2）为 0.9540，第二个数据集为 0.9482，第三个数据集为 0.9977。然而，对于 MOTIF 特征，最佳算法取决于数据集。在第一个数据集中，所有算法的表现相似，R2 为 0.956。相比之下，LightGBM 和堆叠回归算法在第二个数据集中的表现要好于其他算法，但由于特定数据集的差异，R2 较低，仅为 0.531。在最后一个数据集中，堆叠回归再次取得了最佳结果，R2 为 0.9967。

{"title":"Occupancy prediction: A comparative study of static and MOTIF time series features using WiFi Syslog data","authors":"Bassam A. Abdelghani, Ahlam Al Mohammad, Jamal Dari, Mina Maleki, Shadi Banitaan","doi":"10.1016/j.suscom.2024.101040","DOIUrl":"10.1016/j.suscom.2024.101040","url":null,"abstract":"<div><div>Occupancy prediction has been the subject of ongoing research, employing various methods and data sources to improve occupancy prediction accuracy and energy efficiency in buildings. Precise occupancy prediction is crucial for optimizing energy usage, ensuring occupant comfort, and enhancing building management. With the increasing demand for intelligent building management systems, robust and accurate occupancy prediction models are becoming more critical. This study aims to predict building occupancy using WiFi Syslog files from three different datasets: an open-source dataset from the University of Massachusetts Dartmouth, a new locally collected dataset from the dental school at the University of Detroit Mercy, and finally, a dataset from an office building in Berkeley, California. Two types of features, static features, and MOTIF time series features, were extracted from the datasets to process and compare their performance in occupancy prediction.</div><div>The first step of the proposed framework consisted of selecting the most suitable time range to compare occupancy prediction models between different datasets. It was concluded that this analysis was best conducted semester by semester. Multiple regression algorithms, such as random forest and LightGBM, were applied in the following step, along with advanced ensemble techniques, including stacking and blending, to assess the model. The stacking regression showed the best results for static features across all datasets. It achieved a Coefficient of Determination (<span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>) of 0.9540 in the first dataset, 0.9482 in the second, and 0.9977 in the third. For MOTIF features, however, the best algorithm depended on the dataset. All algorithms performed similarly in the first dataset, with <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> of 0.956. In contrast, LightGBM and the Stacking Regressor had better results than the others in the second dataset, with a low <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> of 0.531 due to dataset-specific differences. The stacking regression once again delivered the best results in the last dataset with an <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> of 0.9967.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101040"},"PeriodicalIF":3.8,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A scenario-customizable and visual-rendering simulator for on-vehicle vibration energy harvesting 用于车载振动能量采集的可定制场景和可视化渲染模拟器

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-09-23 DOI: 10.1016/j.suscom.2024.101039

Fangcheng Guo , Jingjin Li , Chung Ket Thein , Anqi Gao , Jianfeng Ren , Chang Heon Lee , Jiawei Li , Tianxiang Cui , Heng Yu

The rising demand for renewable energy supply in standalone computing devices has led to the emergence of vibration energy harvesting (VEH) to overcome technical and environmental challenges. For instance, VEH is desirable in IoT scenarios where maintaining a battery supply is non-sustainable or impractical due to many devices or remote circumstances. VEH can be environmentally friendly given that it reduces the reliance on traditional battery production and usage, thus reducing the carbon footprint and chemical waste in disposable batteries. However, a significant hurdle in VEH adoption is the lack of effective simulation tools for generating various application scenarios to describe, validate, or predict the efficacy of the VEH-based devices. It is necessary for designing and implementing a VEH simulator for a variety of realistic application scenarios. Being the first of its kind, this study presents a scenario-customizable and visual-rendering VEH simulation system based on the Unity3D Engine. The proposed simulator features a modular design that consists of several key functional components including vibration scenarios’ creation and manipulation, VEH model specification, Unity-Python Co-computing mechanism, and 3D visualization. This paper also presents two AI-based case studies leveraging the functionality and data provided by the simulator to demonstrate its potential for data-driven research and applications.

独立计算设备对可再生能源供应的需求日益增长，因此出现了振动能量采集（VEH）技术，以克服技术和环境挑战。例如，在物联网应用场景中，由于设备众多或环境偏远，维持电池供应是不可持续或不切实际的，这时就需要振动能量收集。VEH 可以减少对传统电池生产和使用的依赖，从而减少一次性电池的碳足迹和化学废物，因此非常环保。然而，采用 VEH 的一个重大障碍是缺乏有效的模拟工具来生成各种应用场景，以描述、验证或预测基于 VEH 的设备的功效。因此，有必要为各种现实应用场景设计和实施 VEH 模拟器。本研究首次提出了基于 Unity3D 引擎的场景定制和视觉渲染 VEH 模拟系统。该模拟器采用模块化设计，由多个关键功能组件组成，包括振动场景创建和操作、VEH 模型规范、Unity-Python 协同计算机制和三维可视化。本文还介绍了两个基于人工智能的案例研究，利用模拟器提供的功能和数据，展示其在数据驱动的研究和应用方面的潜力。

{"title":"A scenario-customizable and visual-rendering simulator for on-vehicle vibration energy harvesting","authors":"Fangcheng Guo , Jingjin Li , Chung Ket Thein , Anqi Gao , Jianfeng Ren , Chang Heon Lee , Jiawei Li , Tianxiang Cui , Heng Yu","doi":"10.1016/j.suscom.2024.101039","DOIUrl":"10.1016/j.suscom.2024.101039","url":null,"abstract":"<div><div>The rising demand for renewable energy supply in standalone computing devices has led to the emergence of vibration energy harvesting (VEH) to overcome technical and environmental challenges. For instance, VEH is desirable in IoT scenarios where maintaining a battery supply is non-sustainable or impractical due to many devices or remote circumstances. VEH can be environmentally friendly given that it reduces the reliance on traditional battery production and usage, thus reducing the carbon footprint and chemical waste in disposable batteries. However, a significant hurdle in VEH adoption is the lack of effective simulation tools for generating various application scenarios to describe, validate, or predict the efficacy of the VEH-based devices. It is necessary for designing and implementing a VEH simulator for a variety of realistic application scenarios. Being the first of its kind, this study presents a scenario-customizable and visual-rendering VEH simulation system based on the Unity3D Engine. The proposed simulator features a modular design that consists of several key functional components including vibration scenarios’ creation and manipulation, VEH model specification, Unity-Python Co-computing mechanism, and 3D visualization. This paper also presents two AI-based case studies leveraging the functionality and data provided by the simulator to demonstrate its potential for data-driven research and applications.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101039"},"PeriodicalIF":3.8,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incorporation of computational routines in a microservice architecture in AgDataBox platform 在 AgDataBox 平台的微服务架构中纳入计算例程

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-09-21 DOI: 10.1016/j.suscom.2024.101038

Ricardo Sobjak , Eduardo Godoy de Souza , Claudio Leones Bazzi , Kelyn Schenatto , Nelson Miguel Betzek , Alan Gavioli

Agriculture has been undergoing a digital process that aims to apply digital technologies to make the sector more productive, profitable, and environmentally responsible. This trend has been adopted since applying precision agriculture (PA) techniques and, more recently, with digital agriculture (DA). DA aims to use all available information and knowledge to enable the automation of sustainable processes in agriculture, applying data analysis methods and techniques by specific software and platforms to collect and transform data into meaningful information for agriculture. Platform AgDataBox (ADB) offers tools to allow agriculture specialists to obtain, process, and visualize data for the correct decision-making. However, its structure needed to be readjusted to new software architecture to allow the aggregation of new functionalities and expand the ADB platform. This study aimed to develop a web microservices architecture (ADB-MSA) to incorporate the required functionalities to create thematic maps (TMs) and delineate management zones (MZs). ADB-MSA provided eight microservices, six of which (statistics, spatial, interpolation, clustering, rectification, and lime/nutrient recommendation) execute procedures based on JavaScript, R, and Python programming languages. At the same time, the other two are used to store data. In the case study, the procedures to create TMs and delineate MZs were performed with data from one commercial area. Thus, the services provided in the architecture meet the steps of creating TMs and delineating MZs, as MZs for fertilizer application were generated and evaluated according to phosphorus and potassium requirements. ADB-MSA allows the development of several new client applications (web, mobile, desktop, and embedded systems) to promote solutions in agriculture, streamlining processes, as it abstracts the implementation and execution complexity of available algorithms.

农业一直在经历数字化进程，目的是应用数字技术提高农业的生产率、利润和环境责任。自从应用精准农业（PA）技术，以及最近的数字农业（DA）技术以来，这一趋势已被采纳。数字农业旨在利用所有可用信息和知识，实现农业可持续流程的自动化，通过特定软件和平台应用数据分析方法和技术，收集数据并将其转化为对农业有意义的信息。AgDataBox 平台（ADB）提供了各种工具，使农业专家能够获取、处理和可视化数据，从而做出正确的决策。然而，其结构需要根据新的软件架构进行重新调整，以便聚合新的功能并扩展 ADB 平台。本研究旨在开发一个网络微服务架构（ADB-MSA），以整合创建专题地图（TM）和划定管理区（MZ）所需的功能。ADB-MSA 提供了八个微服务，其中六个（统计、空间、插值、聚类、校正和石灰/养分推荐）执行基于 JavaScript、R 和 Python 编程语言的程序。同时，另外两个用于存储数据。在案例研究中，创建 TM 和划分 MZ 的程序是利用一个商业区的数据执行的。因此，架构中提供的服务满足了创建临时管理区和划定管理区的步骤，因为根据磷和钾的需求生成并评估了施肥的管理区。ADB-MSA 允许开发多个新的客户端应用程序（网络、移动、桌面和嵌入式系统），以推广农业解决方案，简化流程，因为它抽象了现有算法的实施和执行复杂性。

{"title":"Incorporation of computational routines in a microservice architecture in AgDataBox platform","authors":"Ricardo Sobjak , Eduardo Godoy de Souza , Claudio Leones Bazzi , Kelyn Schenatto , Nelson Miguel Betzek , Alan Gavioli","doi":"10.1016/j.suscom.2024.101038","DOIUrl":"10.1016/j.suscom.2024.101038","url":null,"abstract":"<div><div>Agriculture has been undergoing a digital process that aims to apply digital technologies to make the sector more productive, profitable, and environmentally responsible. This trend has been adopted since applying precision agriculture (PA) techniques and, more recently, with digital agriculture (DA). DA aims to use all available information and knowledge to enable the automation of sustainable processes in agriculture, applying data analysis methods and techniques by specific software and platforms to collect and transform data into meaningful information for agriculture. Platform AgDataBox (ADB) offers tools to allow agriculture specialists to obtain, process, and visualize data for the correct decision-making. However, its structure needed to be readjusted to new software architecture to allow the aggregation of new functionalities and expand the ADB platform. This study aimed to develop a web microservices architecture (ADB-MSA) to incorporate the required functionalities to create thematic maps (TMs) and delineate management zones (MZs). ADB-MSA provided eight microservices, six of which (statistics, spatial, interpolation, clustering, rectification, and lime/nutrient recommendation) execute procedures based on JavaScript, R, and Python programming languages. At the same time, the other two are used to store data. In the case study, the procedures to create TMs and delineate MZs were performed with data from one commercial area. Thus, the services provided in the architecture meet the steps of creating TMs and delineating MZs, as MZs for fertilizer application were generated and evaluated according to phosphorus and potassium requirements. ADB-MSA allows the development of several new client applications (web, mobile, desktop, and embedded systems) to promote solutions in agriculture, streamlining processes, as it abstracts the implementation and execution complexity of available algorithms.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101038"},"PeriodicalIF":3.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of reservoir operation by sine cosine algorithm: A case of study in Algeria 利用正弦余弦算法优化水库运行：阿尔及利亚研究案例

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-09-11 DOI: 10.1016/j.suscom.2024.101035

Merouane Boudjerda , Bénina Touaibia , Mustapha Kamel Mihoubi , Ozgur Kisi , Mohammd Ehteram , Ahmed El-Shafie

The optimal operation of the reservoir has vital importance in water engineering. In the presented article, a new optimization method, named sine cosine algorithm (SCA) was employed to obtain operating policy for an irrigation system. The SCA was utilized for the monthly operation of the Boukerdane Dam placed in the north of Algeria. The fitness function was the minimization of the total shortage for the studied period. Three scenarios considering three different seasons of inflow (dry, normal and wet) are used to optimize the reservoir system’s operation. The SCA outputs were compared with particle swarm optimization (PSO) and kidney algorithm (KA). The outcomes indicated that the SCA surpassed the PSO and KA in convergence rate. The general results indicated the low speed of KA and PSO in achieving convergence. The results indicated that the highest RES (resiliency index), SUS (sustainability index) and REL (reliability index) achieved by the SCA were 65, 86 and 92 %, respectively. Comparing the third scenario with the first and second scenarios, it was observed that the third scenario (wet seasons) improved the results.

水库的优化运行在水利工程中至关重要。本文采用了一种名为正弦余弦算法（SCA）的新优化方法，以获得灌溉系统的运行策略。SCA 被用于阿尔及利亚北部 Boukerdane 大坝的月度运行。拟合函数是研究期间总短缺量的最小化。考虑到三个不同的流入季节（干旱、正常和潮湿），采用了三种方案来优化水库系统的运行。将 SCA 输出与粒子群优化（PSO）和肾算法（KA）进行了比较。结果表明，SCA 的收敛速度超过了 PSO 和 KA。总体结果表明，KA 和 PSO 的收敛速度较低。结果表明，SCA 达到的最高 RES（弹性指数）、SUS（可持续性指数）和 REL（可靠性指数）分别为 65%、86% 和 92%。将第三种方案与第一种和第二种方案进行比较后发现，第三种方案（雨季）的结果有所改善。

{"title":"Optimization of reservoir operation by sine cosine algorithm: A case of study in Algeria","authors":"Merouane Boudjerda , Bénina Touaibia , Mustapha Kamel Mihoubi , Ozgur Kisi , Mohammd Ehteram , Ahmed El-Shafie","doi":"10.1016/j.suscom.2024.101035","DOIUrl":"10.1016/j.suscom.2024.101035","url":null,"abstract":"<div><div>The optimal operation of the reservoir has vital importance in water engineering. In the presented article, a new optimization method, named sine cosine algorithm (SCA) was employed to obtain operating policy for an irrigation system. The SCA was utilized for the monthly operation of the Boukerdane Dam placed in the north of Algeria. The fitness function was the minimization of the total shortage for the studied period. Three scenarios considering three different seasons of inflow (dry, normal and wet) are used to optimize the reservoir system’s operation. The SCA outputs were compared with particle swarm optimization (PSO) and kidney algorithm (KA). The outcomes indicated that the SCA surpassed the PSO and KA in convergence rate. The general results indicated the low speed of KA and PSO in achieving convergence. The results indicated that the highest RES (resiliency index), SUS (sustainability index) and REL (reliability index) achieved by the SCA were 65, 86 and 92 %, respectively. Comparing the third scenario with the first and second scenarios, it was observed that the third scenario (wet seasons) improved the results.</div></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101035"},"PeriodicalIF":3.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized dynamic service placement for enhanced scheduling in fog-edge computing environments 优化动态服务布局，增强雾边缘计算环境的调度能力

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-09-11 DOI: 10.1016/j.suscom.2024.101037

Yongxing Lin , Yan Shi , Nazila Mohammadnezhad

The traditional cloud computing model struggles to efficiently handle the vast number of Internet of Things (IoT) services due to its centralized nature and physical distance from end-users. In contrast, edge and fog computing have emerged as promising solutions for supporting latency-sensitive IoT applications by distributing computational resources closer to the data source. However, these technologies are limited by their size and computational capacities, making optimal service placement a critical challenge. This paper addresses this challenge by introducing a dynamic and distributed service placement policy tailored for edge and fog environments. By leveraging the inherent advantages of proximity in fog and edge nodes, the proposed policy seeks to enhance service delivery efficiency, reduce latency, and improve resource utilization. The proposed method focuses on optimizing the placement of high-demand services closer to the data generation sources to enhance scheduling efficiency in fog computing environments. Our method is divided into three interconnected modules. The first module is the service type estimator, which is responsible for distributing services to appropriate nodes. Here, we use the Political Optimizer (PO) as a new metaheuristic algorithm for deploying IoT services. The second module is service dependency estimator, which manages service dependencies. Here, we load dependent services near the data using a path matrix based on the Warshall algorithm. Finally, the third module is resource demand scheduling, which estimates resource demand to facilitate optimal scheduling. Here, we use a popularity-based policy to manage resource demand and service execution scheduling. Implementation results demonstrate significant improvements over existing state-of-the-art policies, highlighting the efficacy of the proposed policy in enhancing service delivery within fog-edge computing frameworks.

传统的云计算模式由于其集中性和与终端用户的物理距离，很难有效处理大量的物联网（IoT）服务。相比之下，边缘计算和雾计算通过将计算资源分布在更靠近数据源的地方，成为支持延迟敏感型物联网应用的有前途的解决方案。然而，这些技术受限于其规模和计算能力，使得优化服务布局成为一项严峻挑战。本文针对这一挑战，引入了一种为边缘和雾环境量身定制的动态分布式服务放置策略。通过利用雾节点和边缘节点固有的邻近优势，所提出的策略旨在提高服务交付效率、减少延迟并提高资源利用率。所提方法的重点是优化高需求服务的布局，使其更接近数据生成源，从而提高雾计算环境中的调度效率。我们的方法分为三个相互关联的模块。第一个模块是服务类型估计器，负责将服务分配到合适的节点。在这里，我们使用政治优化器（PO）作为部署物联网服务的一种新元启发式算法。第二个模块是服务依赖性估算器，负责管理服务依赖性。在这里，我们使用基于 Warshall 算法的路径矩阵加载数据附近的依赖服务。最后，第三个模块是资源需求调度，用于估算资源需求以促进优化调度。在这里，我们使用基于流行度的策略来管理资源需求和服务执行调度。实施结果表明，与现有的最先进策略相比，我们的策略有了明显改善，这凸显了我们提出的策略在加强雾边缘计算框架内服务交付方面的功效。

{"title":"Optimized dynamic service placement for enhanced scheduling in fog-edge computing environments","authors":"Yongxing Lin , Yan Shi , Nazila Mohammadnezhad","doi":"10.1016/j.suscom.2024.101037","DOIUrl":"10.1016/j.suscom.2024.101037","url":null,"abstract":"<div><p>The traditional cloud computing model struggles to efficiently handle the vast number of Internet of Things (IoT) services due to its centralized nature and physical distance from end-users. In contrast, edge and fog computing have emerged as promising solutions for supporting latency-sensitive IoT applications by distributing computational resources closer to the data source. However, these technologies are limited by their size and computational capacities, making optimal service placement a critical challenge. This paper addresses this challenge by introducing a dynamic and distributed service placement policy tailored for edge and fog environments. By leveraging the inherent advantages of proximity in fog and edge nodes, the proposed policy seeks to enhance service delivery efficiency, reduce latency, and improve resource utilization. The proposed method focuses on optimizing the placement of high-demand services closer to the data generation sources to enhance scheduling efficiency in fog computing environments. Our method is divided into three interconnected modules. The first module is the service type estimator, which is responsible for distributing services to appropriate nodes. Here, we use the Political Optimizer (PO) as a new metaheuristic algorithm for deploying IoT services. The second module is service dependency estimator, which manages service dependencies. Here, we load dependent services near the data using a path matrix based on the Warshall algorithm. Finally, the third module is resource demand scheduling, which estimates resource demand to facilitate optimal scheduling. Here, we use a popularity-based policy to manage resource demand and service execution scheduling. Implementation results demonstrate significant improvements over existing state-of-the-art policies, highlighting the efficacy of the proposed policy in enhancing service delivery within fog-edge computing frameworks.</p></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101037"},"PeriodicalIF":3.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A succinct state-of-the-art survey on green cloud computing: Challenges, strategies, and future directions 关于绿色云计算的最新简明调查：挑战、战略和未来方向

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-09-10 DOI: 10.1016/j.suscom.2024.101036

Dipto Biswas , Sohely Jahan , Sajeeb Saha , Md. Samsuddoha

Cloud computing is a method of providing various computing services, including software, hardware, databases, data storage, and infrastructure, to the public through the Internet. The rapid expansion of cloud computing services has raised significant concerns over their environmental impact. Cloud computing services should be designed in a green manner, efficient in energy consumption, virtualized, consolidated, and eco-friendly. Green Cloud Computing (GCC) is a significant field of study that focuses on minimizing the environmental impact and energy usage of cloud infrastructures. This survey provides a comprehensive overview of the current state of GCC, focusing on the challenges, strategies, and future directions. The review study begins by identifying important challenges in GCC from practical implementations, identifying GCC-introduced environmental protection and prevention initiatives, and expressing the demand for long-term technical progression. It then addresses GCC’s primary concerns, such as energy efficiency, resource management, operational costs, and carbon emissions, and categorizes implementations according to algorithms, architectures, frameworks, general issues, and models and methodologies. Furthermore, enhancements in virtualization, multi-tenancy, and consolidation have been identified, analyzed, and accurately portrayed to address the advancements in GCC. Finally, the survey outlines future research directions and opportunities for advancing the field of GCC, including the development of novel algorithms, technologies for energy harvesting, and energy-efficient and eco-friendly solutions. By providing a comprehensive overview of GCC, this survey aims to serve as documentation for further evolving new emerging technological approaches in the GCC environment.

云计算是一种通过互联网向公众提供各种计算服务的方法，包括软件、硬件、数据库、数据存储和基础设施。云计算服务的迅速扩展引起了人们对其环境影响的极大关注。云计算服务应采用绿色设计、高效能耗、虚拟化、整合和生态友好。绿色云计算（GCC）是一个重要的研究领域，其重点是最大限度地减少云基础设施对环境的影响和能源消耗。本调查全面概述了 GCC 的现状，重点关注挑战、战略和未来方向。回顾性研究首先从实际实施中确定了 GCC 面临的重要挑战，明确了 GCC 引入的环境保护和预防措施，并表达了对长期技术进步的需求。然后，它探讨了 GCC 的主要关注点，如能源效率、资源管理、运营成本和碳排放，并根据算法、架构、框架、一般问题以及模型和方法对实施进行了分类。此外，还对虚拟化、多租户和整合方面的改进进行了识别、分析和准确描绘，以应对 GCC 的进步。最后，调查报告概述了推动 GCC 领域发展的未来研究方向和机遇，包括开发新型算法、能源采集技术以及高能效和生态友好型解决方案。通过对 GCC 的全面概述，本调查旨在为进一步发展 GCC 环境中的新兴技术方法提供文献资料。

{"title":"A succinct state-of-the-art survey on green cloud computing: Challenges, strategies, and future directions","authors":"Dipto Biswas , Sohely Jahan , Sajeeb Saha , Md. Samsuddoha","doi":"10.1016/j.suscom.2024.101036","DOIUrl":"10.1016/j.suscom.2024.101036","url":null,"abstract":"<div><p>Cloud computing is a method of providing various computing services, including software, hardware, databases, data storage, and infrastructure, to the public through the Internet. The rapid expansion of cloud computing services has raised significant concerns over their environmental impact. Cloud computing services should be designed in a green manner, efficient in energy consumption, virtualized, consolidated, and eco-friendly. Green Cloud Computing (GCC) is a significant field of study that focuses on minimizing the environmental impact and energy usage of cloud infrastructures. This survey provides a comprehensive overview of the current state of GCC, focusing on the challenges, strategies, and future directions. The review study begins by identifying important challenges in GCC from practical implementations, identifying GCC-introduced environmental protection and prevention initiatives, and expressing the demand for long-term technical progression. It then addresses GCC’s primary concerns, such as energy efficiency, resource management, operational costs, and carbon emissions, and categorizes implementations according to algorithms, architectures, frameworks, general issues, and models and methodologies. Furthermore, enhancements in virtualization, multi-tenancy, and consolidation have been identified, analyzed, and accurately portrayed to address the advancements in GCC. Finally, the survey outlines future research directions and opportunities for advancing the field of GCC, including the development of novel algorithms, technologies for energy harvesting, and energy-efficient and eco-friendly solutions. By providing a comprehensive overview of GCC, this survey aims to serve as documentation for further evolving new emerging technological approaches in the GCC environment.</p></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101036"},"PeriodicalIF":3.8,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new hybrid fixed and adaptive gains control algorithm to reduce power losses on LLCL filter-based renewable energy conversion systems with systematic parametrization using Grey Wolf optimizer 基于 LLCL 滤波器的可再生能源转换系统采用新的固定增益和自适应增益混合控制算法，利用灰狼优化器进行系统参数化，以降低功率损耗

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-08-23 DOI: 10.1016/j.suscom.2024.101034

Felipe Pontes de Matos, Marlon Mauricio Hernandez Cely, Paulo Jefferson Dias de Oliveira Evald

Currently, there is a transition in the energy matrix around the world, where traditional sources of energy generation are continually being replaced by energy generation systems based on renewable sources to mitigate the climate crisis. In this bias, this work presents the mathematical modeling of an LLCL filter, used to connect power generation systems based on renewable energy sources to the electrical grid, and presents a novel hybrid fixed-and adaptive gains control strategy for current injection into the grid using this system. The developed hybrid controller is composed of a proportional–integral controller and a direct robust adaptive controller. The first term of the controller guarantees the reference current, while the second term of the controller is used for disturbance rejection. Furthermore, a systematic procedure for the controller’s parametrization based on Grey Wolf Optimizer is also provided. The control of the current injected into the grid is carried out considering the LLCL filter without passive damping resistors in the filter structure to avoid power losses due to the passive filter elements. Additionally, the LLCL filter model considers minimal parasitic resistances to evaluate the controller’s performance and optimize it for the application of interest, aiming to maximize the system performance by ensuring a short transient regime due to the fast closed-loop system response. Simulation results indicate high performance of this optimized control strategy with small tracking error even considering grid impedance variations.

目前，全世界的能源结构正在发生转变，传统的能源发电方式不断被基于可再生能源的发电系统所取代，以缓解气候危机。在此背景下，本作品介绍了用于将基于可再生能源的发电系统连接到电网的 LLCL 滤波器的数学模型，并提出了一种新颖的固定增益和自适应增益混合控制策略，用于利用该系统向电网注入电流。所开发的混合控制器由比例积分控制器和直接鲁棒自适应控制器组成。控制器的第一项保证了参考电流，而第二项则用于抑制干扰。此外，还提供了基于灰狼优化器的控制器参数化系统程序。在对注入电网的电流进行控制时，考虑到在滤波器结构中不使用无源阻尼电阻器的 LLCL 滤波器，以避免无源滤波器元件造成的功率损耗。此外，LLCL 滤波器模型考虑了最小寄生电阻，以评估控制器的性能，并针对相关应用对其进行优化，目的是通过快速闭环系统响应确保短瞬态机制，从而最大限度地提高系统性能。仿真结果表明，即使考虑到电网阻抗变化，这种优化控制策略的性能也很高，跟踪误差很小。

{"title":"A new hybrid fixed and adaptive gains control algorithm to reduce power losses on LLCL filter-based renewable energy conversion systems with systematic parametrization using Grey Wolf optimizer","authors":"Felipe Pontes de Matos, Marlon Mauricio Hernandez Cely, Paulo Jefferson Dias de Oliveira Evald","doi":"10.1016/j.suscom.2024.101034","DOIUrl":"10.1016/j.suscom.2024.101034","url":null,"abstract":"<div><p>Currently, there is a transition in the energy matrix around the world, where traditional sources of energy generation are continually being replaced by energy generation systems based on renewable sources to mitigate the climate crisis. In this bias, this work presents the mathematical modeling of an LLCL filter, used to connect power generation systems based on renewable energy sources to the electrical grid, and presents a novel hybrid fixed-and adaptive gains control strategy for current injection into the grid using this system. The developed hybrid controller is composed of a proportional–integral controller and a direct robust adaptive controller. The first term of the controller guarantees the reference current, while the second term of the controller is used for disturbance rejection. Furthermore, a systematic procedure for the controller’s parametrization based on Grey Wolf Optimizer is also provided. The control of the current injected into the grid is carried out considering the LLCL filter without passive damping resistors in the filter structure to avoid power losses due to the passive filter elements. Additionally, the LLCL filter model considers minimal parasitic resistances to evaluate the controller’s performance and optimize it for the application of interest, aiming to maximize the system performance by ensuring a short transient regime due to the fast closed-loop system response. Simulation results indicate high performance of this optimized control strategy with small tracking error even considering grid impedance variations.</p></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101034"},"PeriodicalIF":3.8,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction notice to ‘Deep learning-based energy inefficiency detection in the smart buildings' [Sustainable Computing: Informatics and Systems 40 (2023) 100921] 基于深度学习的智能建筑能效检测》撤稿通知 [Sustainable Computing: Informatics and Systems 40 (2023) 100921]

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-08-06 DOI: 10.1016/j.suscom.2024.101022

Jueru Huang , Dmitry D. Koroteev , Marina Rynkovskaya

引用次数: 0

Secured osprey-based energy efficient routing and congestion control in WSN WSN 中基于鹗的安全节能路由和拥塞控制

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-08-02 DOI: 10.1016/j.suscom.2024.101026

R.M. Bhavadharini , B. Surendiran

An adaptive metaheuristic optimization-based QoS-aware, Energy-balancing, Secure Routing Protocol (AQoS-ESRP) is proposed in this article. The network is modelled as a biconcentric hexagon (BiCon-HexA), and the clusters are formed within the BiCon-HexA network. The BiCon-HexA is divided into six sectors to support effective data aggregation, and then clusters are formed within all sectors. The optimal cluster head (CH) selection mechanism is modelled by an Adaptive Hunter-Prey Optimization (AdapH-PO) algorithm considering QoS parameters. Data aggregation is then done securely with an enhanced encryption approach. Here, upgraded elliptic curve cryptography (UEllip-CC) is used to encode data in CH. This UEllip-CC approach provides security improvements in data transmission. Furthermore, in this study, CHs are combined in the multi-hop routing of data packets to reduce the power consumption problems of wireless sensor networks (WSN). To determine the optimal route for data transmission, an energy-balanced multi-path routing algorithm called improved convolutional osprey network (ICON) is presented. Nevertheless, the data transmission nodes can be overloaded in the data routing phase. Here, the congestion problem can be solved by applying an improved version of the Random Early Detection (RED) congestion control model to discard the data packets more noticeably. The simulation of AQoS-ESRP is done with Matlab, and the performance is evaluated using different metrics. When compared to existing systems, the simulation results clearly indicate a significantly higher throughput and delay. Thus, the AQoS ESRP model is employed to maximize the overall data transfer in the WSN.

本文提出了一种基于自适应元启发式优化的 QoS 感知、能量平衡、安全路由协议（AQoS-ERP）。网络被模拟成一个双中心六边形（BiCon-HexA），并在 BiCon-HexA 网络中形成集群。为了支持有效的数据聚合，BiCon-HexA 被划分为六个扇区，然后在所有扇区内形成簇。最佳簇头（CH）选择机制采用自适应猎人-猎物优化（AdapH-PO）算法建模，其中考虑了 QoS 参数。然后，采用增强型加密方法安全地进行数据聚合。在这里，升级的椭圆曲线加密法（UEllip-CC）被用来对 CH 中的数据进行加密。这种 UEllip-CC 方法提高了数据传输的安全性。此外，在这项研究中，CH 在数据包的多跳路由中被结合起来，以减少无线传感器网络（WSN）的功耗问题。为了确定数据传输的最佳路由，提出了一种名为改进卷积鹗网络（ICON）的能量平衡多路径路由算法。然而，在数据路由阶段，数据传输节点可能会超载。在这里，可以通过应用改进版的随机早期检测（RED）拥塞控制模型来解决拥塞问题，从而更明显地丢弃数据包。使用 Matlab 对 AQoS-ESRP 进行了仿真，并使用不同指标对其性能进行了评估。与现有系统相比，仿真结果清楚地表明吞吐量和延迟都有明显提高。因此，采用 AQoS ESRP 模型可以最大限度地提高 WSN 的整体数据传输能力。

{"title":"Secured osprey-based energy efficient routing and congestion control in WSN","authors":"R.M. Bhavadharini , B. Surendiran","doi":"10.1016/j.suscom.2024.101026","DOIUrl":"10.1016/j.suscom.2024.101026","url":null,"abstract":"<div><p>An adaptive metaheuristic optimization-based QoS-aware, Energy-balancing, Secure Routing Protocol (AQoS-ESRP) is proposed in this article. The network is modelled as a biconcentric hexagon (BiCon-HexA), and the clusters are formed within the BiCon-HexA network. The BiCon-HexA is divided into six sectors to support effective data aggregation, and then clusters are formed within all sectors. The optimal cluster head (CH) selection mechanism is modelled by an Adaptive Hunter-Prey Optimization (AdapH-PO) algorithm considering QoS parameters. Data aggregation is then done securely with an enhanced encryption approach. Here, upgraded elliptic curve cryptography (UEllip-CC) is used to encode data in CH. This UEllip-CC approach provides security improvements in data transmission. Furthermore, in this study, CHs are combined in the multi-hop routing of data packets to reduce the power consumption problems of wireless sensor networks (WSN). To determine the optimal route for data transmission, an energy-balanced multi-path routing algorithm called improved convolutional osprey network (ICON) is presented. Nevertheless, the data transmission nodes can be overloaded in the data routing phase. Here, the congestion problem can be solved by applying an improved version of the Random Early Detection (RED) congestion control model to discard the data packets more noticeably. The simulation of AQoS-ESRP is done with Matlab, and the performance is evaluated using different metrics. When compared to existing systems, the simulation results clearly indicate a significantly higher throughput and delay. Thus, the AQoS ESRP model is employed to maximize the overall data transfer in the WSN.</p></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"44 ","pages":"Article 101026"},"PeriodicalIF":3.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DBSCAN based approach for energy efficient VM placement using medium level CPU utilization 基于 DBSCAN 的方法，利用中等水平的 CPU 利用率实现高能效虚拟机放置

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems

Pub Date : 2024-08-02 DOI: 10.1016/j.suscom.2024.101025

Akanksha Tandon, Sanjeev Patel

Virtual machine placement (VMP) is a popular problem in Cloud Data Centers (CDCs). An efficient virtual machine (VM) allocation is essential for processor speed and energy saving. This is more useful where the CDC uses an Internet of Things (IoT) infrastructure. To enhance energy savings, we aim to improve the adaptive four thresholds energy-aware framework for VM deployment. We observed that the role of the threshold for identifying the over-loaded host is crucial. In order to determine the appropriate threshold, we employed density-based spatial clustering of applications with noise (DBSCAN), medium absolute deviation (MAD), and interquartile range (IQR) using the medium fit power efficient decreasing (MFPED) algorithm. Our proposed algorithm modified medium fit energy efficient decreasing (MMFEED) achieves a reduction in energy consumption of 47.3%, 46.1%, 39%, 23.2%, 10.9%, and 3.4% compared to the IQR, MAD, static threshold (THR), exponential weighted moving average (EWMA), modified energy-efficient virtual machine placement (MEEVMP), and adaptive four threshold energy-aware framework for VM deployment energy efficient (AFED-EF), respectively, under the minimum migration time (MMT) selection policy. The proposed algorithm outperforms these algorithms in terms of energy consumption for VM selection policy MMT.

虚拟机分配（VMP）是云数据中心（CDC）中的一个常见问题。高效的虚拟机（VM）分配对处理器速度和节能至关重要。当 CDC 使用物联网（IoT）基础设施时，这一点更为有用。为了提高节能效果，我们旨在改进用于虚拟机部署的自适应四阈值能源感知框架。我们注意到，阈值在识别过载主机方面的作用至关重要。为了确定合适的阈值，我们采用了基于密度的应用空间聚类噪声（DBSCAN）、中等绝对偏差（MAD）和四分位数范围（IQR），并使用了中等拟合功率效率递减（MFPED）算法。在最小迁移时间（MMT）选择策略下，与 IQR、MAD、静态阈值（THR）、指数加权移动平均值（EWMA）、改进型节能虚拟机放置（MEEVMP）和用于虚拟机部署节能的自适应四阈值能量感知框架（AFED-EF）相比，我们提出的改进型中等拟合节能递减（MMFEED）算法分别实现了 47.3%、46.1%、39%、23.2%、10.9% 和 3.4% 的能耗降低。就虚拟机选择策略 MMT 的能耗而言，所提出的算法优于这些算法。

{"title":"DBSCAN based approach for energy efficient VM placement using medium level CPU utilization","authors":"Akanksha Tandon, Sanjeev Patel","doi":"10.1016/j.suscom.2024.101025","DOIUrl":"10.1016/j.suscom.2024.101025","url":null,"abstract":"<div><p>Virtual machine placement (VMP) is a popular problem in Cloud Data Centers (CDCs). An efficient virtual machine (VM) allocation is essential for processor speed and energy saving. This is more useful where the CDC uses an Internet of Things (IoT) infrastructure. To enhance energy savings, we aim to improve the adaptive four thresholds energy-aware framework for VM deployment. We observed that the role of the threshold for identifying the over-loaded host is crucial. In order to determine the appropriate threshold, we employed density-based spatial clustering of applications with noise (DBSCAN), medium absolute deviation (MAD), and interquartile range (IQR) using the medium fit power efficient decreasing (MFPED) algorithm. Our proposed algorithm modified medium fit energy efficient decreasing (MMFEED) achieves a reduction in energy consumption of 47.3%, 46.1%, 39%, 23.2%, 10.9%, and 3.4% compared to the IQR, MAD, static threshold (THR), exponential weighted moving average (EWMA), modified energy-efficient virtual machine placement (MEEVMP), and adaptive four threshold energy-aware framework for VM deployment energy efficient (AFED-EF), respectively, under the minimum migration time (MMT) selection policy. The proposed algorithm outperforms these algorithms in terms of energy consumption for VM selection policy MMT.</p></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"43 ","pages":"Article 101025"},"PeriodicalIF":3.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141935799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0