2021 IEEE International Conference on Web Services (ICWS)最新文献_第8页

User Allocation in Mobile Edge Computing: A Deep Reinforcement Learning Approach 移动边缘计算中的用户分配:一种深度强化学习方法

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00064

Subrat Prasad Panda, A. Banerjee, A. Bhattacharya

{"title":"User Allocation in Mobile Edge Computing: A Deep Reinforcement Learning Approach","authors":"Subrat Prasad Panda, A. Banerjee, A. Bhattacharya","doi":"10.1109/ICWS53863.2021.00064","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00064","url":null,"abstract":"In recent times, the need for low latency has made it necessary to deploy application services physically and logically close to the users rather than using the cloud for hosting services. This paradigm of computing, known as edge or fog computing, is becoming increasingly popular. An edge user allocation policy determines how to allocate service requests from mobile users to MEC servers. Current state-of-the-art techniques assume that the total resource utilization on an edge server is equal to the sum of the individual resource utilizations of services provisioned from the edge server. However, the relationship between resources utilized on an edge server with the number of service requests served from there is usually highly non-linear, hence, mathematically modelling the resource utilization is challenging. This is especially true in case of an environment with CPU-GPU co-execution, as commonly observed in modern edge computing. In this work, we provide an on-device Deep Reinforcement Learning (DRL) framework to predict the resource utilization of incoming service requests from users, thereby estimating the number of users an edge server can accommodate for a given latency threshold. We further propose an algorithm to obtain the user allocation policy. We compare the performance of the proposed DRL framework with traditional allocation approaches and show that the DRL framework outperforms deterministic approaches by at least 10% in terms of the number of users allocated.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130881934","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: 9

Attaining Meta-self-awareness through Assessment of Quality-of-Knowledge 通过知识质量评估获得元自我意识

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00099

Abdessalam Elhabbash, R. Bahsoon, P. Tiňo, P. R. Lewis, Yehia Elkhatib

引用次数: 3

Dealing with Label Uncertainty in Web Service Anti-patterns Detection using a Possibilistic Evolutionary Approach 用可能性进化方法处理Web服务反模式检测中的标签不确定性

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00053

Sofien Boutaib, Maha Elarbi, Slim Bechikh, M. Makhlouf, L. B. Said

{"title":"Dealing with Label Uncertainty in Web Service Anti-patterns Detection using a Possibilistic Evolutionary Approach","authors":"Sofien Boutaib, Maha Elarbi, Slim Bechikh, M. Makhlouf, L. B. Said","doi":"10.1109/ICWS53863.2021.00053","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00053","url":null,"abstract":"Like the case of any software, Web Services (WSs) developers could introduce anti-patterns due to the lack of experience and badly-planned changes. During the last decade, search-based approaches have shown their outperformance over other approaches mainly thanks to their global search ability. Unfortunately, these approaches do not consider the uncertainty of class labels. In fact, two experts could be uncertain about the smelliness of a particular WS interface but also about the smell type. Currently, existing works reject uncertain data that correspond to WSs interfaces with doubtful labels. Motivated by this observation and the good performance of the possibilistic K-NN classifier in handling uncertain data, we propose a new evolutionary detection approach, named Web Services Anti-patterns Detection and Identification using Possibilistic Optimized K-NNs (WS-ADIPOK), which can cope with the uncertainty based on the Possibility Theory. The obtained experimental results reveal the merits of our proposal regarding four relevant state-of-the-art approaches.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117186858","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

R-CASS: Using Algorithm Selection for Self-Adaptive Service Oriented Systems R-CASS:基于算法选择的自适应服务导向系统

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00021

N. Deshpande, Naveen Sharma, Qi Yu, Daniel E. Krutz

引用次数: 1

An Empirical Study on Underlying Correlations between Runtime Performance Deficiencies and “Bad Smells” of Microservice Systems 微服务系统运行时性能缺陷与“不良气味”潜在相关性的实证研究

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00103

Lei Liu, Zhiying Tu, Xiang He, Xiaofei Xu, Zhongjie Wang

{"title":"An Empirical Study on Underlying Correlations between Runtime Performance Deficiencies and “Bad Smells” of Microservice Systems","authors":"Lei Liu, Zhiying Tu, Xiang He, Xiaofei Xu, Zhongjie Wang","doi":"10.1109/ICWS53863.2021.00103","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00103","url":null,"abstract":"Although many principles have been put forward to guide microservice design, such as Domain-Driven Design, Architectural Bad Smells (ABS) would be inevitably imported during microservice system design and development. There has been a consensus that the existence of ABSs would bring negative effects to microservice systems. Although some approaches use static analysis to detect ABSs in the design phase, we conjecture that the design-phase ABSs would result in some performance deficiencies at runtime. This paper conducts an empirical study on underlying correlations between runtime performance deficiencies and ABSs in microservice system design. An automated experimental stress testing framework called MRSTF is developed for automatic deployment of MSS and collecting/analyzing runtime performance data. A microservice system TrainTicket is used in this empirical study. We manually inject several typical ABSs into the system and use MRSTF to compare the runtime performances before and after the injection and check if the existence of ABSs has significant effects on the runtime performance. Experiment results show that ABSs have significant negative effects on some performance metrics of runtime MSS while doing not on others. This study provides solid evidence on the feasibility of optimizing MSS design by eliminating ABSs based on runtime performance data.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116861761","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: 3

A Measurement Study on Serverless Workflow Services 无服务器工作流服务的度量研究

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00102

Jinfeng Wen, Yi Liu

{"title":"A Measurement Study on Serverless Workflow Services","authors":"Jinfeng Wen, Yi Liu","doi":"10.1109/ICWS53863.2021.00102","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00102","url":null,"abstract":"Major cloud providers increasingly roll out their serverless workflow services to orchestrate serverless functions, making it possible to construct complex applications effectively. A comprehensive study is necessary to help developers understand the pros and cons, and make better choices among these serverless workflow services. However, the characteristics of these serverless workflow services have not been systematically analyzed. To fill the knowledge gap, we conduct a comprehensive measurement study on four mainstream serverless workflow services, focusing on both features and the performance. First, we review their official documentation and extract their features from six dimensions, including programming model, state management, etc. Then, we compare their performance (i.e., the execution time of functions, execution time of workflows, orchestration overhead time of workflows) under various settings considering activity complexity and data-flow complexity of workflows, as well as function complexity of serverless functions. Our findings and implications could help developers and cloud providers improve their development efficiency and user experience.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126234617","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: 6

Web Page Information Extraction Service Based on Graph Convolutional Neural Network and Multimodal Data Fusion 基于图卷积神经网络和多模态数据融合的网页信息提取服务

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00094

Mingzhu Zhang, Zhongguo Yang, Sikandar Ali, Weilong Ding

{"title":"Web Page Information Extraction Service Based on Graph Convolutional Neural Network and Multimodal Data Fusion","authors":"Mingzhu Zhang, Zhongguo Yang, Sikandar Ali, Weilong Ding","doi":"10.1109/ICWS53863.2021.00094","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00094","url":null,"abstract":"Information extraction and its service is a hot topic. Many works focus on extracting information from a certain web page and ignore the localization of the webpage which contains useful information. Nevertheless, developing a holistic system to extract information consists of locating a webpage and extracting information from that webpage, and these two steps are indispensable. For instance, extracting lecture news from universities' websites is a typical hard task that need to locate web pages and extract news information from them. Due to different layouts and visual appearances, statistic-based methods and visual based methods failed to find them. In this study, we propose an all-holistic method to locate lecture news on the university website. Graph Convolutional Network (GCN) is applied to fuse the multimodal data, which could learn useful features from different views, the linked relationship, the visual similarity, and the semantic of web pages. Firstly, we apply the link model to explore the parent-child relationship between web pages, then calculate the similarity of parent-child pages using a visual model and obtain the semantic features based on the BERT model. Specifically, the visual similarity features are learned based on triplet loss function which imposes the Convolutional Neural Network (CNN) model to learn similar parts in the same group. Lastly, these features are fused into the GCN model to find a certain webpage and it can be adaptive to various university websites. The experiments conducted on 50 websites show our method outperforms state-of-the-art.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131151724","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

Intention-oriented Hierarchical Bundle Recommendation with Preference Transfer 具有偏好转移的面向意图的分层束推荐

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00026

Meng Tan, Wei Chen, Weiqing Wang, An Liu, Lei Zhao

{"title":"Intention-oriented Hierarchical Bundle Recommendation with Preference Transfer","authors":"Meng Tan, Wei Chen, Weiqing Wang, An Liu, Lei Zhao","doi":"10.1109/ICWS53863.2021.00026","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00026","url":null,"abstract":"Bundle recommendation offers promotions of bundled items instead of a single one, which is a common strategy for sales revenue increase and latent customer mining. Due to the scarcity of user-bundle interactions, it is compulsory to go beyond modeling user-bundle interactions and take user-item interactions into account. Existing studies consider user-item interactions by sharing model parameters or learning representation in a multi-task manner or modeling representation based on graph neural network. However, such methods ignore the mutual influence between user preferences for items and bundles. Moreover, they fail to analyse the intentions behind users' purchase behaviors, which can be utilized to make better bundle recommendation. To overcome the drawbacks of existing studies, we propose a novel model IHBR (Intention-oriented Hierarchical Bundle Recommendation with Preference Transfer). Specifically, we consider the co-purchase and co-occurrence information within items for modeling intention-oriented hierarchical representations. Furthermore, we provide a new perspective to exploit mutual influence between user preferences for items and bundles. The experimental results obtained on two real-world datasets demonstrate that our method outperforms the state-of-the-art baselines.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134198618","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: 3

A Privacy-aware Stackelberg Game Approach for Joint Pricing, Investment, Computation Offloading and Resource Allocation in MEC-enabled Smart Cities 基于mec的智慧城市联合定价、投资、计算卸载和资源分配的隐私意识Stackelberg博弈方法

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00089

Hualong Huang, Kai Peng, Peichen Liu

引用次数: 2

A Holistic Auto-Scaling Algorithm for Multi-Service Applications Based on Balanced Queuing Network 一种基于平衡排队网络的多业务应用整体自缩放算法

2021 IEEE International Conference on Web Services (ICWS) Pub Date : 2021-09-01 DOI: 10.1109/ICWS53863.2021.00074

Jing-hua Tong, M. Wei, Maolin Pan, Yang Yu

{"title":"A Holistic Auto-Scaling Algorithm for Multi-Service Applications Based on Balanced Queuing Network","authors":"Jing-hua Tong, M. Wei, Maolin Pan, Yang Yu","doi":"10.1109/ICWS53863.2021.00074","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00074","url":null,"abstract":"Container-supported microservice technology is widely used in cloud applications. For elastic cloud, it's vital to maintain application response time within service-level agreements (SLA) by auto-scaling technology. For applications composed of multiple services (i.e. multi-service applications), due to complex topologies, there are many factors that reduce auto-scaling algorithm performance, such as correlations among services, untimely decision, oversupply, etc. To resolve this, we propose a holistic auto-scaling algorithm (HAB) based on balanced Jackson queuing network (JQN) to reduce SLA violations rapidly with less resource cost. With the holistic auto-scaling strategy, HAB scales all services quickly and accurately. Keeping the balanced state among services, HAB saves resource cost, reduces auto-scaling decision space and simplifies algorithm parameters. The experimental results demonstrate that HAB has an average decrease of 42.31% in SLA violation rate, an average decrease of 17.88% in resource cost and an average increase of 19.39% in stability, compared with other main methods.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132717992","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: 6