{"title":"COPA: A Combined Autoscaling Method for Kubernetes","authors":"Zhijun Ding, Qichen Huang","doi":"10.1109/ICWS53863.2021.00061","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00061","url":null,"abstract":"Autoscaling is one of the major features of Cloud Computing aiming to improve the Quality-of-Service(QoS) in response to fluctuating workloads. Existing state-of-the-art autoscaling methods for Kubernetes focus on single scaling mode, that is, only horizontal scaling and only vertical scaling. For horizontal scaling, a high resource usage rate cannot be guaranteed sometimes; and for vertical scaling, microservice instances appear a performance ceiling that does not grow indefinitely as the supply of resources increases. In this paper, we propose a novel combined scaling method called COPA. Based on the collected microservice performance data, real-time workload, expected response time, and microservice instances scheme at runtime, COPA uses the queuing network model to calculate a combined scaling scheme that aims to minimize the default cost and resource cost. We evaluated our approach in a Kubernetes cluster, and compare it with existing state-of-the-art autoscaling methods under four different workload types. Such experiments show a reduction of ×1.22 for resource cost while ensuring the QoS as compared to the baseline method.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"30 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":"115487216","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}
Jing Zhang, Yang Chen, Yilong Yang, Changran Lei, Deqiang Wang
{"title":"ServeNet-LT: A Normalized Multi-head Deep Neural Network for Long-tailed Web Services Classification","authors":"Jing Zhang, Yang Chen, Yilong Yang, Changran Lei, Deqiang Wang","doi":"10.1109/ICWS53863.2021.00025","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00025","url":null,"abstract":"Automatic service classification plays an important role in service discovery, selection, and composition. Recently, machine learning has been widely used in service classification. Though promising results are obtained, previous methods are merely evaluated on web services datasets with small-scale data and relatively balanced data, which limit their real-world applications. In this paper, we address the long-tailed web services classification problem with more categories and imbalanced data. Due to the long-tailed distribution of datasets, the existing machine learning and deep learning methods cannot work well. To deal with the long-tailed problem, we propose a normalized multi-head classifier learning strategy, which effectively reduces the classifier bias and benefit the generalization capacity of the extracted features. Extensive experiments are conducted on a large-scale long-tailed web services dataset, and the results show that our model outperforms the 11 compared service classification methods to a large margin.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"67 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":"116643109","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}
{"title":"Automatic Control Network Anomaly Detection Based on Behavior Understanding","authors":"Jianhui Luo","doi":"10.1109/ICWS53863.2021.00087","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00087","url":null,"abstract":"In automatic control networks, for man-in-the-middle attacks, they tamper with the control instructions and the underlying feedback data, but the protocol and format of the data packet, making the attack difficult to detect. In this paper, we introduce a network intrusion detection model based on the automatic control network behavior understanding and machine learning. The model can understand the operating status of the control network from the correlation of parameter status, find abnormal behavior status that does not conform to the normal operating status, and locate and trace the source of the tampered instruction or parameter to understand the attacker's intention. We verified the feasibility and practicability of the model in simulating real automatic control network scenarios.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"49 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":"125441589","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}
Huimin Chen, H. Jia, Xia Wu, Xiuli Wang, Maoning Wang
{"title":"Quantum Token for Network Authentication","authors":"Huimin Chen, H. Jia, Xia Wu, Xiuli Wang, Maoning Wang","doi":"10.1109/ICWS53863.2021.00095","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00095","url":null,"abstract":"Classical token-based authentication can play a significant role in the web security check without accessing the database. For example, JSON Web Tokens (JWT) has been used to support scenarios such as single-sign-on. However, with the development of quantum computer, the security of JWT relying on the RSA algorithm would be compromised. Therefore, we propose a protocol to realize network authentication utilizing quantum token. Inspired by the structure of classical JWT, the structure of quantum token also consists of three parts: header, payload and quantum information. After the user logs in successfully, the quantum token can be issued by the server. If the user presents the quantum token to access again during the validity period, the server can verify whether the quantum token is valid. Our quantum token protocol can detect eavesdropping and achieve identity authentication. We also conduct a security analysis of the proposed protocol by addressing possible motives of an Eavesdropper and conclude the approach to be resilient against a broad range of attacks.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"20 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":"132369809","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}
{"title":"Lightweight and Context-aware Modeling of Microservice-based Internet of Things","authors":"Zhen Wang, Chang-ai Sun, Marco Aiello","doi":"10.1109/ICWS53863.2021.00046","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00046","url":null,"abstract":"Service-Oriented Architecture (SOA) provides a scalable framework for heterogeneous, pervasive Internet of Things (IoT) devices. For such open and dynamic infrastructure, a proper service description schema is fundamental to unify the self-description of services. However, existing approaches mainly rely on verbose service protocols which produce unnecessary service overhead for resource limited devices. In addition, these approaches usually focus on describing service functions while largely ignoring context characteristics of IoT services. A lightweight and context-aware service description approach is yet to be proposed. In this paper, we propose a context-aware IoT service description approach based on the microservice architecture. Our approach not only provides a service description schema with lightweight protocols, but also comprehensively describes the context, service, and interface characteristics of IoT services. We demonstrate the applicability and effectiveness of our approach for the case of a smart elderly care system. Furthermore, we provide a comparison with related approaches to elaborate on pros and cons of our proposal with respect to the state of the art in the field.","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":"129387835","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}
Qiang Zhou, Wei Chen, Weiqing Wang, Jiajie Xu, Lei Zhao
{"title":"Multiple Features Driven Author Name Disambiguation","authors":"Qiang Zhou, Wei Chen, Weiqing Wang, Jiajie Xu, Lei Zhao","doi":"10.1109/ICWS53863.2021.00071","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00071","url":null,"abstract":"Author Name Disambiguation (AND) has received more attention recently, accompanied by the increase of academic publications. To tackle the AND problem, existing studies have proposed many approaches based on different types of information, such as raw document feature (e.g., co-author, title, and keywords), fusion feature (e.g., a hybrid publication embedding based on raw document feature), local structural information (e.g., a publication's neighborhood information on a graph), and global structural information (e.g., the interactive information between a node and others on a graph). However, there has been no work taking all the above-mentioned information into account for the AND problem so far. To fill the gap, we propose a novel framework namely MFAND (Multiple Features Driven Author Name Disambiguation). Specifically, we first employ the raw document and fusion feature to construct six similarity graphs for each author name to be disambiguated. Next, the global and local structural information extracted from these graphs is fed into a novel encoder called R3JG, which integrates and reconstructs the above-mentioned four types of information associated with an author, with the goal of learning the latent information to enhance the generalization ability of the MFAND. Then, the integrated and reconstructed information is fed into a binary classification model for disambiguation. Note that, several pruning strategies are applied before the information extraction to remove noise effectively. Finally, our proposed framework is investigated on two real-world datasets, and the experimental results show that MFAND performs better than all state-of-the-art methods.","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":"129389038","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}
Burcu Sayin, E. Krivosheev, Jorge Ramírez, F. Casati, E. Taran, V. Malanina, Jie Yang
{"title":"Crowd-Powered Hybrid Classification Services: Calibration is all you need","authors":"Burcu Sayin, E. Krivosheev, Jorge Ramírez, F. Casati, E. Taran, V. Malanina, Jie Yang","doi":"10.1109/ICWS53863.2021.00019","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00019","url":null,"abstract":"Hybrid classification services are online services that combine machine learning (ML) and humans - either crowd workers or experts - to achieve a classification objective, from relatively simple ones such as deriving the sentiment of a text to more complex ones such as medical diagnoses. This paper takes the first steps toward a science for hybrid classification services, discussing key concepts, challenges, and architectures, and then focusing on a central aspect, that of ML calibration and how it can be achieved with crowdsourced labels.","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":"128822612","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}
{"title":"Sieve: Attention-based Sampling of End-to-End Trace Data in Distributed Microservice Systems","authors":"Zicheng Huang, Pengfei Chen, Guangba Yu, Hongyang Chen, Zibin Zheng","doi":"10.1109/ICWS53863.2021.00063","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00063","url":null,"abstract":"End-to-end tracing plays an important role in understanding and monitoring distributed microservice systems. The trace data are valuable to help find out the anomalous or erroneous behavior of the system. However, the volume of trace data is huge leading to a heavy burden on analyzing and storing them. To reduce the volume of trace data, the sampling technique is widely adopted. However, existing uniform sampling approaches are unable to capture uncommon traces that are more interesting and informative. To tackle this problem, we design and implement Sieve, an online sampler that aims to bias sampling towards uncommon traces by taking advantage of the attention mechanism. The evaluation results on the trace datasets collected from real-world and experimental microservice systems show that Sieve is effective to increase sampling probabilities of the structurally and temporally uncommon traces and reduce the storage space to a large extent by taking a low sampling rate.","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":"128179605","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}
Shivali Agarwal, Raunak Sinha, G. Sridhara, Pratap Das, Utkarsh Desai, Srikanth G. Tamilselvam, Amith Singhee, Hiroaki Nakamuro
{"title":"Monolith to Microservice Candidates using Business Functionality Inference","authors":"Shivali Agarwal, Raunak Sinha, G. Sridhara, Pratap Das, Utkarsh Desai, Srikanth G. Tamilselvam, Amith Singhee, Hiroaki Nakamuro","doi":"10.1109/ICWS53863.2021.00104","DOIUrl":"https://doi.org/10.1109/ICWS53863.2021.00104","url":null,"abstract":"In this paper, we propose a novel approach for monolith decomposition, that maps the implementation structure of a monolith application to a functional structure that in turn can be mapped to business functionality. First, we infer the classes in the monolith application that are distinctively representative of the business functionality in the application domain. This is done using formal concept analysis on statically determined code flow structures in a completely automated manner. Then, we apply a clustering technique, guided by the inferred representatives, on the classes belonging to the monolith to group them into different types of partitions, mainly: 1) functional groups representing microservice candidates, 2) a utility class group, and 3) a group of classes that require significant refactoring to enable a clean microservice architecture. This results in microservice candidates that are naturally aligned with the different business functions exposed by the application. A detailed evaluation on four publicly available applications show that our approach is able to determine better quality microservice candidates when compared to other existing state of the art techniques. We also conclusively show that clustering quality metrics like modularity are not reliable indicators of microservice candidate goodness.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"20 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":"128282654","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}
{"title":"Reviewers ICWS 2021","authors":"","doi":"10.1109/icws53863.2021.00010","DOIUrl":"https://doi.org/10.1109/icws53863.2021.00010","url":null,"abstract":"","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"24 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":"127387785","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}