2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)最新文献_第5页

LogSayer: Log Pattern-driven Cloud Component Anomaly Diagnosis with Machine Learning LogSayer:日志模式驱动的云组件异常诊断与机器学习

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212954

Pengpeng Zhou, Yang Wang, Zhenyu Li, Xin Eric Wang, Gareth Tyson, Gaogang Xie

{"title":"LogSayer: Log Pattern-driven Cloud Component Anomaly Diagnosis with Machine Learning","authors":"Pengpeng Zhou, Yang Wang, Zhenyu Li, Xin Eric Wang, Gareth Tyson, Gaogang Xie","doi":"10.1109/IWQoS49365.2020.9212954","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9212954","url":null,"abstract":"Anomaly diagnosis is a critical task for building a reliable cloud system and speeding up the system recovery form failures. With the increase of scales and applications of clouds, they are more vulnerable to various anomalies, and it is more challenging for anomaly troubleshooting. System logs that record significant events at critical time points become excellent sources of information to perform anomaly diagnosis. Never-theless, existing log-based anomaly diagnosis approaches fail to achieve high precision in highly concurrent environments due to interleaved unstructured logs. Besides, transient anomalies that have no obvious features are hard to detect by these approaches. To address this gap, this paper proposes LogSayer, a log pattern-driven anomaly detection model. LogSayer represents the system state by identifying suitable statistical features (e.g. frequency, surge), which are not sensitive to the exact log sequence. It then measures changes in the log pattern when a transient anomaly occurs. LogSayer uses Long Short-Term Memory (LSTM) neural networks to learn the historical correlation of log patterns and applies a BP neural network for adaptive anomaly decisions. Our experimental evaluations over the HDFS and OpenStack data sets show that LogSayer outperforms the state-of-the-art log-based approaches with precision over 98%.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134052527","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: 15

PFcrowd: Privacy-Preserving and Federated Crowdsourcing Framework by Using Blockchain PFcrowd:使用区块链的隐私保护和联合众包框架

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212891

C. Zhang, Yu Guo, Hongwei Du, X. Jia

{"title":"PFcrowd: Privacy-Preserving and Federated Crowdsourcing Framework by Using Blockchain","authors":"C. Zhang, Yu Guo, Hongwei Du, X. Jia","doi":"10.1109/IWQoS49365.2020.9212891","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9212891","url":null,"abstract":"Crowdsourcing is a promising computing paradigm that utilizes collective intelligence to solve complex tasks. While it is valuable, traditional crowdsourcing systems lock computation resources inside each individual system where tasks cannot reach numerous potential workers among the other systems. Therefore, there is a great need to build a federated platform for different crowdsourcing systems to share resources. However, the security issue lies in the center of constructing the federated crowdsourcing platform. Although many studies are focusing on privacy-preserving crowdsourcing, existing solutions require a trusted third party to perform the key management, which is not applicable in our federated platform. The reason is that it is difficult for a third party to be trusted by various systems. In this paper, we present a secure crowdsourcing framework as our initial effort toward this direction, which bridges together the recent advancements of blockchain and cryptographic techniques. Our proposed design, named PFcrowd, allows different crowdsourcing systems to perform encrypted task-worker matching over the blockchain platform without involving any third-party authority. The core idea is to utilize the blockchain to assist the federated crowdsourcing by moving the task recommendation algorithm to the trusted smart contract. To avoid third-party involvement, we first leverage the re-writable deterministic hashing (RDH) technique to convert the problem of federated task-worker matching into the secure query authorization. We then devise a secure scheme based on RDH and searchable encryption (SE) to support privacy-preserving task-worker matching via the smart contract. We formally analyze the security of our proposed scheme and implement the system prototype on Ethereum. Extensive evaluations of real-world datasets demonstrate the efficiency of our design.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"248 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116694814","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: 12

Modeling and Analyzing Live Streaming Performance 建模和分析直播性能

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212876

Tong Zhang, Fengyuan Ren, Bo Wang

{"title":"Modeling and Analyzing Live Streaming Performance","authors":"Tong Zhang, Fengyuan Ren, Bo Wang","doi":"10.1109/IWQoS49365.2020.9212876","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9212876","url":null,"abstract":"Today, live streaming is gaining a rapid growth in use, which refers to streaming the media content recorded and broadcast in real time. In live streaming, latency is of utmost importance since smaller latency means higher user engagement. HTTP adaptive streaming (HAS) is now the most popular live streaming technology, where the video client sends HTTP requests to server to download video segments. The bitrate adaptation (ABR) algorithm inside the client determines bitrate level for every segment. It is of great help for ABR algorithm to quantify the influence of different HAS factors on streaming performance. However, existing work mainly focuses on video on demand (VoD) streaming rather than live streaming. In this paper, we theoretically analyze live streaming performance. We first establish a queuing model to describe playout buffer evolution. Based on the model, we respectively characterize rebuffering probability, rebuffering count and streaming latency, and analyze the effects of chunk arrival rate, arrival interval fluctuation, startup threshold and video skipping on them. From analysis results, we propose insights and recommendations for bitrate adaptation in live streaming and design a simple heuristic ABR algorithm leveraging them. Extensive simulations verify the insights as well as effectiveness of the designed algorithm.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122175735","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

Improving the Path Programmability for Software-Defined WANs under Multiple Controller Failures 改进多控制器故障下软件定义广域网的路径可编程性

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212884

Zehua Guo, Songshi Dou, Wenchao Jiang

{"title":"Improving the Path Programmability for Software-Defined WANs under Multiple Controller Failures","authors":"Zehua Guo, Songshi Dou, Wenchao Jiang","doi":"10.1109/IWQoS49365.2020.9212884","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9212884","url":null,"abstract":"Enabling path programmability is an essential feature of Software-Defined Networking (SDN). During controller failures in Software-Defined Wide Area Networks (SD-WANs), a resilient design should maintain path programmability for offline flows, which were controlled by the failed controllers. Existing solutions can only partially recover the path programmability rooted in two problems: (1) the implicit preferable recovering flows with long paths and (2) the sub-optimal remapping strategy in the coarse-grained switch level. In this paper, we propose Programmability Guardian to improve the path programmability of offline flows while maintaining low communication overhead. These goals are achieved through the fine-grained flow-level mappings enabled by existing SDN techniques. Programmabil-ityGuardian configures the flow-controller mappings to recover offline flows with a similar path programmability, maximize the total programmability of the offline flows, and minimize the total communication overhead for controlling these recovered flows. Simulation results of different controller failure scenarios show that ProgrammabilityGuardian recovers all offline flows with a balanced path programmability, improves the total programmability of the recovered flows up to 68%, and reduces the communication overhead up to 83%, compared with the baseline algorithm.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128568492","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

Supporting Multi-dimensional and Arbitrary Numbers of Ranks for Software Packet Scheduling 支持多维、任意数量级的软件分组调度

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212844

Jiaqi Zheng, Yanan Jiang, Bingchuan Tian, Huaping Zhou, Chen Tian, Guihai Chen, Wanchun Dou

引用次数: 1

Uncontrolled Randomness in Blockchains: Covert Bulletin Board for Illicit Activity 区块链中不受控制的随机性:非法活动的隐蔽公告板

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9213064

Nasser Alsalami, Bingsheng Zhang

{"title":"Uncontrolled Randomness in Blockchains: Covert Bulletin Board for Illicit Activity","authors":"Nasser Alsalami, Bingsheng Zhang","doi":"10.1109/IWQoS49365.2020.9213064","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9213064","url":null,"abstract":"Public blockchains can be abused to covertly store and disseminate potentially harmful digital content which poses a serious regulatory issue. In this work, we show the severity of the problem by demonstrating that blockchains can be exploited to surreptitiously distribute arbitrary content. More specifically, all major blockchain systems use randomized cryptographic primitives, such as digital signatures and non-interactive zero-knowledge proofs; we illustrate how the uncontrolled randomness in such primitives can be maliciously manipulated to enable covert communication and hidden persistent storage. To clarify the potential risk, we design, implement and evaluate our technique against the widely-used ECDSA signature scheme, the CryptoNote's ring signature scheme, and Monero's ring confidential transactions. Importantly, the significance of the demonstrated attacks stems from their undetectability, their adverse effect on the future of decentralized blockchains, and their serious repercussions on users' privacy and crypto funds. Finally, we present a generic framework to immunize blockchains against these attacks.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"114 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113982150","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: 7

Decode-and-Compare: An Efficient Verification Scheme for Coded Edge Computing 译码比较:编码边缘计算的有效验证方案

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212828

M. Fu, Jin Wang, Jianping Wang, K. Lu, A. Jukan, Fei Gu

引用次数: 1

PE-HEALTH: Enabling Fully Encrypted CNN for Health Monitor with Optimized Communication PE-HEALTH:为具有优化通信的健康监视器启用完全加密的CNN

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212822

Yang Liu, Yilong Yang, Zhuo Ma, Ximeng Liu, Zhuzhu Wang, Siqi Ma

{"title":"PE-HEALTH: Enabling Fully Encrypted CNN for Health Monitor with Optimized Communication","authors":"Yang Liu, Yilong Yang, Zhuo Ma, Ximeng Liu, Zhuzhu Wang, Siqi Ma","doi":"10.1109/IWQoS49365.2020.9212822","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9212822","url":null,"abstract":"Cloud-based Convolutional neural network (CNN) is a powerful tool for the healthcare center to provide health condition monitor service. Although the new service has future prospects in the medical, patient's privacy concerns arise because of the sensitivity of medical data. Prior works to address the concern have the following unresolved problems: 1) focus on data privacy but neglect to protect the privacy of the machine learning model itself; 2) introduce considerable communication costs for the CNN inference, which lowers the service quality of the cloud server. To push forward this area, we propose PE-HEALTH, a privacy-preserving health monitor framework that supports fully-encrypted CNN (both input data and model). In PE-HEALTH, the medical Internet of Things (IoT) sensor serves as the health condition data collector. For protecting patient privacy, the IoT sensor additively shares the collected data and uploads the shared data to the cloud server, which is efficient and suited to the energy-limited IoT sensor. To keep model privacy, PE-HEALTH allows the healthcare center to previously deploy, and then, use an encrypted CNN on the cloud server. During the CNN inference process, PE-HEALTH does not need the cloud servers to exchange any extra messages for operating the convolutional operation, which can greatly reduce the communication cost.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122226920","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: 4

Towards the Construction of Global IPv6 Hitlist and Efficient Probing of IPv6 Address Space 构建IPv6全局命中表及有效探测IPv6地址空间

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9212980

Guanglei Song, Lin He, Zhiliang Wang, Jiahai Yang, Tao Jin, Jieling Liu, Guo Li

{"title":"Towards the Construction of Global IPv6 Hitlist and Efficient Probing of IPv6 Address Space","authors":"Guanglei Song, Lin He, Zhiliang Wang, Jiahai Yang, Tao Jin, Jieling Liu, Guo Li","doi":"10.1109/IWQoS49365.2020.9212980","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9212980","url":null,"abstract":"Fast IPv4 scanning has made sufficient progress in network measurement and security research. However, it is infeasible to perform brute-force scanning of the IPv6 address space. We can find active IPv6 addresses through scanning candidate addresses generated by the state-of-the-art algorithms, whose probing efficiency of active IPv6 addresses, however, is still very low. In this paper, we aim to improve the probing efficiency of IPv6 addresses in two ways. Firstly, we perform a longitudinal active measurement study over four months, building a high-quality dataset called hitlist with more than 1.3 billion IPv6 addresses distributed in 45.2k BGP prefixes. Different from previous work, we probe the announced BGP prefixes using a pattern-based algorithm, which makes our dataset overcome the problems of uneven address distribution and low active rate. Secondly, we propose an efficient address generation algorithm DET, which builds a density space tree to learn high-density address regions of the seed addresses in linear time and improves the probing efficiency of active addresses. On the public hitlist and our hitlist, we compare our algorithm DET against state-of-the-art algorithms and find that DET increases the de-aliased active address ratio by 10%, and active address (including aliased addresses) ratio by 14%, by scanning 50 million addresses.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129770287","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

Incorporating Intra-flow Dependencies and Inter-flow Correlations for Traffic Matrix Prediction 基于流内依赖性和流间相关性的交通矩阵预测

2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS) Pub Date : 2020-06-01 DOI: 10.1109/IWQoS49365.2020.9213008

Kaihui Gao, Dan Li, Li Chen, Jinkun Geng, Fei Gui, Yang Cheng, Yue Gu

{"title":"Incorporating Intra-flow Dependencies and Inter-flow Correlations for Traffic Matrix Prediction","authors":"Kaihui Gao, Dan Li, Li Chen, Jinkun Geng, Fei Gui, Yang Cheng, Yue Gu","doi":"10.1109/IWQoS49365.2020.9213008","DOIUrl":"https://doi.org/10.1109/IWQoS49365.2020.9213008","url":null,"abstract":"Traffic matrix (TM) prediction is essential for effective traffic engineering and network management. Based on our analysis of real traffic traces from Wide Area Network, the traffic flows in TM are both time-varying (i.e. with intra-flow dependencies) and correlated with each other (i.e. with inter-flow correlations). However, most existing works in TM prediction ignore inter-flow correlations. In this paper, we propose a novel Attention-based Convolutional Recurrent Neural Network (ACRNN) model to capture both intra-flow dependencies and inter-flow correlations. ACRNN mainly contains two components: 1) Correlational Modeling employs attention-based convolutional structures to capture the correlation of any two flows in TMs; 2) Temporal Modeling uses attention-based recurrent structures to model the long-term temporal dependencies of each flow, and then predicts TMs according inter-flow correlations and intra-flow dependencies. Experiments on two real-world datasets show that, when predicting the next TM, ACRNN model reduces the Mean Squared Error by up to 44.8% and reduces the Mean Absolute Error by up to 30.6%, compared to state-of-the-art method; and the gap is even larger when predicting the next multiple TMs. Besides, simulation results demonstrate that ACRNN's accurate prediction can help traffic engineering to mitigate traffic congestion.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116699913","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: 14