2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)最新文献_第5页

Collaborative Interactive Wireless Charging in a Cyclic Mobispace 循环移动空间中的协同交互无线充电

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624149

Rui Zhang, S. Zhang, Zhuzhong Qian, Mingjun Xiao, Jie Wu, Jidong Ge, Sanglu Lu

{"title":"Collaborative Interactive Wireless Charging in a Cyclic Mobispace","authors":"Rui Zhang, S. Zhang, Zhuzhong Qian, Mingjun Xiao, Jie Wu, Jidong Ge, Sanglu Lu","doi":"10.1109/IWQoS.2018.8624149","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624149","url":null,"abstract":"Electric vehicle (EV) is a promising technological tool for diminishing environmental impact caused by gasoline-consumed transportation. Due to the limited battery capacity, EVs need to be charged frequently in a static charging station and thus waste large amounts of time being out of service. Research previously conducted in this topic have proposed solutions for deployment of charging lanes that can charge in-motion EVs. However, they cannot guarantee that every EV can be operational in their respective entire route. Meanwhile, we observe that EVs have repetitive motions and may cyclically encounter with each other which no prior research having been investigated. In addition, the development on the circuit design of energy transmit antennas can render EVs to be able to bi-directionally, highly efficiently transfer energy between themselves. These two observations enable us to distribute energy among EVs in a collaborative and interactive manner. We consider the cases of both loss-less and lossy energy transfer between EVs. In both cases, we formulate the problem of minimizing the time needed (or energy transferred) to reach a given energy distribution into a series of linear programming problems. When compared with a state-of-the-art algorithm, extensive simulation results show that the proposed algorithms can reduce the balancing time and energy loss by up to 70.60% and 36.59%, respectively.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"792 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116134198","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

Towards a Fast Regular Expression Matching Method Over Compressed Traffic 压缩流量下快速正则表达式匹配方法研究

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624147

Xiuwen Sun, Hao Li, Xingxing Lu, Dan Zhao, Zheng Peng, Chengchen Hu

引用次数: 2

Robust and Rapid Clustering of KPIs for Large-Scale Anomaly Detection 大规模异常检测中kpi的鲁棒快速聚类

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624168

Zhihan Li, Youjian Zhao, Rong Liu, Dan Pei

{"title":"Robust and Rapid Clustering of KPIs for Large-Scale Anomaly Detection","authors":"Zhihan Li, Youjian Zhao, Rong Liu, Dan Pei","doi":"10.1109/IWQoS.2018.8624168","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624168","url":null,"abstract":"For large Internet companies, it is very important to monitor a large number of KPIs (Key Performance Indicators) and detect anomalies to ensure the service quality and reliability. However, large-scale anomaly detection on millions of KPIs is very challenging due to the large overhead of model selection, parameter tuning, model training, or labeling. In this paper we argue that KPI clustering can help: we can cluster millions of KPIs into a small number of clusters and then select and train model on a per-cluster basis. However, KPI clustering faces new challenges that are not present in classic time series clustering: KPIs are typically much longer than other time series, and noises, anomalies, phase shifts and amplitude differences often change the shape of KPIs and mislead the clustering algorithm. To tackle the above challenges, in this paper we propose a robust and rapid KPI clustering algorithm, ROCKA. It consists of four steps: preprocessing, baseline extraction, clustering and assignment. These techniques help group KPIs according to their underlying shapes with high accuracy and efficiency. Our evaluation using real-world KPIs shows that ROCKA gets F-score higher than 0.85, and reduces model training time of a state-of-the-art anomaly detection algorithm by 90%, with only 15% performance loss.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128201538","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: 46

A WiFi-Direct Based Local Communication System 基于WiFi-Direct的本地通信系统

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624171

Zijian Wang, Fuliang Li, Xingwei Wang, Tengfei Li, Tao Hong

引用次数: 12

Toward Accurate Inference of Web Activities from Passive DNS Data 从被动DNS数据中准确推断Web活动

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624158

Jingxiu Su, Zhenyu Li, S. Grumbach, Kave Salamatian, Chunjing Han, Gaogang Xie

引用次数: 3

Ridesharing as a Service: Exploring Crowdsourced Connected Vehicle Information for Intelligent Package Delivery 拼车即服务:探索智能包裹递送的众包互联车辆信息

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624152

Fangxin Wang, Yifei Zhu, Feng Wang, Jiangchuan Liu

{"title":"Ridesharing as a Service: Exploring Crowdsourced Connected Vehicle Information for Intelligent Package Delivery","authors":"Fangxin Wang, Yifei Zhu, Feng Wang, Jiangchuan Liu","doi":"10.1109/IWQoS.2018.8624152","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624152","url":null,"abstract":"Nowadays online shopping has become explosively popular and the vast numbers of generated packages have brought great challenges to the traditional logistics industry, especially the last mile package delivery. Traditional delivery approaches rely on dedicated couriers for package dispatch, while the labor cost is quite expensive and the quality is hard to guarantee due to the diverse delivery addresses and tight deadlines. On the other hand, modern cities are full of available transportation resources such as private car trips. The mobile crowdsourcing through 4G/5G and vehicle-related communications enables the vehicle resources to be connected as an intelligent transportation system. As such, we believe ridesharing will be a core service for connected vehicles, which we refer to as Ridesharing as a Service (RaaS). In this paper, we focus on the quality of service (QoS) of RaaS in the last mile package delivery. Mining from real-world car trips, we build up a citywide routing graph and conduct a personalized travel cost prediction considering both the travel time of each driver and the fuel consumption of each vehicle. We then design an online algorithm to assign proper package delivery tasks to the submitted car trips, aiming to maximize the utility of the ridesharing service provider. Our extensive real-world trace-driven evaluations further demonstrate the superiority of our RaaS based package delivery.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121431218","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: 16

Device-Agnostic Log Anomaly Classification with Partial Labels 基于部分标签的设备无关日志异常分类

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624141

Weibin Meng, Y. Liu, Shenglin Zhang, Dan Pei, Hui Dong, Lei Song, Xulong Luo

引用次数: 38

ImgPricing: Everyone Can Earn Proper Rewards by Simply Taking Photos ImgPricing:每个人都可以通过简单的拍照获得适当的奖励

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624162

Qinya Li, Fan Wu, Guihai Chen

{"title":"ImgPricing: Everyone Can Earn Proper Rewards by Simply Taking Photos","authors":"Qinya Li, Fan Wu, Guihai Chen","doi":"10.1109/IWQoS.2018.8624162","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624162","url":null,"abstract":"A high-quality and large-scale image collection is a fundamental demand in the 3D reconstruction. Crowdsourcing can help us collect lots of diversified images. However, it is not easy to attract people to do this task due to their self-interest. Moreover, the collected images are quality-varying. Those low-quality images may disturb the performance of reconstruction. To avoid low-quality images and lead participants to collect high-quality data, we take images quality into account when allocating rewards. The rewards of participants should be proportionable with their contribution. In this paper, we propose a pricing mechanism, called ImgPricing, to determine the reward of participants in 3D reconstruction system. We model the process of image collection as a cooperative game, and regard each participant's contribution and corresponding image quality as critical factors when allocating rewards. ImgPricing differs from traditional pricing schemes, such as Shapley value, as it introduces the image sequence as an indispensable factor. Finally, we implement our design on the Android platform and evaluate its performance. We use some metrics, such as computational efficiency, fairness and anti-interference, to evaluate ImgPricing and compare with other traditional schemes. Our analyses show ImgPricing is superior to others in terms of computational efficiency and fairness.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121876254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SDNKeeper: Lightweight Resource Protection and Management System for SDN-Based Cloud SDNKeeper:面向sdn云的轻量级资源保护和管理系统

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624135

Xue Leng, Kaiyu Hou, Yan Chen, Kai Bu, Libin Song

{"title":"SDNKeeper: Lightweight Resource Protection and Management System for SDN-Based Cloud","authors":"Xue Leng, Kaiyu Hou, Yan Chen, Kai Bu, Libin Song","doi":"10.1109/IWQoS.2018.8624135","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624135","url":null,"abstract":"SDN-based cloud has the merit of allowing more flexibility in network management, however, the security of network accessing and the correctness of network configuration in SDN-based cloud have not been effectively addressed yet. In this paper, SDNKeeper, a generic and fine-grained policy enforcement system in SDN-based cloud is proposed, which can defend against unauthorized attacks and avoid network resource misconfiguration. With the usage of SDNKeeper, numerous flexible network management policies can be created by administrators, which give administrators the discretionary room on controlling the network resources. To be specific, SDNKeeper can reject any unauthorized network access request at Northbound Interface (NBI), which located between application plane and control plane. Moreover, compared with other traditional policy-based access control systems, SDNKeeper is totally application-transparent and lightweight, which is easy to implement, deploy and runtime configure. Based on the prototype implementation and evaluation, we conclude that SDNKeeper can perform access control accurately with negligible computation overhead whilst the throughput degradation is still within the acceptable range.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129921135","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

Toward Smart and Cooperative Edge Caching for 5G Networks: A Deep Learning Based Approach 面向5G网络的智能和协作边缘缓存:基于深度学习的方法

2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) Pub Date : 2018-06-01 DOI: 10.1109/IWQoS.2018.8624176

Haitian Pang, Jiangchuan Liu, Xiaoyi Fan, Lifeng Sun

{"title":"Toward Smart and Cooperative Edge Caching for 5G Networks: A Deep Learning Based Approach","authors":"Haitian Pang, Jiangchuan Liu, Xiaoyi Fan, Lifeng Sun","doi":"10.1109/IWQoS.2018.8624176","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624176","url":null,"abstract":"The emerging 5G mobile networking promises ultrahigh network bandwidth and ultra-low communication latency (<1ms), benefiting a wide range of applications, including live video streaming, online gaming, virtual and augmented reality, and Vehicle-to-X, to name but a few. The backbone Internet, however, does not keep up, particularly in latency (>100ms), due to its store-and-forward design and the physical barrier from signal propagation speed, not to mention congestion that frequently happens. Caching is known to be effective to bridge the speed gap, which has become a critical component in the 5G deployment as well. Besides storage, 5G base stations (BSs) will also be powered with strong computing modules, offering mobile edge computing (MEC) capability. This paper explores the potentials of edge computing towards improving the cache performance, and we envision a learning-based framework that facilitates smart caching beyond simple frequency- and time-based replace strategies and cooperation among base stations. Within this framework, we develop DeepCache, a deep-learning-based solution to understand the request patterns in individual base stations and accordingly make intelligent cache decisions. Using mobile video, one of the most popular applications with high traffic demand, as a case, we further develop a cooperation strategy for nearby base stations to collectively serve user requests. Experimental results on real-world dataset show that using the collaborative DeepCache algorithm, the overall transmission delay is reduced by 14%∼22%, with a backhaul data traffic saving of 15%∼23%.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126961167","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: 50