2015 IEEE Conference on Computer Communications (INFOCOM)最新文献_第7页

P3: Joint optimization of charger placement and power allocation for wireless power transfer P3:无线电力传输中充电器放置与功率分配的联合优化

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218622

S. Zhang, Zhuzhong Qian, Fanyu Kong, Jie Wu, Sanglu Lu

{"title":"P3: Joint optimization of charger placement and power allocation for wireless power transfer","authors":"S. Zhang, Zhuzhong Qian, Fanyu Kong, Jie Wu, Sanglu Lu","doi":"10.1109/INFOCOM.2015.7218622","DOIUrl":"https://doi.org/10.1109/INFOCOM.2015.7218622","url":null,"abstract":"Wireless power transfer is a promising technology to extend the lifetime of, and thus enhance the usability of, the energy-hungry battery-powered devices. It enables energy to be wirelessly transmitted from power chargers to energy receiving devices. Existing studies have mainly focused on maximizing network lifetime, optimizing charging efficiency, minimizing charging delay, etc. Different from these works, our objective is to optimize charging quality in a 2-D target area. Specifically, we consider the following charger Placement and Power allocation Problem (P3): Given a set of candidate locations for placing chargers, find a charger placement and a corresponding power allocation to maximize the charging quality, subject to a power budget. We prove that P3 is NP-complete. We first study P3 with fixed power levels, for which we propose a (1-1/e)-approximation algorithm; we then design an approximation algorithm of factor 1-1/e / 2L for P3, where e is the base of the natural logarithm, and L is the maximum power level of a charger. We also show how to extend P3 in a cycle. Extensive simulations demonstrate that, the gap between our design and the optimal algorithm is within 4.5%, validating our theoretical results.","PeriodicalId":342583,"journal":{"name":"2015 IEEE Conference on Computer Communications (INFOCOM)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134410563","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: 66

MOOC performance prediction via clickstream data and social learning networks 基于点击流数据和社交学习网络的MOOC性能预测

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218617

Christopher G. Brinton, M. Chiang

{"title":"MOOC performance prediction via clickstream data and social learning networks","authors":"Christopher G. Brinton, M. Chiang","doi":"10.1109/INFOCOM.2015.7218617","DOIUrl":"https://doi.org/10.1109/INFOCOM.2015.7218617","url":null,"abstract":"We study student performance prediction in Massive Open Online Courses (MOOCs), where the objective is to predict whether a user will be Correct on First Attempt (CFA) in answering a question. In doing so, we develop novel techniques that leverage behavioral data collected by MOOC platforms. Using video-watching clickstream data from one of our MOOCs, we first extract summary quantities (e.g., fraction played, number of pauses) for each user-video pair, and show how certain intervals/sets of values for these behaviors quantify that a pair is more likely to be CFA or not for the corresponding question. Motivated by these findings, our methods are designed to determine suitable intervals from training data and to use the corresponding success estimates as learning features in prediction algorithms. Tested against a large set of empirical data, we find that our schemes outperform standard algorithms (i.e., without behavioral data) for all datasets and metrics tested. Moreover, the improvement is particularly pronounced when considering the first few course weeks, demonstrating the “early detection” capability of such clickstream data. We also discuss how CFA prediction can be used to depict graphs of the Social Learning Network (SLN) of students, which can help instructors manage courses more effectively.","PeriodicalId":342583,"journal":{"name":"2015 IEEE Conference on Computer Communications (INFOCOM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123967601","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: 145

ActCap: Accelerating MapReduce on heterogeneous clusters with capability-aware data placement ActCap:通过能力感知的数据放置在异构集群上加速MapReduce

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218509

Bo Wang, Jinlei Jiang, Guangwen Yang

引用次数: 25

SEISA: Secure and efficient encrypted image search with access control 安全，高效的加密图像搜索与访问控制

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218593

Jiawei Yuan, Shucheng Yu, Linke Guo

{"title":"SEISA: Secure and efficient encrypted image search with access control","authors":"Jiawei Yuan, Shucheng Yu, Linke Guo","doi":"10.1109/INFOCOM.2015.7218593","DOIUrl":"https://doi.org/10.1109/INFOCOM.2015.7218593","url":null,"abstract":"Image search has been widely deployed in many applications for the rich content that images contain. In the era of big data, image search engines have to be hosted in data centers. As a viable solution, outsourcing the image search to public clouds is an economic choice for many small organizations. However, as many images contain sensitive information, e.g., healthcare information and personal faces/locations, directly outsourcing image search services to public clouds obviously raises privacy concerns. With this observation, several attempts are made towards secure image search over encrypted dataset, but they are limited by either search accuracy or search efficiency. In this paper, we propose a lightweight secure image search scheme over encrypted data, namely SEISA. Compared with image search techniques over plaintexts, SEISA only increases about 9% search cost and sacrifices about 3% on search accuracy. SEISA also efficiently supports search access control by employing a novel polynomial based design, which enables data owners to define who can search a specific image. Furthermore, we design a secure k-means outsourcing algorithm that significantly saves the data owner's cost. To demonstrate SEISA's performance, we implement a prototype of SEISA on Amazon EC2 cloud over a dataset with 10 million images.","PeriodicalId":342583,"journal":{"name":"2015 IEEE Conference on Computer Communications (INFOCOM)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128823536","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: 69

On the accuracy of smartphone-based mobile network measurement 基于智能手机的移动网络测量精度研究

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218402

Weichao Li, Ricky K. P. Mok, Daoyuan Wu, R. Chang

{"title":"On the accuracy of smartphone-based mobile network measurement","authors":"Weichao Li, Ricky K. P. Mok, Daoyuan Wu, R. Chang","doi":"10.1109/INFOCOM.2015.7218402","DOIUrl":"https://doi.org/10.1109/INFOCOM.2015.7218402","url":null,"abstract":"As most of mobile apps rely on network connections for their operations, measuring and understanding the performance of mobile networks is becoming very important for end users and operators. Despite the availability of many measurement apps, their measurement accuracy has not received sufficient scrutiny. In this paper, we appraise the accuracy of smartphone-based network performance measurement using the Android platform and the network round-trip time as the metric. We use a multiple-sniffer testbed to overcome the challenge of obtaining a complete trace for acquiring the required timestamps. Our experiment results show that the RTTs measured by the apps are all inflated, ranging from a few milliseconds (ms) to tens of milliseconds. Moreover, the 95% confidence interval can be as high as 2.4ms. A finer-grained analysis reveals that the delay inflation can be introduced both in the Dalvik VM (DVM) and below the Linux kernel. The in-DVM overhead can be mitigated but the other cannot be. Finally, we propose and implement a native app which uses HTTP messages for network measurement, and the delay inflation can be kept under 5ms for almost all cases.","PeriodicalId":342583,"journal":{"name":"2015 IEEE Conference on Computer Communications (INFOCOM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117020394","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: 26

Capturing resource tradeoffs in fair multi-resource allocation 在公平的多资源分配中获取资源权衡

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218479

Doron Zarchy, David Hay, Michael Schapira

引用次数: 21

Static power of mobile devices: Self-updating radio maps for wireless indoor localization 移动设备的静态功率:用于室内无线定位的自更新无线地图

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218639

Chenshu Wu, Zheng Yang, Chaowei Xiao, Chaofan Yang, Yunhao Liu, M. Liu

{"title":"Static power of mobile devices: Self-updating radio maps for wireless indoor localization","authors":"Chenshu Wu, Zheng Yang, Chaowei Xiao, Chaofan Yang, Yunhao Liu, M. Liu","doi":"10.1109/INFOCOM.2015.7218639","DOIUrl":"https://doi.org/10.1109/INFOCOM.2015.7218639","url":null,"abstract":"The proliferation of mobile computing has prompted WiFi-based indoor localization to be one of the most attractive and promising techniques for ubiquitous applications. A primary concern for these technologies to be fully practical is to combat harsh indoor environmental dynamics, especially for long-term deployment. Despite numerous research on WiFi fingerprint-based localization, the problem of radio map adaptation has not been sufficiently studied and remains open. In this work, we propose AcMu, an automatic and continuous radio map self-updating service for wireless indoor localization that exploits the static behaviors of mobile devices. By accurately pinpointing mobile devices with a novel trajectory matching algorithm, we employ them as mobile reference points to collect real-time RSS samples when they are static. With these fresh reference data, we adapt the complete radio map by learning an underlying relationship of RSS dependency between different locations, which is expected to be relatively constant over time. Extensive experiments for 20 days across 6 months demonstrate that AcMu effectively accommodates RSS variations over time and derives accurate prediction of fresh radio map with average errors of less than 5dB. Moreover, AcMu provides 2x improvement on localization accuracy by maintaining an up-to-date radio map.","PeriodicalId":342583,"journal":{"name":"2015 IEEE Conference on Computer Communications (INFOCOM)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127010647","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: 66

Video acuity assessment in mobile devices 移动设备视频清晰度评估

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218361

E. Baik, A. Pande, Chris Stover, P. Mohapatra

引用次数: 13

On the impossibility of efficient self-stabilization in virtual overlays with churn 带扰动的虚拟叠加中有效自稳定的不可能性

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218394

Stefanie Roos, T. Strufe

引用次数: 6

Contextual-code: Simplifying information pulling from targeted sources in physical world 上下文代码:简化从物理世界的目标源提取的信息

2015 IEEE Conference on Computer Communications (INFOCOM) Pub Date : 2015-08-24 DOI: 10.1109/INFOCOM.2015.7218611

Yang Tian, Kaigui Bian, G. Shen, Xiaochen Liu, Xiaoguang Li, T. Moscibroda

{"title":"Contextual-code: Simplifying information pulling from targeted sources in physical world","authors":"Yang Tian, Kaigui Bian, G. Shen, Xiaochen Liu, Xiaoguang Li, T. Moscibroda","doi":"10.1109/INFOCOM.2015.7218611","DOIUrl":"https://doi.org/10.1109/INFOCOM.2015.7218611","url":null,"abstract":"The popularity of QR code clearly indicates the strong demand of users to acquire (or pull) further information from interested sources (e.g., a poster) in the physical world. However, existing information pulling practices such as a mobile search or QR code scanning incur heavy user involvement to identify the targeted posters. Meanwhile, businesses (e.g., advertisers) are also interested to learn about the behaviors of potential customers such as where, when, and how users show interests in their offerings. Unfortunately, little such context information are provided by existing information pulling systems. In this paper, we present Contextual-Code (C-Code) - an information pulling system that greatly relieves users' efforts in pulling information from targeted posters, and in the meantime provides rich context information of user behavior to businesses. C-Code leverages the rich contextual information captured by the smartphone sensors to automatically disambiguate information sources in different contexts. It assigns simple codes (e.g., a character) to sources whose contexts are not discriminating enough. To pull the information from an interested source, users only need to input the simple code shown on the targeted source. Our experiments demonstrate the effectiveness of C-Code design. Users can effectively and uniquely identify targeted information sources with an average accuracy over 90%.","PeriodicalId":342583,"journal":{"name":"2015 IEEE Conference on Computer Communications (INFOCOM)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126374421","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