Poster Sessions

PieBridge: A Cross-DR scale Large Data Transmission Scheduling System

Y. Zhang (Tsinghua University), K. Xu (Tsinghua University), G. Yao (Baidu), M. Zhang (Baidu), X. Nie (Tsinghua University)

Abstract: Cross-DR WAN (Datacenter Region Wide Area Network) with various services are deployed to provide timely data information and analytics for users in a wide range of geographical locations. For its reliability and performance, data duplication synchronization is essential among different IDCs (Internet datacenters). However, this problem poses a challenge. First, data duplication requires huge amount of bandwidth whereas the bandwidth of cross-DR links and the upload/download rates of server interfaces are limited. Second, data transmissions are time sensitive, but the current network cannot complete such tasks in a timely manner. In this work, we present PieBridge, a cross-RD data duplicate transmission platform that accommodates hundreds of TBs of data generated from user applications online data analytics. We deployed PieBridge on the IDCs of Baidu and obtained promising performance results in comparison with the prevalent approaches.

A Longitudinal Analysis of .i2p Leakage in the Public DNS Infrastructure

S. Jeong (Korea University), A. Kang (SUNY Buffalo), J. Kim (Chung-Ang University), H. Kim (Korea University), A. Mohaisen (SUNY Buffalo)

Abstract: The Invisible Internet Project (I2P) is an overlay network that provides secure and anonymous communication channels. EepSites are the anonymous websites hosted in the I2P network. To access the eepSites, DNS requests of a domain name suffixed with the {\sf .i2p} pseudo top-level domain (TLD) are routed within the I2P network. However, not only that {\sf .i2p} queries are leaking in the public DNS infrastructure, but also such leakage has various plausible root causes and implications that are different from other related leakage. In this paper, we analyze the leaked {\sf .i2p} requests captured in the A and J root name servers of the public DNS, showing that a large number of queries are observed and outlining various potential directions of addressing such leakage.

Best Effort Task Scheduling for Data Parallel Jobs

Z. Li (National University of Defense Technology), Y. Zhang (National University of Defense Technology), Y. Zhao (National University of Defense Technology), Y. Peng (National University of Defense Technology), D. Li (National University of Defense Technology)

Abstract: The tasks of data-parallel computation jobs come up with diverse and time-varying resource requirements. The dynamic nature of task requirements brings challenges on making good scheduling decisions, due to it is hard to keep work-conserving. In this paper, we present BETS to cope with the requirement dynamics that aims at utilizing cluster resources fully. BETS employs a task model that represents for runtime task requirements, a coarse-grained task pipeline to make use of resources in a time-division multiplexing fashion, and fine-grained resource management to guarantee performance.

Efficient Remapping of Internet Routing Events

E. Fazzion (Universidade Federal de Minas Gerais), Í. Cunha (Universidade Federal de Minas Gerais), D. Guedes (Universidade Federal de Minas Gerais), W. Meira Jr. (Universidade Federal de Minas Gerais), R. Teixeira (Inria), D. Veitch (University of Technology Sydney), C. Diot (Safran)

Abstract: Routing events impact multiple paths in the Internet, but current active topology mapping techniques monitor paths independently. Detecting a routing event on one Internet path does not trigger any measurements on other possibly-impacted paths. This approach leads to outdated and inconsistent routing information. We characterize routing events in the Internet and investigate probing strategies to efficiently identify paths impacted by a routing event. Our results indicate that targeted probing can help us quickly remap routing events and maintain more up-to-date and consistent topology maps.

Privacy-Aware Infrastructure for Managing Personal Data

Y. Amar (Queen Mary University of London), H. Haddadi (Queen Mary University of London), R. Mortier (University of Cambridge)

Abstract: In recent times, we have seen a proliferation of personal data. This can be attributed not just to a larger proportion of our lives moving online, but also through the rise of ubiquitous sensing through mobile and IoT devices. Alongside this surge, concerns over privacy, trust, and security are expressed more and more as different parties attempt to take advantage of this rich assortment of data. The Databox seeks to enable all the advantages of personal data analytics while at the same time enforcing **accountability** and **control** in order to protect a user's privacy. In this work, we propose and delineate a personal networked device that allows users to **collate**, **curate**, and **mediate** their personal data.

Performance Evaluation of Locator/Identifier Separation Protocol through RIPE Atlas

Y. Li (Telecom ParisTech), L. Iannone (Telecom ParisTech)

Abstract: The mph{Locator/Identifier Separation Protocol} (LISP) introduces several benefits to the Internet architecture, yet, since it is just in the initial deployment stage, comprehensive understanding of its integration performance with legacy Internet becomes essential. We leverage on RIPE Atlas, the largest Internet measurement infrastructure, to conduct large scale measurements analysis to provide the feedback to improve LISP technology. The preliminary evaluations show that LISP generally has a reliable performance, compared with the existing Internet. From our vantage point, we observe that LISP introduces a non-negligible latency for the European and North American destinations, occasionally some extremely large delay, however, it shows a faster connection for the Asian intercontinental transmission.

TafLoc: Time-adaptive and Fine-grained Device-free Localization with Little Cost

L. Chang (Northwest University), J. Xiong (Singapore Management University), X. Chen (Northwest University), J. Wang (Northwest University), J. Hu (Northwest University), D. Fang (Northwest University), W. Wang (Northwest University), L. Chang (Northwest University)

Abstract: Many emerging applications drive the needs of device-free localization (DfL), in which the target can be localized without any device attached. Because of the ubiquitousness of WiFi infrastructures nowadays, the widely available Received Signal Strength (RSS) information at the WiFi Access points are commonly employed for localization purposes. However, current RSS based DfL systems have one main drawback hindering their real-life applications. That is, the RSS measurements (fingerprints) vary slowly in time even without any change in the environment and frequent updates of RSS at each location lead to a high human labor cost. In this paper, we propose an RSS based low cost DfL system named TafLoc which is able to accurately localize the target over a long time scale. To reduce the amount of human labor cost in updating the RSS fingerprints, TafLoc represents the RSS fingerprints as a matrix which has several unique properties. Based on these properties, we propose a novel fingerprint matrix reconstruction scheme to update the whole fingerprint database with just a few RSS measurements, thus the labor cost is greatly reduced. Extensive experiments illustrate the effectiveness of TafLoc, outperforming the state-of-the-art RSS based DfL systems.

A First Look into Transnational Routing Detours

A. Edmundson (Princeton University), R. Ensafi (Princeton University), N. Feamster (Princeton University), J. Rexford (Princeton University)

Abstract: An increasing number of countries are passing laws that facilitate the mass surveillance of their citizens. In response, governments and citizens are increasingly paying attention to the countries that their Internet traffic traverses. In some cases, countries are taking extreme steps, such as building new IXPs and encouraging local interconnection to keep local traffic local. We find that although many of these efforts are extensive, they are often futile, due to the inherent lack of hosting and route diversity for many popular sites. We investigate how the use of overlay network relays and the DNS open resolver infrastructure can prevent traffic from traversing certain jurisdictions.

PathCache: A Path Prediction Toolkit

R. Singh (Stony Brook University), P. Gill (Stony Brook University)

Abstract: Path prediction on the Internet has been a topic of research in the networking community for close to a decade. Applications of path prediction solutions have ranged from optimizing selection of peers in peer- to-peer networks to improving and debugging CDN predictions. Recently, revelations of traffic correlation and surveillance on the Internet have raised the topic of path prediction in the context of network security. Specifically, predicting network paths can allow us to identify and avoid given organizations on network paths (e.g., to avoid traffic correlation attacks in Tor) or to infer the impact of hijacks and interceptions when direct measurements are not available. In this poster we propose the design and implementation of PathCache which aims to reuse measurement data to estimate AS level paths on the Internet. Unlike similar systems, PathCache does not assume that routing on the Internet is destination based. Instead, we develop an algorithm to compute confidence in paths between ASes. These multiple paths ranked by their confidence values are returned to the user.

Application-specific Acceleration Framework for Mobile Applications

B. Choi (KAIST), J. Kim (KAIST), D. Han (KAIST)

Abstract: Minimizing response times for mobile applications is critical for quality user experience that often impacts the revenue of mobile services. Generalized approaches to accelerated mobile applications (e.g., TCP acceleration, SPDY, compression) are less effective because they do not take account for application specific behaviors. In contrast, application specific approaches build application-specific proxies by leveraging the app-specific protocol behaviors to enable dynamic caching and/or prefetching. However, this is non-trivial because it requires manual analysis of application level protocols and their interactions. Therefore, only a small number of apps enjoyed the benefit. This paper addresses the problem of scaling the number of applications by automating the process. To this end, we present a framework for mobile application acceleration that leverages automatic protocol analysis to automatically discover opportunities for app acceleration. The framework automatically finds out when and where to prefetch or perform dynamic caching. We present the framework design and a preliminary result that demonstrates its viability.