MONROE-Nettest: A Configurable Tool for Dissecting Speed Measurements in Mobile Broadband Networks

As the demand for mobile connectivity continues to grow, there is a strong need to evaluate the performance of Mobile Broadband (MBB) networks. In the last years, mobile "speed", quantified most commonly by data rate, gained popularity as the widely accepted metric to describe their performance. However, there is a lack of consensus on how mobile speed should be measured. In this paper, we design and implement MONROE-Nettest to dissect mobile speed measurements, and investigate the effect of different factors on speed measurements in the complex mobile ecosystem. MONROE-Nettest is built as an Experiment as a Service (EaaS) on top of the MONROE platform, an open dedicated platform for experimentation in operational MBB networks. Using MONROE-Nettest, we conduct a large scale measurement campaign and quantify the effects of measurement duration, number of TCP flows, and server location on measured downlink data rate in 6 operational MBB networks in Europe. Our results indicate that differences in parameter configuration can significantly affect the measurement results. We provide the complete MONROE-Nettest toolset as open source and our measurements as open data.Comment: 6 pages, 3 figures, submitted to INFOCOM CNERT Workshop 201

Characterizing and Improving the Reliability of Broadband Internet Access

In this paper, we empirically demonstrate the growing importance of reliability by measuring its effect on user behavior. We present an approach for broadband reliability characterization using data collected by many emerging national initiatives to study broadband and apply it to the data gathered by the Federal Communications Commission's Measuring Broadband America project. Motivated by our findings, we present the design, implementation, and evaluation of a practical approach for improving the reliability of broadband Internet access with multihoming.Comment: 15 pages, 14 figures, 6 table

Online Identification of Last-Mile Throughput Bottlenecks on Home Routers

Supervisors: Renata Teixeira (Inria) , Promethee Spathis (UPMC)Advisors: Anna-Kaisa Pietilainen (Inria) , Srikanth Sundaresan (Samsara Networks/ICSI), Nick Feamster (Princeton University)International audienceWe develop a system that runs online on commodity home routers to locate last-mile throughput bottlenecks to the home wireless network or the access ISP. Pinpointing whether the home wireless or the access ISP bottlenecks Internet through-put is valuable for home users who want to better troubleshoot their Internet experience; for access ISPs that receive numerous calls from frustrated home customers; and for informing the debate on regulating the residential broadband market. Developing such a system is challenging because commodity home routers have limited resources. The main contribution of this thesis is to develop a last-mile throughput bottleneck detection algorithm that relies solely on lightweight metrics available in commodity home routers. Our evaluation shows that our system accurately locates last-mile bottlenecks on commodity home routers with little performance degradation

Systems and Methods for Measuring and Improving End-User Application Performance on Mobile Devices

In today's rapidly growing smartphone society, the time users are spending on their smartphones is continuing to grow and mobile applications are becoming the primary medium for providing services and content to users. With such fast paced growth in smart-phone usage, cellular carriers and internet service providers continuously upgrade their infrastructure to the latest technologies and expand their capacities to improve the performance and reliability of their network and to satisfy exploding user demand for mobile data. On the other side of the spectrum, content providers and e-commerce companies adopt the latest protocols and techniques to provide smooth and feature-rich user experiences on their applications. To ensure a good quality of experience, monitoring how applications perform on users' devices is necessary. Often, network and content providers lack such visibility into the end-user application performance. In this dissertation, we demonstrate that having visibility into the end-user perceived performance, through system design for efficient and coordinated active and passive measurements of end-user application and network performance, is crucial for detecting, diagnosing, and addressing performance problems on mobile devices. My dissertation consists of three projects to support this statement. First, to provide such continuous monitoring on smartphones with constrained resources that operate in such a highly dynamic mobile environment, we devise efficient, adaptive, and coordinated systems, as a platform, for active and passive measurements of end-user performance. Second, using this platform and other passive data collection techniques, we conduct an in-depth user trial of mobile multipath to understand how Multipath TCP (MPTCP) performs in practice. Our measurement study reveals several limitations of MPTCP. Based on the insights gained from our measurement study, we propose two different schemes to address the identified limitations of MPTCP. Last, we show how to provide visibility into the end- user application performance for internet providers and in particular home WiFi routers by passively monitoring users' traffic and utilizing per-app models mapping various network quality of service (QoS) metrics to the application performance.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146014/1/ashnik_1.pd