Youngbin Im

MASERATI: mobile adaptive streaming based on environmental and contextual information

Wireless/mobile video streaming has become increasingly popular, which makes wireless link bandwidth scarce. To provide streaming services to mobile users, it is crucial to adapt to the link condition and traffic fluctuation. We investigate which factors in natural environments and user contexts affect the available link bandwidth. To this end, we conduct a measurement study which contains 38 repeated trips along the same 5~km circular road in the campus of Seoul National University in April and May 2013. We measure the download throughput of video streaming from two different networks (3G and 4G LTE) with varying location, time, humidity, and speed. Our measurement results reveal that the humidity and location are the more important factors in the 3G network, while the speed, time, and location are the more important ones in the 4G LTE network to predict the available link bandwidth. We then propose an adaptive video streaming framework, MASERATI, where the information of environments and contexts is used to predict the available bandwidth. We demonstrate that MASERATI significantly improves the QoE of mobile streaming users in terms of the playout success rate, video quality, and stability, in comparison to DASH.

AMUSE: Empowering Users for Cost-Aware Offloading with Throughput-Delay Tradeoffs

Mobile users face a tradeoff between cost, throughput, and delay in making their offloading decisions. To navigate this tradeoff, we propose AMUSE (Adaptive bandwidth Management through USer-Empowerment), a practical, costaware WiFi offloading system that takes into account a users throughput-delay tradeoffs and cellular budget constraint. Based on predicted future usage and WiFi availability, AMUSE decides which applications to offload to what times of the day. To practically enforce the assigned rate of each TCP application, we introduce a receiver-side TCP bandwidth control algorithm that adjusts the rate by controlling the TCP advertisement window from the user side. We implement AMUSE on Windows 7 tablets and evaluate its effectiveness with 3G and WiFi usage data obtained from a trial with 25 mobile users. Our results show that AMUSE improves user utility.

Vertical handovers in multiple heterogeneous wireless networks: a measurement study for the future internet

As the access patterns of mobile users are diverse and their traffic demand is growing, multiple wireless access networks become dominant and their coexistence will be the norm in the future Internet infrastructure. To evaluate protocols and algorithms in these heterogeneous wireless networking environments, testbed-based experiments are of crucial importance since mathematical modeling and simulation cannot reflect the high complexity of systems and wireless link dynamics sufficiently. Leveraging femtocell technologies, we propose and build a testbed in which WiFi access points and WiMAX base stations are integrated. We also implement the vertical handover functionality through the SIP protocol, and carry out comprehensive measurements to analyze vertical handover delays. The testbed measurements of vertical handovers reveal that the DHCP mechanism, the authentication process in WiMAX, and the probing process in WiFi incur substantial delay.

A Practical Evaluation of Rate Adaptation Algorithms in HTTP-based Adaptive Streaming

Abstract The HTTP-based Adaptive Streaming (HAS) techniques are widely used in Internet video streaming services, including YouTube and Netflix. The Dynamic Adaptive Streaming over HTTP (DASH) is the latest international standard that facilitates the interoperability of different HAS techniques of various vendors. DASH specification defines the media presentation description (MPD), which describes a list of available content, URL addresses, and the segment format. The rate adaptation algorithms, however, are not part of the standard, and the details of the algorithms are left to vendors. As a result, there are many different algorithms adopted in both commercial and open source players while the detailed algorithms and their performance are barely understood. In this paper, we investigate the detailed operations of the different players by code level analysis and through reverse engineering. Specifically, we present the pseudo codes of 3 open source players and devise a method to obtain the detailed operation information, e.g., bitrate and buffer amount, of popular streaming players whose source codes are not publicly available. We conduct extensive experiments on our testbed and provide suggestions based on the behaviors of these players, including the repeated over-estimation of the available bandwidth, unfair bitrate selection when multiple players compete for the bandwidth, and insensitivity of Quick UDP Internet Connections (QUIC) protocol to the varying network bandwidth.

FIRM: Flow-based Interference-aware Route Management in Wireless Mesh Networks

In IEEE 802.11-based wireless mesh networks, routing is crucial in achieving high throughput in face of both interflow and intra-flow interference. Prior work focuses on finding the maximum available bandwidth path when a new flow enters the network. However, few has considered the effect of the new flow on the throughput of the existing flows. We propose a routing framework that uses the topology map of a mesh network with the carrier sense and interference relations and estimates the available bandwidth of a candidate path. We propose two algorithms for finding a route for a new flow: (1) FIRM searches for the maximum bandwidth path for the new flow, and (2) FIRM + not only considers the available bandwidth of a path for the new flow, but also the amount of throughput degradation of existing flows. We implement and evaluate FIRM and FIRM + with the IRU routing algorithm on a 15 node indoor IEEE 802.11a testbed. Various experiments reveal that FIRM + achieves the highest total throughput of all flows.

Calibrating Time-variant, Device-specific Phase Noise for COTS WiFi Devices

Current COTS WiFi based work on wireless motion sensing extracts human movements such as keystroking and hand motion mainly from amplitude training to classify different types of motions, as obtaining meaningful phase values is very challenging due to time-varying phase noises occurred with the movement. However, the methods based only on amplitude training are not very practical since their accuracy is not environment and location independent. This paper proposes an effective phase noise calibration technique which can be broadly applicable to COTS WiFi based motion sensing. We leverage the fact that multi-path for indoor environment contains certain static paths, such as reflections from wall or static furniture, as well as dynamic paths due to human hand and arm movements. When a hand moves, the phase value of the signal from the hand rotates as the path length changes and causes the superposition of signals over static and dynamic paths in antenna and frequency domain. To evaluate the effectiveness of the proposed technique, we experiment with a prototype system that can track hand gestures in a non-intrusive manner, i.e. users are not equipped with any device, using COTS WiFi devices. Our evaluation shows that calibrated phase values provide much rich, yet robust information on motion tracking -- 80th percentile angle estimation error up to 14 degrees, 80th percentile tracking error up to 15 cm, and its robustness to the environment and the speed of movement.

FLARE: Coordinated Rate Adaptation for HTTP Adaptive Streaming in Cellular Networks

Fog computing is an emerging architecture that aims to run applications on multiple devices that lie on a continuum from cloud servers to personal user smartphones. These architectures allow applications to optimize over the information stored at and functionalities run on each device, based on individual device capabilities. We demonstrate the benefits of this approach for mobile video streaming. Existing HAS (HTTP adaptive streaming) techniques often suffer from problems like unstable video quality and suboptimal resource utilization. We find that a lack of coordination prevents both clientand network-side HAS techniques from solving them. However, our fog approach can exploit existing telecommunication APIs, which expose network capabilities to applications, in order to coordinate between clients and the network. Our coordinated HAS solution, FLARE, optimizes the total utility of all clients in a cell while maintaining stable video quality and supporting user- and device-specific needs. We implement FLARE on a commodity LTE femtocell and use the implementation to conduct the first comparison of HAS players on an LTE femtocell. By conducting extensive experiments using the ns-3 simulator, we also demonstrate that FLARE (i) enhances the average video bitrate, (ii) achieves stable video quality, and (iii) balances the throughput of simultaneous video and data flows, compared to other representative HAS solutions.