The median webpage has increased in size by more than 80% in the last 4 years. This extra complexity allows for a rich browsing experience, but it hurts the majority of mobile users which still pay for their traffic. This has motivated several data-saving solutions, which aim at reducing the complexity of webpages by transforming their content. Despite each method being unique, they either reduce user privacy by further centralizing web traffic through data-saving middleboxes or introduce web compatibility (Web-compat) issues by removing content that breaks pages in unpredictable ways.

The last three decades have seen much evolution in web and network protocols: amongst them, a transition from HTTP/1.1 to HTTP/2 and a shift from loss-based to delay-based TCP congestion control algorithms. This paper argues that these two trends come at odds with one another, ultimately hurting web performance. Using a controlled synthetic study, we show how delay-based congestion control protocols (e.g., BBR and CUBIC + Hybrid Slow Start) result in the underestimation of the available congestion window in mobile networks, and how that dramatically hampers the effectiveness of HTTP/2. To quantify the impact of such finding in the current web, we evolve the web performance toolbox in two ways. First, we develop Igor, a client-side TCP congestion control detection tool that can differentiate between loss-based and delay-based algorithms by focusing on their behavior during slow start. Second, we develop a Chromium patch which allows fine-grained control on the HTTP version to be used per domain. Using these new web performance tools, we analyze over 300 real websites and find that 67% of sites relying solely on delay-based congestion control algorithms have better performance with HTTP/1.1.

Most popular web browsers include “reader modes” that improve the user experience by removing un-useful page elements. Reader modes reformat the page to hide elements that are not related to the page's main content. Such page elements include site navigation, advertising related videos and images, and most JavaScript. The intended end result is that users can enjoy the content they are interested in, without distraction.

This demo presents how phone functionality can be offloaded from a smartphone over wireless link to a PhoneLet by sharing one SIM card across multiple devices. This can lead to significant cost and network load reductions by decreasing the number of simultaneously connected mobile clients. Furthermore, it can save energy for the mobile user when connected to a powered PhoneLet by offloading phone functionality. It absorbs the energy cost of online presence and inefficient mobile applications' communication patterns, instead providing connectivity for the user over a WiFi link.

Mobile phones in the 3G/4G era enable us to stay connected not only to the voice network, but also to online services like social networks. In this paper, we study the energy and network costs of mobile applications that provide continuous online presence (e.g. WhatsApp, Facebook, Skype). By combining measurements taken on the mobile and the cellular access network, we reveal a detailed picture of the mechanisms selected to implement online presence, along with their effect on handset energy consumption and network signaling traffic.

The popularity of smartphones, cloud computing, and the app store model have led to cellular networks being used in a completely different way than what they were designed for. As a consequence, mobile applications impose new challenges in the design and efficient configuration of constrained networks to maximize application's performance. Such difficulties are largely caused by the lack of cross-layer under- standing of interactions between different entities -applications, devices, the network and its management plane. In this paper, we describe RILAnalyzer, an open-source tool that provides mechanisms to perform network analysis from within a mobile device. RILAnalyzer is capable of recording low-level radio information and accurate cellular net- work control-plane data, as well as user-plane data. We demonstrate how such data can be used to identify previously overlooked issues. Through a small user study across four cellular network providers in two European countries we infer how different network configurations are in reality and explore how such configurations interact with application logic, causing network and energy overheads.

Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable. As a result, developers worldwide are building increasingly complex applications that require ever increasing amounts of computational power and energy. In this paper we propose ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud. ThinkAir exploits the concept of smartphone virtualization in the cloud and provides method-level computation offloading. Advancing on previous work, it focuses on the elasticity and scalability of the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images. We implement ThinkAir and evaluate it with a range of benchmarks starting from simple micro-benchmarks to more complex applications. First, we show that the execution time and energy consumption decrease two orders of magnitude for a N-queens puzzle application and one order of magnitude for a face detection and a virus scan application. We then show that a parallelizable application can invoke multiple VMs to execute in the cloud in a seamless and on-demand manner such as to achieve greater reduction on execution time and energy consumption. We finally use a memory-hungry image combiner tool to demonstrate that applications can dynamically request VMs with more computational power in order to meet their computational requirements.

This demo presents Signposts, a system to provide users with a secure, simple mechanism to establish and maintain communication channels between their personal cloud of named devices. Signpost names exist in the DNSSEC hierarchy, and resolve to secure end-points when accessed by existing DNS clients. Signpost clients intercept user connection intentions while adding privacy and multipath support. Signpost servers co-ordinate clients to dynamically discover routes and overcome the middleboxes that pervade modern edge networks. The demo will show a simple scenario where an individual's personal devices (phone, laptop) are interconnected via Signposts while sitting on different networks behind various middleboxes. As a result they will be able to fetch and push data between each other, demonstrated by, e.g., simple web browsing, even as the network configuration changes.

Today's mobile phones represent a rich and powerful computing platform, given their sensing, processing and communication capabilities. Phones are also part of the everyday life of billions of people, and therefore represent an exceptionally suitable tool for conducting social and psychological experiments in an unobtrusive way.