MicroPlay: A Networking Framework for Local Multiplayer Games

Smartphones are an ideal platform for local multiplayer games, thanks to their computational and networking ca- pabilities as well as their popularity and portability. How- ever, existing game engines do not exploit the locality of players to improve game latency. In this paper, we propose MicroPlay, a complete networking framework for local mul- tiplayer mobile games. To the best of our knowledge, this is the first framework that exploits local connections between smartphones, and in particular, the broadcast nature of the wireless medium, to provide smooth, accurate rendering of all players with two desired properties. First, it performs direct-input rendering (i.e., without any inter- or extrapola- tion of game state) for all players; second, it provides very low game latency. We implement a MicroPlay prototype on Android phones, as well as an example multiplayer racing game, called Racer, in order to demonstrate MicroPlay’s ca- pabilities. Our experiments show that cars can be rendered smoothly, without any prediction of state, and with only 20– 40 ms game latency

Improving Location Accuracy And Network Capacity In Mobile Networks

Todays mobile computing must support a wide variety of applications such as location-based services, navigation, HD media streaming and augmented reality. Providing such services requires large network bandwidth and precise localization mechanisms, which face significant challenges. First, new (real-time) localization mechanisms are needed to locate neighboring devices/objects with high accuracy under tight environment constraints, e.g. without infrastructure support. Second, mobile networks need to deliver orders of magnitude more bandwidth to support the exponentially increasing traffic demand, and adapt resource usage to user mobility.In this dissertation, we build effective and practical solutions to address these challenges. Our first research area is to develop new localization mechanisms that utilize the rich set of sensors on smartphones to implement accurate localization systems. We propose two designs. The first system tracks distance to nearby devices with centimeter accuracy by transmitting acoustic signals between the devices. We design robust and efficient signal processing algorithms that measure distances accurately on the fly, thus enabling real-time user motion tracking. Our second system locates a transmitting device in real-time using commodity smart- phones. Driving by the insight that rotating a wireless receiver (smartphone) around a users body can effectively emulate the sensitivity and functionality of a directional antenna, we design a rotation-based measurement algorithm that can accurately predict the direction of the target transmitter and locate the transmitter with a few measurements.Our second research area is to develop next generation mobile networks to significantly boost network capacity. We propose a drastically new outdoor picocell design that leverages millimeter wave 60GHz transmissions to provide multi-Gbps bandwidth for mobile users. Using extensive measurements on off-the-shelf 60GHz radios, we explore the feasibility of 60GHz picocells by characterizing range, attenuation due to reflections, sensitivity to movement and blockage, and interference in typical urban environments. Our results dispel some common myths on 60GHz, and show that 60GHz outdoor picocells are indeed a feasible approach for delivering orders of magnitude increase in network capacity.Finally, we seek to capture and understand user mobility patterns which are essential in mobile network design and deployment. While traditional methods of collecting human mobility traces are expensive and not scalable, we explore a new direction that extracts large-scale mobility traces through widely available geosocial datasets, e.g. Foursquare "check-in" datasets. By comparing raw GPS traces against Foursquare checkins, we analyze the value of using geosocial datasets as representative traces of human mobility. We then develop techniques to both "sanitize" and "repopulate" geosocial traces, thus producing detailed mobility traces more indicative of actual human movement and suitable for mobile network design