Georgios Larkou

Demo: a programming cloud of smartphones

In this demonstration we present SmartLab1, an exciting experimental testbed of approximately 40+ real Android Smartphones, plus emulated devices, deployed at the Department of Computer Science building at the University of Cyprus. SmartLab provides a public, permanent testbed for the development and testing of smartphone network applications via an intuitive web-based interface. Registered users can upload and install Android executables (APKs) on a number of Android smartphones, capture their output, reboot the devices, create concurrent interactive jobs using MonkeyRunner scripts, interact with the remote devices and many other exciting features. SmartLab aims to facilitate research in smartphone network programming environments, communication protocols, system design, and applications.

Indoor geolocation on multi-sensor smartphones

In this demo, we present an efficient hybrid indoor positioning solution that uses multi-sensory location-oriented observations, including WiFi, accelerometer, gyroscope and digital compass data, that are widely available on Android smartphones.

Managing big data experiments on smartphones

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones.

CLODA: A Crowdsourced Linked Open Data Architecture

In this paper we present our Crowdsourced Linked Open Data Architecture (CLODA), a first attempt to combine crowdsourcing, localization and location-based services to generate, collect, validate and relate real-world, geo-spatial and multidimensional information using smartphones and other mobile devices. CLODA focuses on the construction of URI addressable, interlinked and semi-structured data following the Linked-Open Data (LOD) paradigm. The validity of the constructed data is then contributed by a participating crowd. We present our prototype implementation on top of Google Maps and a blend of in-house technologies, particularly our indoor positioning framework, coined Airplace, our trajectory similarity framework, coined SmartTrace, our neighborhood detection framework, coined Proximity and our smartphone testing platform coined SmartLab.

Demonstration abstract: Crowdsourced indoor localization and navigation with anyplace

In this demonstration paper, we present the Anyplace system that relies on the abundance of sensory data on smartphones (e.g., WiFi signal strength and inertial measurements) to deliver reliable indoor geolocation information. Our system features two highly desirable properties, namely crowdsourcing and scalability. Anyplace implements a set of crowdsourcing-supportive mechanisms to handle the enormous amount of crowdsensed data, filter incorrect user contributions and exploit WiFi data from heterogeneous mobile devices. Moreover, Anyplace follows a big-data architecture for efficient and scalable storage and retrieval of localization and mapping data.

Demonstration abstract: sensor mockup experiments with SmartLab

In this demonstration paper we present SmartLab1, an architecture for managing a cluster of both Android Real Devices (ARDs) and Android Virtual Devices (AVDs) via an intuitive web-based interface. Our architecture consists of several exciting components for re-programming and instrumenting smartphones to perform application testing and data gathering in a facile manner, as well as executing mockup experiments by “feeding” the devices with GPS/sensor readings. We will particularly demonstrate the various components of our architecture that encompasses smartphone sensor data collected by mobile users and organized in our distributed NoSQL document store. The given datasets can then be replayed on our testbed comprising of real and virtual smartphones accessible to developers through our Web 2.0 user interface. We present the applicability of our architecture through various mockup experiments over different application scenarios.