Showing papers by "Veljko Pejovic published in 2014"

InterruptMe: designing intelligent prompting mechanisms for pervasive applications

Abstract: The mobile phone represents a unique platform for interactive applications that can harness the opportunity of an immediate contact with a user in order to increase the impact of the delivered information. However, this accessibility does not necessarily translate to reachability, as recipients might refuse an initiated contact or disfavor a message that comes in an inappropriate moment. In this paper we seek to answer whether, and how, suitable moments for interruption can be identified and utilized in a mobile system. We gather and analyze a real-world smartphone data trace and show that users' broader context, including their activity, location, time of day, emotions and engagement, determine different aspects of interruptibility. We then design and implement InterruptMe, an interruption management library for Android smartphones. An extensive experiment shows that, compared to a context-unaware approach, interruptions elicited through our library result in increased user satisfaction and shorter response times.

SenSocial: a middleware for integrating online social networks and mobile sensing data streams

Abstract: Smartphone sensing enables inference of physical context, while online social networks (OSNs) allow mobile applications to harness users' interpersonal relationships. However, OSNs and smartphone sensing remain disconnected, since obstacles, including the synchronization of mobile sensing and OSN monitoring, inefficiency of smartphone sensors, and privacy concerns, stand in the way of merging the information from these two sources.In this paper we present the design, implementation and evaluation of SenSocial, a middleware that automates the process of obtaining and joining OSN and physical context data streams for the development of ubiquitous computing applications. SenSocial enables instantiation, management and aggregation of context streams from multiple remote devices. Through micro-benchmarks we show that SenSocial successfully and efficiently captures OSN and mobile sensed data streams. We developed two prototype applications in order to evaluate our middleware and we demonstrate that SenSocial significantly reduces the amount of programming effort needed for building social sensing applications.

Anticipatory mobile computing for behaviour change interventions

Abstract: Behavioural change interventions represent a powerful means for tackling a number of health and well-being issues, from obesity to stress and addiction. In the current medical practice, the change is induced through tailored coaching, support and information delivery. However, with the advent of smartphones, innovative ways of delivering interventions are emerging. Indeed, mobile phones, equipped with an array of sensors, and carried by their users at all times, enable therapists to both learn about the user behaviour, and impact the behaviour through the delivery of more relevant and personalised information. In this work we propose harnessing pervasive computing to not only learn from users' past behaviour, but also predict future actions and emotional states, deliver interventions proactively, evaluate their impact at run-time, and over time learn a personal intervention-effect model of a participant.

WhiteRate: A Context-Aware Approachto Wireless Rate Adaptation

Abstract: The increased demand for wireless connectivity emphasizes the necessity of efficient wireless communication as resources such as the available spectrum and energy reserves become limiting factors for network proliferation. Recent advancements in software-defined radio enable high flexibility of the physical layer allowing fine grained transmission adjustments. Although communication efficiency can greatly benefit from physical layer flexibility, modern wireless protocols can neither handle these new opportunities nor allocate resources according to the overlying application needs. In this work we develop WhiteRate, a method for physical layer parameter adaptation that efficiently utilizes available energy and spectrum resources, while maintaining the desired quality of communication. Our solution adjusts the modulation and coding scheme, and channel width to achieve a communication profile that matches application requirements. We implement WhiteRate in GNUradio and evaluate it in both indoor and outdoor environments. We demonstrate improvements on two important fronts: spectrum utilization and energy efficiency. Moreover, we show that by using WhiteRate, both benefits can be achieved simultaneously.

VillageLink: Wide-area wireless coverage

Abstract: White spaces promise to revolutionize the way wireless connectivity is delivered over wide areas. However, large-scale white space networks face the problem of allocating channels to multiple contending users in the wide white space band. To tackle the issue, we first examine wireless propagation in a long-distance outdoor white space testbed and find that a complex combination of free-space loss and antenna effects impacts transmission in white spaces. Thus, a need arises for a strategy that goes beyond simple channel utilization balancing, and uses frequency probing to profile channels according to their propagation properties. We devise VillageLink, a Gibbs sampling-based method that optimizes channel allocation in a distributed manner with a minimum number of channel switching events. Through extensive simulations we demonstrate that VillageLink results in a significant capacity improvement over alternative solutions.