PerCrowd 2019 - 2nd International Workshop on Context-Awareness for Multi-Device Pervasive and Mobile Computing (

Multi-device computing is an emerging research area that is potentiated by the large number of smart devices that proliferate every aspect of our daily lives. By detecting the multi-device context for harnessing collaborative and opportunistic resources in proximity, it is possible to reduce the cost of executing computational tasks in the constrained resources of smart devices, and to diffuse the presence of smart devices beyond their existing computing isolated behavior.
The impact of multi-device computing has found many applications in everyday settings, for which they were not initially conceived, such as continuous multi-device experience for users, formation of proximal infrastructure at the edge network, multi-device remote control systems, multi-device sensing and multi-device autonomous interactions, among others. The goal of PerCrowd 2019 is to explore the impact of multi-device context in self-organizing and opportunistic computing. More in detail, The goal of this workshop is to explore the use and effect of contexts on multi-device settings, whose computational behavior can be propagated within communities of devices for improving their energy consumption and performance.
Original papers addressing theoretical, practical, and technical aspects of opportunistic and self-organizing multi-device communities are solicited. Papers describing prototype implementations and deployment of such applications and systems are particularly welcome. The submission of informative surveys of the state of the art as well as position papers on controversial issues is also encouraged.
Topics of interest include but are not limited to:
- Context-aware multi-device systems and applications, e.g., multi-device sensing, sampling and computation
- Resource extension of pervasive and mobile applications, e.g., screen sharing, multi-device interfaces and multi-device control systems
- Opportunistic multi-device context modeling via crowdsensing
- Algorithms to reduce task complexity via optimal distribution in multi-device setups
- Pervasive computing applications harnessing opportunistic multi-device formation, e.g., location, proximity, underutilized times, etc.
- Self-organizing community construction and evolution
- Usage models for multi-device computing, e.g., incentive models, stability models, decision making models, and privacy models.
- Users experiences towards multi-device systems and applications
- Infrastructure, architectures, and platforms for multi-device systems, as well as, emerging applications for multi-device environments.
- Integration of multi-device systems on the move with proximal infrastructure, e.g., Edge, Cloudlet and Fog
- Lessons and experiences of evaluating context-awareness for multi-device systems and applications