CrowdOS: A Ubiquitous Operating System for Crowdsourcing and Mobile Crowd Sensing
This work addresses the problem of fragmented models and frameworks in crowdsourcing applications for researchers and developers, though it appears incremental by building on existing OS concepts.
The paper tackles the lack of compatibility and unified frameworks in crowdsourcing and mobile crowd sensing by proposing CrowdOS, a ubiquitous operating system that integrates lifelong learning and core modules, resulting in significant improvements in efficiency and energy consumption as validated in evaluations.
With the rise of crowdsourcing and mobile crowdsensing techniques, a large number of crowdsourcing applications or platforms (CAP) have appeared. In the mean time, CAP-related models and frameworks based on different research hypotheses are rapidly emerging, and they usually address specific issues from a certain perspective. Due to different settings and conditions, different models are not compatible with each other. However, CAP urgently needs to combine these techniques to form a unified framework. In addition, these models needs to be learned and updated online with the extension of crowdsourced data and task types, thus requiring a unified architecture that integrates lifelong learning concepts and breaks down the barriers between different modules. This paper draws on the idea of ubiquitous operating systems and proposes a novel OS (CrowdOS), which is an abstract software layer running between native OS and application layer. In particular, based on an in-depth analysis of the complex crowd environment and diverse characteristics of heterogeneous tasks, we construct the OS kernel and three core frameworks including Task Resolution and Assignment Framework (TRAF), Integrated Resource Management (IRM), and Task Result quality Optimization (TRO). In addition, we validate the usability of CrowdOS, module correctness and development efficiency. Our evaluation further reveals TRO brings enormous improvement in efficiency and a reduction in energy consumption.