Exploiting The Stable Fixture Matching Game For Mobile Crowd Sensing: A Local Event Sharing Framework

The surging of smartphone sensing, wireless networking and social media have enabled a great variety of applications, such as environment surveillance, marketing, health monitoring and so on. This new paradigm is typically referred to as mobile crowd sensing (MCS). Existing solutions on MCS are majorly based on text, image and video analysis using the distributively sensed data. One shortcoming of such approaches is the data processing delay. Considered as an enhanced function to the temporary social media services, for example Twitter, we propose a real-time event sharing framework that provides mobile users with the freedom of expressing their various interests regarding the event data. To achieve such goals, we introduce a novel Hashtag design, which is a combination of five types of information: time, location, keywords, data type and data size. Users, by comparing their own interests with the uploaded Hashtags in the Twitter server, can search for suitable partner users to share information with in real time. The formulated user sharing/pairing problem is modeled as the Stable Fixture (SF) matching game, and can be solved by the Irving's SF (ISF) algorithm in a distributive manner. The simulations have demonstrated the superiority of our proposed ISF method by comparing with both centralized method and heuristic algorithms.