Title: Middleware for Mobile Sensing Applications in Urban Environments Abstract: Urbanets are spontaneously created urban networks consisting of mobile multisensor platforms, such as smart phones and vehicular systems, individual sensors incorporated in buildings or roads, and public sensor networks deployed by municipalities. With their extended sensing coverage, Urbanets enable people-centric mobile applications capable of sensing the physical world anytime, anywhere. Urbanet applications can be developed in a distributed manner to provide better performance, save network resources, and be more scalable and fault-tolerant. However, programming such applications using conventional distributed computing paradigms is hard, if not impossible. These paradigms assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. As the domain of Urbanet applications diversifies, distributed middleware architectures that can cope with network volatility and provide flexible programming support will become necessary. This talk presents Contory and Context-aware Migratory Services, two distributed middleware architectures capable of supporting the development and execution of Urbanet applications. Contory offers a declarative programming model that views Urbanets as a distributed sensor database. Contory transparently and dynamically adapts to the changing operating conditions and lets applications assess the quality of the provided results. Context-aware Migratory Services provides a client-server paradigm, in which services can migrate to different nodes in the network in order to maintain a semantically correct and continuous interaction with clients in highly volatile conditions. In this talk, I will also describe the implementation and evaluation of these middleware architectures on smart phones as well as several prototype applications implemented on top of them. I will conclude with a discussion on future research directions for people-centric mobile sensing applications.