Programming Support for Data Intensive Distributed Mobile Applications at the Edge

Mobile, IoT, and wearable devices have been transitioning from passive consumers of remote data to active generators of massive amounts of data. Mobile apps often need to move data, generated on one device, to other nearby devices for processing. For example, when reading its wearer's health vitals, a health monitoring app on a wearable device needs to transfer the data to the wearer's smartphone for display and analysis. This local processing of data by means of nearby computing resources has been promoted as a solution to network bandwidth bottlenecks, and commonly referred to as edge computing. Despite the critical dependence of edge computing on the device-to-device data sharing functionality, its mainstream implementations introduce low-level and hard-to-maintain code into the mobile codebase. To address this problem, this research introduces Remote ICC (RICCi), a novel middleware framework that provides programming support for data-intensive mobile applications at the edge, thereby reconciling programming convenience and performance efficiency. RICCi builds upon the native Android Inter-Component Communication (ICC) to simultaneously support seamless and efficient inter-device data sharing via a convenient and familiar programming model. To reach these design objectives, RICCi innovates in the middleware space by offering distributed programming abstractions that are data-oriented rather than procedure-oriented, thereby elevating latency into a first-class design concern for developing distributed mobile apps.