CSR: Small: Location, location, location (L3): Support for Geo-Centric Applications

Recent years have seen the proliferation of a variety of sensors embedded in different environments, and the increasing availability of smart wearable devices. Together these trends have resulted in the growth of sensor data of interest to many communities across social, economic, health-care, and scientific domains. This has led to the emergence of geo-centric applications: a class of applications that can process and extract rich information from the sensor data to provide novel services to users. However, these applications currently suffer from poor performance and failures due to the limited computing and storage resources available on the devices and their location dependency. This project will develop new computing abstractions, algorithms, and systems, that enable a new frontier of geo-centric applications to be supported. The goal of this project is to catalyze the role of computer systems in meeting the needs of emerging geo-centric applications in mobile, sensor, and Internet-of-things (IoT) areas.

This project will build a system called Location, location, location: Support for Geo-Centric Applications - or L3 for short. A number of novel system and application abstractions to manage the dynamism that arises from location in support of geo-centric applications will be developed. First is the concept of a Resource cloud, a system-facing abstraction that is geo-aware and manages a set of changing resources based on publish-subscribe and matchmaking. Second is the concept of a Resource container, an application-facing abstraction that provides policy-based resource selection and allocation across a diverse set of resources including storage, computation, and even data sources, to meet the specific requirements of an application. The project will address specific research problems that arise in the design and implementation of the Resource cloud and Resource container, including: on-demand resource provision to the Resource cloud, collective matching of resource requests that scale to diverse resource types and to highly shared resources, and automated resource policy generation and optimization based on application requirements.