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

近年来，各种传感器嵌入到不同的环境中，智能可穿戴设备的可用性也越来越高。这些趋势共同导致了社会、经济、卫生保健和科学领域许多社区感兴趣的传感器数据的增长。这导致了以地理为中心的应用程序的出现：一类可以从传感器数据中处理和提取丰富信息的应用程序，为用户提供新颖的服务。然而，由于设备上可用的计算和存储资源有限，以及它们对位置的依赖，这些应用程序目前受到性能差和故障的困扰。该项目将开发新的计算抽象、算法和系统，从而支持以地理为中心的应用程序的新前沿。该项目的目标是促进计算机系统在满足移动、传感器和物联网（IoT）领域新兴的以地理为中心的应用需求方面的作用。该项目将构建一个名为Location， Location， Location：支持以地理为中心的应用程序（简称L3）的系统。将开发许多新颖的系统和应用程序抽象来管理由位置产生的动态，以支持以地理为中心的应用程序。首先是资源云的概念，它是一种面向系统的抽象，具有地理感知能力，并基于发布-订阅和匹配管理一组不断变化的资源。第二个是资源容器的概念，这是一个面向应用程序的抽象，它提供基于策略的资源选择和分配，跨不同的资源集，包括存储、计算甚至数据源，以满足应用程序的特定需求。该项目将解决在资源云和资源容器的设计和实现中出现的具体研究问题，包括：按需向资源云提供资源，可扩展到不同资源类型和高度共享资源的资源请求的集体匹配，以及基于应用程序需求的自动化资源策略生成和优化。

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.