CCF: Fundamental Algorithms for Data Management

数据管理的基本算法我们正处于一个数据（娱乐、媒体）有望按需提供的时代，而不是主要通过电视等广播方式。存储技术将需要以高质量的服务来科普极高的需求。存储大量数据并使其可供大量用户访问将是一个挑战。本研究的重点是开发用于管理大规模存储系统中的数据的基本算法。这项研究的重点是所有类型的数据，从存储在磁盘集合上的多媒体数据，以及正在收集和存储在分布式传感器网络中的数据。这项研究解决了如何开发算法来有效和高效地管理这些数据的问题。本项目将培训一名研究生，并开发一门关于数据管理方法的课程。本研究开发了管理数据的工具和方法，特别关注数据布局和数据迁移。数据布局为存储系统指定需要多少副本来科普需求，这个问题是NP-难的，我们的目标是开发快速实用的近似算法。数据迁移的目标是集中在重新部署的问题上，当需求模式随时间变化时，组织布局。我们还考虑了传感器网络中数据收集和监控的能量问题。

Fundamental Algorithms for Data ManagementWe are in an era where data (entertainment, media) is expected to be available on demand, and not primarily through broadcast methods such as TV. Storage technologies will need to cope with extremely high demand, with high quality of service. Storing large amounts of data and making it accessible to a very large number of users will be a challenge. The focus of this research is to develop fundamental algorithms for managing data in large scale storage systems. This research focuses on data of all types, ranging from multimedia data stored on a collection of disks, as well as data that is being collected and stored in a distributed sensor network. This research addresses the question of how to develop algorithms to manage this data effectively and efficiently. This project will involve training of a graduate student, and the development of a course on data management methods.This research develops tools and methods for managing data, with a special focus on data layout and data migration. The data layout specifies for a storage system, how many replicas are required to cope with the demand, and which servers they should reside on.This problem is NP-hard and our goal is to develop fast and practical approximation algorithms for it.The goal of data migration is to focus on the problem of re-organizing the layout when the demand pattern changes over time.We also consider energy issues in data collection and monitoring in sensor networks.