NECO: Robust, Delay-Tolerant Sketches for Aggregating Sensor Data Streams

NECO：用于聚合传感器数据流的鲁棒、耐延迟草图

• 批准号: 0831903
• 负责人: Srikanta Tirthapura
• 金额: $ 22.83万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0831903&HistoricalAwards=false
• 关键词: NECO; Robust; Delay; Tolerant; Sketches

NeTS-NECO: Robust, Delay-Tolerant Sketches for AggregatingSensor Data StreamsEmerging data-intensive mobile sensor networking applications promisea close observation of the world around us at a relatively low dataacquisition cost. In these applications, it is a challenge toaggregate observation streams from distributed sources, due to thebandwidth and delay constraints of the network, and the energy costsof data transmission. This project develops techniques for processingvoluminous sensor data streams within the resource constraints imposedby a distributed infrastructure-less network.Techniques are designed to summarize the observation streams intosmall space "sketches". By disseminating sketches rather than the rawdata, it is possible to trade-off reduced communication cost forapproximate answers to user queries. The project investigates thetechnical challenge of making the sketches robust and suitable fortransmission over unreliable links. The sketches are delay-tolerant,i.e. they can tolerate long and variable network latencies. Variousclasses of queries are supported including: basic aggregates ofnumerical and categorical data, multi-dimensional temporal andgeographic aggregates, and time-decayed aggregates. The design ofsketches is informed and inspired by the recent rapid progress made inthe area of massive data stream processing. The project will result innew algorithms and data structures for sketching sensor data withprovable guarantees on the quality of answers. The research isexpected to benefit data-intensive sensor networking applications thatare critical to our society, such as earthquake, pollution, andtraffic monitoring.

NetS-NECO：用于聚合传感器数据流的鲁棒、延迟容忍的草图新兴的数据密集型移动的传感器网络应用承诺以相对较低的数据采集成本密切观察我们周围的世界。在这些应用中，由于网络带宽和时延的限制，以及数据传输的能量消耗，聚集来自分布式源的观测流是一个挑战。该项目开发了在分布式无基础设施网络的资源限制下处理大量传感器数据流的技术，并设计了将观测流总结成小空间“草图”的技术。通过传播草图而不是原始数据，可以权衡降低通信成本以获得用户查询的近似答案。该项目研究了使草图健壮并适合在不可靠的链路上传输的技术挑战。草图是延迟容忍的，即它们可以容忍长时间和可变的网络延迟。支持多种类型的查询，包括：数值和分类数据的基本聚合，多维时间和地理聚合，以及时间衰减聚合。草图的设计受到了最近在大规模数据流处理领域取得的快速进展的启发。该项目将产生新的算法和数据结构，用于绘制传感器数据，并对答案的质量提供可证明的保证。这项研究有望使对我们社会至关重要的数据密集型传感器网络应用受益，如地震，污染和交通监测。