Title :
Study on Cost-Sensitive Communication Models on Large-scale Monitor Networks
Author :
Liu, Donghong ; Li, Aiping ; Tian, Li ; Jia, Yan ; Zou, Peng
Author_Institution :
Sch. of Comput., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
Large-scale distributed monitor networks are in face of the challenge of tremendous data communication costs due to the resource restriction. Prediction models can be used to reduce communication cost over the networks. A framework is proposed which provides a mechanism to maintain adaptive prediction models that significantly reduce communication cost over the distributed environment while still guaranteeing sufficient precision of demand results. Prediction models are also proposed to process prediction queries over future data streams in this paper. Three particular models, static model, linear model and acceleration model, and the corresponding tuning schemas are given. Experimentations are performed based on the simulated data and ocean air temperature data measured by TAO (tropical atmosphere ocean). Analytical and experimental evidence show that the proposed approach significantly reduces overall communication cost and performs well over prediction queries.
Keywords :
data communication; distributed processing; prediction theory; query processing; adaptive prediction models; cost sensitive communication model; data communication; data streams; distributed monitor networks; query processing; tropical atmosphere ocean; Adaptation model; Atmospheric modeling; Data models; Distributed databases; Monitoring; Predictive models; Temperature measurement; communication cost; data stream; large-scale monitor networks; prediction model; prediction query;
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
DOI :
10.1109/ICEE.2010.539