Work

An Efficient Data Aggregation Scheme Leveraging Time Series Prediction in Wireless Sensor Networks

Year: 2011

Type: article

Abstract: In wireless sensor networks, the data periodically sensed by sensor nodes are usually of high temporal correlation.Therefore, prediction based data aggregation scheme can be designed to reduce the amount of data transmission and save sensor nodes' limited energy and bandwidth.We proposed a temporal correlation based data aggregation scheme in this paper which utilizes time series model to predict the data of next several periods at both ordinary sensors and aggregators based on the same amount of recent sensed values.We show through experiments using real sensor data that our proposed scheme can provide considerable aggregation ratio while maintaining a low prediction error rate.

Source: International Journal of Machine Learning and Computing

DOI: 10.7763/ijmlc.2011.v1.55

Authors: Guorui Li, Ying Wang

Institutions: Yanshan University, Northeastern University

Language: English

Topic: Energy Efficient Wireless Sensor Networks

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: National Oceanic and Atmospheric Administration, Fundamental Research Funds for the Central Universities

OpenAlex ID: W2037366270