Home > Publications
Home University of Twente
Prospective Students
Intranet (internal)

EEMCS EPrints Service

9354 A Distributed and Self-Organizing Scheduling Algorithm for Energy-Efficient Data Aggregation in Wireless Sensor Networks
Home Policy Brochure Browse Search User Area Contact Help

Chatterjea, S. and Nieberg, T. and Meratnia, N. and Havinga, P.J.M. (2007) A Distributed and Self-Organizing Scheduling Algorithm for Energy-Efficient Data Aggregation in Wireless Sensor Networks. Technical Report TR-CTIT-07-10, Centre for Telematics and Information Technology University of Twente, Enschede. ISSN 1381-3625

Full text available as:


978 Kb
Open Access

Exported to Metis


Wireless sensor networks (WSNs) are increasingly being used to monitor various parameters in a wide range of environmental monitoring applications. In many instances, environmental scientists are interested in collecting raw data using long-running queries injected into a WSN for analyzing at a later stage rather than injecting snap-shot queries into the network that contain data-reducing operators (e.g. MIN, MAX, AVG) that aggregate data. Collection of raw data poses a challenge to WSNs as very large amounts of data need to be transported through the network. This not only leads to high levels of energy consumption and thus diminished network lifetime but also results in poor data quality as much of the data may be lost due to the limited bandwidth of present-day sensor nodes. We alleviate this problem by allowing certain nodes in the network to aggregate data by taking advantage of spatial and temporal correlations of various physical parameters and thus eliminating the transmission of redundant data. In this paper we present a distributed scheduling algorithm that decides when a particular node should perform this novel type of aggregation. The scheduling algorithm autonomously reassigns schedules when changes in network topology due to failing or newly added nodes, are detected. Such changes in topology are detected using cross-layer information from the underlying MAC layer. We present theoretical performance bounds of our algorithm and include simulation results which indicate energy savings of up to 80\% when compared to collecting raw data.

Item Type:Internal Report (Technical Report)
Research Group:EWI-CAES: Computer Architecture for Embedded Systems, EWI-DMMP: Discrete Mathematics and Mathematical Programming
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:Consensus: Collaborative Sensor Networks, e-SENSE: Capturing Ambient Intelligence for Mobile Communications through Wireless Sensor Networks
ID Code:9354
Deposited On:20 September 2007
More Information:statisticsmetis

Export this item as:

To correct this item please ask your editor

Repository Staff Only: edit this item