Abstract
This paper presented two methods of correlated data gathering on sensor networks, LOMFC and LOMSC, based on two types of correlation model, Foreign-Coding and Self-Coding. The goal of the methods is to maximize the lifetime of the network. They perform a series of adjustments over a built data gathering topology and improved the lifetime of the network. The methods in this paper overcame the energy consumption imbalance of some previous methods of correlated data gathering and are highly distributed. The stimulations proved that the two methods outperform previous algorithms in lifetime and are always reliable.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - SNPD 2007 |
| Subtitle of host publication | Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing |
| Pages | 3-8 |
| Number of pages | 6 |
| DOIs | |
| State | Published - 2007 |
| Externally published | Yes |
| Event | SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Qingdao, China Duration: 30 Jul 2007 → 1 Aug 2007 |
Publication series
| Name | Proceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing |
|---|---|
| Volume | 2 |
Conference
| Conference | SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing |
|---|---|
| Country/Territory | China |
| City | Qingdao |
| Period | 30/07/07 → 1/08/07 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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