Abstract
A sensor network is made up of numerous small independent sensor nodes with sensing, processing and communicating capabilities. The sensor nodes have limited battery and a minimal amount of on-board computing power. A self-adaptive methodology that utilizes the source and path redundancy techniques to efficiently reduce the required energy consumption is proposed. The proposed methodology presents a self-adaptive strategy to optimize the number of active sensor nodes and assign equal time slots to each sensor nodes for sensing and communication with the BS. The self-adaptive property enables the proposed methodology to perform a global search for optimizing the position of active sensor nodes with respect to the location of the base station (BS). The global search performed by the proposed methodology is carried out in a complete top down manner. The proposed self-adaptive methodology, therefore, not only reduces the energy consumption of wireless sensor nodes but also effectively maximizes the lifetime of active sensor nodes. Simulation results demonstrate that the proposed methodology significantly minimizes the energy consumption and consequently increases the life time of active sensor nodes.
| Original language | English (US) |
|---|---|
| Title of host publication | 2007 International Conference on Information and Emerging Technologies, ICIET |
| Pages | 71-77 |
| Number of pages | 7 |
| DOIs | |
| State | Published - 2007 |
| Event | 2007 International Conference on Information and Emerging Technologies, ICIET - Karachi, Pakistan Duration: Jul 6 2007 → Jul 7 2007 |
Publication series
| Name | 2007 International Conference on Information and Emerging Technologies, ICIET |
|---|
Other
| Other | 2007 International Conference on Information and Emerging Technologies, ICIET |
|---|---|
| Country/Territory | Pakistan |
| City | Karachi |
| Period | 7/6/07 → 7/7/07 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
- Electrical and Electronic Engineering
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