Hierarchical Low Power Consumption Technique with Location Information for Sensor Networks

Abstract

In the wireless sensor networks composed of battery-powered sensor nodes, one of the main issues is how to save power consumption at each node. The usual approach to this problem is to activate only necessary nodes (e.g., those nodes which compose a backbone network), and to put other nodes to sleep. One such algorithm using location information is GAF (Geographical Adaptive Fidelity), and the GAF is enhanced to HGAF (Hierarchical Geographical Adaptive Fidelity). In this paper, we show that we can further improve the energy efficiency of HGAF by modifying the manner of dividing sensor-field. We also provide a theoretical bound on this problem.

Authors and Affiliations

Susumu Matsumae, Fukuhito Ooshita

Keywords

Related Articles

Sample K-Means Clustering Method for Determining the Stage of Breast Cancer Malignancy Based on Cancer Size on Mammogram Image Basis

Breast cancer is a disease that arises due to the growth of breast tissue cells that are not normal. The detection of breast cancer malignancy level / stage relies heavily on the results of the analysis of the doctor. To...

Modeling of the Vegetable Oil Blends Composition

The article presents a computer modeling of blends of vegetable oils for treatment-and-prophylactic and healthy nutrition. To solve this problem, based on biomedical requirements, models of vegetable oil blends have been...

Risk Propagation Analysis and Visualization using Percolation Theory

This article presents a percolation-based approach for the analysis of risk propagation, using malware spreading as a showcase example. Conventional risk management is often driven by human (subjective) assessment of how...

Recognizing Human Actions by Local Space Time and LS-TSVM over CUDA

Local space-time features can be used to make the events adapted to the velocity of moving patterns, size of the object and the frequency in captured video. This paper purposed the new implementation approach of Human Ac...

Instant Human Face Attributes Recognition System 

The objective of this work is to provide a simple and yet efficient tool for human attributes like gender, age and ethnicity by the human facial image in the real time image as we all aware this term that “Real-Time fram...

Download PDF file
  • EP ID EP98566
  • DOI 10.14569/IJACSA.2013.040412
  • Views 101
  • Downloads 0

How To Cite

Susumu Matsumae, Fukuhito Ooshita (2013). Hierarchical Low Power Consumption Technique with Location Information for Sensor Networks. International Journal of Advanced Computer Science & Applications, 4(4), 69-74. https://europub.co.uk/articles/-A-98566