Most Efficient Sensor Network Protocol for a Permanent Natural Disaster Monitoring System

Changmin Lee, Seong Lyun Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

To minimize enormous havoc from disasters, permanent environment monitoring is necessarily required. Thus, we propose a novel energy management protocol for energy harvesting wireless sensor networks, named the adaptive sensor node management protocol (ASMP). The proposed protocol makes system components to systematically control their performance to conserve the energy. Through this protocol, sensor nodes autonomously activate an additional energy conservation algorithm. ASMP embeds three sampling algorithms. For the optimized environment sampling, we proposed the adaptive sampling algorithm for monitoring (ASA-m). ASA-m estimates the expected time period to occur meaningful change. The meaningful change refers to the distance between two target data for the monitoring Quality of Service. Therefore, ASA-m merely gathers the data the system demands. The continuous adaptive sampling algorithm (CASA) solves the problem to be continuously decreasing energy despite of ASA-m. When the monitored environment shows a linear trend property, the sensor node in CASA rests a sampling process, and the server generates predicted data at the estimated time slot. For guaranteeing the self-sustainability, ASMP uses the recoverable adaptive sampling algorithm (RASA). RASA makes consumed energy smaller than harvested energy by utilizing the predicted data. RASA recharges the energy of the sensor node. Through this method, ASMP achieves both energy conservation and service quality.

Original languageEnglish
Article number9378785
Pages (from-to)11776-11792
Number of pages17
JournalIEEE Internet of Things Journal
Volume8
Issue number15
DOIs
Publication statusPublished - 2021 Aug 1

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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