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The human body maintains a precise pH range of arterial blood between 7.35 and 7.45. Deviations result in either acidosis (pH < 7.35) or alkalosis (pH > 7.45). These conditions are further classified as respiratory or metabolic disorders based on their underlying cause.
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Related Experiment Video

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Energy-Balanced Routing Algorithm Based on Ant Colony Optimization for Mobile Ad Hoc Networks.

Dong Yang1, Hongxing Xia2,3, Erfei Xu4

  • 1State Key Laboratory of Integrated Service Network, Xidian University, Xi'an 710071, China. dyang@mail.xidian.edu.cn.

Sensors (Basel, Switzerland)
|October 31, 2018
PubMed
Summary

This study introduces an improved routing algorithm for mobile ad hoc networks (MANETs) to reduce energy consumption and enhance network lifetime. The new method balances energy use and improves data transmission, especially with moving nodes.

Keywords:
energy constraint, ant colony optimization algorithm, convergence, remaining lifetime

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Area of Science:

  • Computer Science
  • Network Engineering
  • Wireless Communication

Background:

  • Mobile ad hoc networks (MANETs) face challenges with energy consumption and node mobility.
  • Existing routing algorithms like AOMDV and AntHocMMP have limitations in optimizing energy and handling dynamic network conditions.

Purpose of the Study:

  • To propose an improved energy and mobility ant colony optimization (IEMACO) routing algorithm for MANETs.
  • To address excessive energy consumption and prolong network lifetime in MANETs.

Main Methods:

  • Introduced an offset coefficient to accelerate convergence and reduce route discovery packets.
  • Incorporated remaining node lifetime (RLTn) and predicted link lifetime (RLTl) into pheromone generation.
  • Designed a pheromone generation method combining RLTn and RLTl for path selection.

Main Results:

  • The IEMACO algorithm reduces route discovery frequency and end-to-end delay.
  • It achieves lower packet loss rates, particularly under node mobility.
  • Simulation results demonstrate a balanced energy consumption across the network.

Conclusions:

  • IEMACO effectively balances energy consumption and improves routing efficiency in MANETs.
  • The algorithm enhances network lifetime and performance, especially in dynamic environments.
  • IEMACO outperforms AOMDV and AntHocMMP in terms of energy efficiency and delay.