Optimization of Wireless Sensor Networks Using the ANT COLONY OPTIMIZATION

Project Code :TMMAWS14

Objective

Ant colony Optimization finds the optimal path with the least average energy consumption and prolong the survival time of the Wireless sensor network.

Abstract

This paper proposes an ant colony optimization-based routing algorithm for wireless sensor networks. The algorithm incorporates link quality into pheromone formation and supports multiple routes, which are characteristics of an ant colony algorithm. When routing is chosen, the probability of the node being chosen as the next hop is calculated based on the pheromone concentration on the route. Because ant colony optimization is self-organizing, dynamic, and multi-path, it is ideal for wireless sensor network routing. This algorithm has a low routing cost, good self-adaptation, and can handle multiple paths. It has the ability to balance the network's energy consumption and extend the network's survival time. The thesis performs a comparative analysis of the simulation experiment and experimental results, demonstrating that the ant colony algorithm can find the optimal routing in a wireless sensor network and achieves the design goal of a wireless sensor network routing algorithm.

Keywords: Wireless Sensor Network, Routing Algorithm, Ant Colony Optimization

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Software: Matlab 2018a or above

Hardware:

Operating Systems:

  • Windows 10
  • Windows 7 Service Pack 1
  • Windows Server 2019
  • Windows Server 2016

Processors:

Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support

Disk:

Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space

RAM:

Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

  • Introduction to Matlab
  • What is EISPACK & LINPACK
  • How to start with MATLAB
  • About Matlab language
  • Matlab coding skills
  • About tools & libraries
  • Application Program Interface in Matlab
  • About Matlab desktop
  • How to use Matlab editor to create M-Files
  • Features of Matlab
  • Basics on Matlab
  • How detect & send a mail using Matlab
  • How to extend our work to another real time applications
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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