Implementation of Evolutionary Algorithms for Improving Energy Consumption in Wireless Sensor Networks

Project Code :TMMACO79

Objective

The main objective of the project is to calculate the energy consumption using ABC, ACO and PSO optimization techniques.

Abstract

´Wireless Sensor Networks (WSNs) consists of a huge number of tiny, low-priced, and battery-powered devices with limited on board sensing, processing and communication capabilities. The batteries of sensor nodes of WSNs are usually with limited capacity; hence it is essential to conserve battery energy to prolonging the WSNs lifetime. Therefore, this paper deals with the matter of energy consumption minimization to maximize the overall network lifespan. In this research, a mathematical model for the lifetime of WSN is formulated based on several parameters to find out the optimal solution of the energy problem in the field of wireless sensor networks using the Particle Swarm Optimization (PSO),Ant Colony Optimization (ACO) and Artificial bee colony(ABC) algorithms. In this regards, ABC algorithm acts with much better efficiency as computational time minimizes, simple, has stable convergence characteristics than ACO and PSO algorithms.

´Index Terms: Wireless Sensor Network, Routing Algorithm, Ant Colony Optimization, Particle Swarm Optimization (PSO)

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 & Hardware Requirements:

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 Math Works products may take up to 29 GB of disk space

RAM:

Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

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
Basics of wireless sensor networks
About Leach protocols.
How system modal can be formed in Matlab.
Construction of algorithm according to system modal
Analyzing and visualization of plots.
About WSN lifetimes.
About cluster heads and aggregators.
About data transmission in-between nodes.
Phases of data transmission:

Generation of input data
Construction of WSN nodes

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

Demo Video

Request Video

Artificial Intelligence

Artificial Neural Network
Deep Learning

Image Processing

Image Enhancement
Image Detection
Image Compression
Fusion and Saliency
Image Retrieval
Image Denoising
Security Applications
Image Segmentation

Communications

Modulation Techniques
5G networks
MIMO Transmissions
Device-to-Device Communications

Wireless Sensor Networks

Routing Concepts
Protocols

Signal Processing

Security Applications
Denoising
Smoothing

Antenna

Patch Antenna