Optimizing Routing with ACO and Energy Efficient Localizing with EE LEACH Algorithm
Objective
Optimize network routing using the Ant Colony Optimization (ACO) algorithm to enhance path selection efficiency. Improve energy-efficient localization by implementing the EE-LEACH algorithm to extend network lifespan. Integrate both techniques to achieve balanced energy consumption and reliable data transmission in wireless sensor networks.
Abstract
Energy-aware localization and effective routing are essential for improving the lifetime and performance of wireless sensor networks (WSNs). In order to enhance data transmission and lower energy usage, this work proposes an optimized routing strategy that combines the Energy-Efficient LEACH (EE-LEACH) algorithm with Ant Colony Optimization (ACO). ACO ensures effective data routing with low energy consumption by dynamically choosing the best routes based on pheromone updates and heuristic information, which is inspired by the foraging behavior of ants. In the meantime, EE-LEACH improves cluster-based communication through network longevity extension, energy balance among nodes, and cluster head selection optimization. Through the integration of EE-LEACH for energy-efficient localization and ACO for routing, the suggested method achieves increased scalability, decreased overhead, and a longer WSN lifespan. According to simulation results, this hybrid approach performs better than conventional LEACH and AODV-based routing systems in terms of network longevity, energy efficiency, and packet delivery, making it a viable option for sensor networks with limited resources.
Keywords: Wireless Sensor Network, LEACH Algorithm, EE-LEACH Algorithm, Ant Colony Optimization (ACO).
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 R2022b
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
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
· What is Communication?
· About Communication
· Introduction to Communication
· How Communication Works?
· Importing the System Design, Characterization and Visualization
· Analyzing of BER tool
· Analyzing of Error Rate Test Console
· Generation of WSN
· WSN network creation
· Nodes Communication
· Clustering
· Routing
· Convolutional
· Equalization and Synchronization etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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