Enhancing energy balance in wireless sensor networks through optimized minimum spanning tree

Area of Science:

• Computer Science
• Network Engineering
• Algorithm Design

Background:

• Wireless sensor networks (WSNs) face significant challenges due to limited energy resources in sensor nodes.
• Energy imbalances lead to premature node failures and reduced overall network lifespan, hindering applications like environmental monitoring and industrial automation.
• Existing solutions struggle to address WSN energy imbalances effectively due to network dynamics and uneven node distribution.

Purpose of the Study:

• To propose a novel method for enhancing energy balance in WSNs using Prim's algorithm.
• To improve the longevity and energy efficiency of wireless sensor networks.
• To optimize the deployment and operation of WSNs for sustainable applications.

Main Methods:

• Utilizing Prim's algorithm to construct Minimum Spanning Trees (MSTs) for optimal node connectivity.
• Implementing network initialization and energy consumption modeling.
• Optimizing the movement of mobile sink nodes within the WSN.

Main Results:

• Demonstrated significant improvement in energy equilibrium across WSN nodes.
• Showcased the effectiveness of Prim's algorithm in minimizing energy consumption.
• Experimental results indicate high sensitivity and moderate complexity of the proposed approach.

Conclusions:

• Prim's algorithm offers a viable solution for enhancing energy balance in WSNs.
• The proposed method effectively extends the operational lifespan of wireless sensor networks.
• This research contributes to more sustainable and efficient WSN deployments through improved energy management.