Power Efficient VNF Placement Strategy for Next Generation Wireless Mesh Networks
DOI:
https://doi.org/10.15662/IJEETR.2026.0802031Keywords:
Virtual Network Functions (VNFs), EAVPWMN (Energy Aware VNF Placement Protocol for Wireless Mesh Networks), Traffic Demand AnalysisAbstract
Next generation wireless mesh networks are expected to support high data rates, low latency, and massive connectivity while operating under strict energy constraints. Virtual Network Functions (VNFs) enable network services to be deployed flexibly using virtualization instead of dedicated hardware. However, improper placement of VNFs in wireless mesh environments can lead to excessive power consumption and reduced network performance.
This project proposes a power efficient VNF placement strategy that intelligently assigns VNFs to mesh nodes based on energy usage, node capacity, and traffic demand. The strategy minimizes overall power consumption while maintaining service quality. By leveraging resource aware decision making, the proposed system improves energy efficiency and network scalability. Simulation results demonstrate reduced power usage and improved utilization of network resources.
The approach is suitable for future wireless mesh networks supporting 5G and beyond applications. The proposed model ensures optimal VNF placement under dynamic traffic conditions. This system contributes toward sustainable and green networking solution. This research proposes an advanced energy-aware VNF placement strategy that optimizes the allocation of VNFs across mesh nodes by considering multiple parameters such as node energy levels, computational capacity, traffic demand, and link quality.
Unlike traditional approaches, the proposed model integrates dynamic traffic prediction and adaptive decision-making to handle real-time network variations. A novel energy cost function is introduced to minimize both processing and communication energy overhead. Additionally, the system incorporates load balancing and fault tolerance mechanisms to enhance network reliability and prevent node failures.
Simulation results demonstrate significant improvements in energy efficiency, reduced latency, and better resource utilization compared to existing methods. The proposed framework also supports scalability and adaptability for emerging technologies such as 5G, Internet of Things (IoT), and smart city applications
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