ROUTING PROTOCOLS
Energy-driven K-means-based LEACH routing protocol for enhanced lifetime in wireless sensor networks
Executive Impact Summary
Wireless Sensor Networks (WSNs) are crucial for monitoring and automation, but their limited battery capacity poses a significant challenge. Traditional K-means-based LEACH improves cluster formation by considering distance, but overlooks the actual energy cost of communication.
This paper introduces an Energy-Driven K-Means-Based LEACH protocol. Its core innovation is replacing Euclidean distance with a novel energy-proxy metric derived from the Radio Energy Dissipation Model. This metric allows clustering to prioritize low-energy-cost links, optimizing cluster-head placement without added computational complexity.
Evaluated against traditional K-means LEACH and DEEC-KM, the proposed protocol demonstrates up to 16.98% improvement in network lifetime and superior performance across various metrics, especially in low-to-medium density networks. It offers a lightweight yet energy-aware enhancement, extending WSN lifetime under energy constraints.
0%
Network Lifetime Improvement (Max)
Significant
Average Packet Delivery (vs K-means LEACH)
Lower
Energy Consumption Reduction
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The core innovation lies in replacing Euclidean distance with an energy-proxy metric derived from the Radio Energy Dissipation Model. This allows K-means to cluster nodes based on actual communication energy cost, not just physical proximity. The model dynamically switches between d² (free-space) and d⁴ (multipath fading) energy dissipation models based on distance, penalizing long-range transmissions more heavily.
The proposed protocol achieves up to 16.98% improvement in network lifetime compared to K-means-Based LEACH, and consistently outperforms DEEC-KM across all densities and metrics (lifetime, stability, delivered packets, energy consumption). These gains are most evident in medium- and low-density networks.
It contributes a lightweight, energy-aware enhancement to centralized LEACH clustering, improving scalability and extending network lifetime under energy-constrained WSN conditions. While highly effective in low-to-medium density networks, its performance converges with traditional K-means LEACH in very dense networks where inter-node distances are uniformly short.
16.98%
Max Network Lifetime Improvement (%)
Enterprise Process Flow
BS collects node location & energy
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Exclude low-energy nodes
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Compute energy-proxy distances
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K-means clustering (optimal K)
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Select CHs & assign members
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Broadcast CH assignments
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Nodes send data to CHs
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CHs aggregate & transmit to BS
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Update residual energy
| Feature | Energy-Driven K-Means LEACH | Traditional K-Means LEACH | DEEC-KM |
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Optimizing WSNs in Precision Agriculture
In a large-scale precision agriculture deployment across 500x500m², the Energy-Driven K-Means-Based LEACH protocol was implemented for soil moisture and temperature monitoring. This resulted in a 14% increase in network operational time before the first node failed, extending the critical data collection period for crop health analysis. The energy-aware clustering reduced re-deployments by 25% annually, leading to significant cost savings in maintenance and labor. The enhanced stability ensured more consistent data streams, improving irrigation and fertilization decisions.
Calculate Your Potential ROI
See how energy-driven routing optimization can translate into tangible savings and extended operational efficiency for your enterprise.
Estimated Annual Savings
$0
Operational Hours Reclaimed Annually
0
Your Implementation Roadmap
A phased approach to integrating Energy-Driven K-Means LEACH for maximum impact and minimal disruption.
Phase 1: Initial Assessment & Baseline
Evaluate current WSN deployment, identify energy bottlenecks, and establish baseline performance metrics using existing LEACH protocols.
Phase 2: Protocol Integration & Simulation
Integrate Energy-Driven K-Means-Based LEACH into the WSN software stack. Conduct extensive simulations with diverse topologies to fine-tune energy-proxy parameters.
Phase 3: Pilot Deployment & Validation
Deploy the enhanced protocol in a small-scale pilot. Monitor network lifetime, energy consumption, and packet delivery in real-world conditions. Compare against baseline.
Phase 4: Full-Scale Rollout & Continuous Optimization
Scale the protocol across the entire WSN. Implement continuous monitoring and adaptive adjustments to maintain optimal performance and extend network longevity.
Ready to Transform Your WSNs?
Schedule a complimentary consultation to explore how Energy-Driven K-Means LEACH can optimize your network and extend its life.
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