Wireless Sensor Network Clustering and Routing for Energy Hole Mitigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless sensor networks face energy depletion issues due to uneven energy consumption, particularly near the base station, leading to the 'energy hole' problem, where cluster heads responsible for data forwarding consume energy rapidly, reducing network lifetime.
Innovation Solution
A clustering and routing method that constructs minimum-energy-consumption path trees (MECPT) and iteratively selects cluster heads and updates trees to balance energy consumption, using competition coefficients to determine cluster head selection and communication paths, ensuring nodes near the base station consume energy more evenly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data fusion by cluster heads is used to reduce transmitted data amount, then network energy consumption is reduced, but cluster heads die early due to excessive energy consumption
Solution Approach 1:
The patent divides the network into multiple batches of cluster selections. In each batch, only certain nodes are selected as cluster heads based on competition coefficients, rather than having all nodes compete equally. This segmentation of the cluster head selection process distributes the energy consumption burden more evenly across different time periods and nodes.
Solution Approach 2:
The patent performs preliminary calculation of competition coefficients for all nodes before actual cluster head selection. This preliminary action identifies which nodes have the capacity to become cluster heads without depleting their energy reserves, allowing the system to pre-determine safe cluster head candidates that will not die early.
2Use of energy by moving object
If multi-hop communication between cluster heads and base station is adopted to reduce long-distance transmission, then cluster head energy consumption is reduced, but nodes close to base station consume energy too fast causing energy hole
Solution Approach 1:
The patent applies different selection criteria for cluster heads at different locations. Nodes closer to the base station are given different competition coefficient calculations compared to distant nodes, taking into account their proximity to the base station. This local quality adjustment prevents nearby nodes from being over-selected as cluster heads, thereby avoiding the energy hole problem.
Solution Approach 2:
The patent uses competition coefficients as a feedback mechanism that dynamically adjusts cluster head selection based on current network state. The competition coefficient calculation incorporates information about node location, remaining energy, and current cluster head status, providing feedback that prevents over-exploitation of nodes near the base station.
3Loss of energy
If iterative cluster head selection and MECPT updating is performed to balance energy consumption, then energy distribution is improved, but calculation complexity increases
Solution Approach 1:
The patent performs a limited number of iterative batches (first batch, second batch, etc.) rather than continuous iteration. After a predetermined number of batches or when convergence criteria are met, the process stops. This partial action achieves sufficient energy balancing without the excessive computational burden of unlimited iteration.
Solution Approach 2:
The patent pre-calculates competition coefficients for all nodes before each batch of cluster head selection. This preliminary calculation organizes the data in advance, reducing the computational complexity during the actual selection process. By preparing the competition coefficients beforehand, the iterative process becomes more efficient.
Data Source
AI summary
Disclosed are a clustering and routing method and system for a wireless sensor network. The method includes: constructing an initial MECPT; constructing cluster trees and updating MECPT; calculating clustering competition coefficients of existing cluster heads relative to nodes other than a base station; determining whether the clustering competition coefficients are all −∞; if yes, enabling non-clustered nodes to communicate with the base station following paths in the initial MECPT, and selecting child nodes of the base station in the initial MECPT as relay nodes; calculating weights about energy consumption of communication between the cluster heads and the relay nodes to get communication paths between nodes and the base station; or if no, clustering nodes based on the clustering competition coefficients, and updating the MECPT and cluster trees to which the nodes are added by an iteration process.