Node Selection in Multihop Wireless Sensor Networks
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Solution Overview
Problem
Multihop wireless sensor networks face challenges in energy-efficient node selection due to uneven energy distribution, potential node sleep cycles, unreliable wireless links, and network partition, leading to packet loss and increased retransmissions.
Innovation Solution
A method for node selection in multihop wireless sensor networks that determines leftover energy and secure values for neighboring nodes, generating candidate sets based on energy and security thresholds, and prioritizing nodes for data transmission based on forward and reverse delivery ratios to ensure reliable and efficient data packet delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If routing protocols determine shortest energy path in multihop wireless sensor network, then energy consumption is optimized, but uneven energy distribution occurs among nodes
Solution Approach 1:
The patent changes the selection parameter from purely energy-based to a composite metric incorporating both residual energy and secure value (trustworthiness). This dual-parameter approach balances energy distribution while ensuring reliable node selection, preventing both energy depletion and security vulnerabilities.
Solution Approach 2:
The patent implements dynamic node selection where the candidate set is continuously updated based on current residual energy levels and secure values. Nodes can enter or exit the candidate set dynamically, allowing the system to adapt to changing energy conditions and maintain balanced energy distribution across the network.
2Use of energy by moving object
If nodes enter sleep cycle to conserve energy, then energy consumption is reduced, but considerable overhead is required for node selection
Solution Approach 1:
The patent performs preliminary evaluation of neighboring nodes by determining their residual energy and secure values before they are needed for data transmission. This advance preparation creates a pre-sorted candidate set, reducing the overhead required at the moment of node selection and minimizing wake-up frequency for sleeping nodes.
Solution Approach 2:
Each node independently determines its own residual energy and evaluates neighboring nodes' secure values through local computations and exchanges. This self-service approach minimizes centralized coordination overhead and allows nodes to autonomously manage their sleep-wake cycles based on their own energy status.
3Reliability
If multiple retransmissions are performed for packet loss due to unreliable wireless links, then data delivery reliability is improved, but energy consumption increases
Solution Approach 1:
The patent incorporates feedback mechanisms through secure value calculation that considers forward delivery ratio and reverse delivery ratio. Nodes with poor delivery performance receive lower secure values, causing them to be excluded from candidate sets. This feedback loop prevents energy-wasting retransmissions through unreliable nodes while maintaining high delivery reliability through trusted nodes.
Solution Approach 2:
The patent extracts unreliable nodes from the candidate set by evaluating their secure values based on delivery ratios. By removing nodes with poor transmission reliability from consideration, the system avoids the energy consumption associated with multiple retransmissions while maintaining data delivery reliability through selection of trustworthy nodes.
4Use of energy by moving object
If node selection is based solely on residual energy, then energy efficiency is improved, but security vulnerabilities increase due to potentially malicious nodes
Solution Approach 1:
The patent introduces asymmetry by evaluating nodes on two different dimensions: residual energy (resource availability) and secure value (trustworthiness). This asymmetric dual-criteria approach ensures that neither energy-rich but malicious nodes nor energy-poor but trustworthy nodes can compromise the system, balancing energy efficiency with security.
Solution Approach 2:
The secure value acts as an intermediary metric that mediates between energy considerations and security requirements. By introducing this intermediate evaluation layer based on delivery ratios, the system can objectively assess node trustworthiness and make balanced decisions that satisfy both energy efficiency and security requirements without direct conflict.
Data Source
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AI summary
A method and system for node selection in a multihop wireless sensor network is disclosed. The method includes: determining, at a source node, a leftover energy associated with each neighboring node of the source node and determining a secure value associated with each neighboring node of the source node. A potential candidate set is generated, which includes one or more nodes for which leftover energy is greater than an energy threshold. Thereafter, an actual candidate set is generated from the potential candidate, such that, secure value of each node in the actual candidate set is greater than a secure value threshold. Further, the actual candidate set is sorted based on a priority value determined based on the secure value. Finally, a node with the highest priority value in the actual candidate set is selected for receiving a data packet from the source node.