Minimizing Energy Consumption and Maximizing Network Lifetime in Wireless Sensor Networks
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Resource Overview
This paper presents an Energy-Efficient Data Gathering Algorithm (EEDGA) using mobile agent models to reduce energy consumption and extend network lifetime in wireless sensor networks. The algorithm first controls active node quantity based on monitoring precision requirements, then determines working nodes by computing minimum dominating sets, and finally employs ant colony optimization to plan optimal migration paths for mobile agents to progressively collect monitoring data. Simulation results demonstrate superior energy efficiency and extended network longevity compared to conventional approaches.
Detailed Documentation
In wireless sensor networks, we propose an Energy-Efficient Data Gathering Algorithm (EEDGA) to minimize energy consumption and maximize network lifetime. The algorithm implements data collection through mobile agent models. Initially, EEDGA controls the number of active nodes according to monitoring precision requirements using threshold-based activation mechanisms. Subsequently, working nodes are determined by solving minimum dominating set problems through greedy approximation algorithms. Finally, ant colony optimization is applied to plan optimal migration routes for mobile agents, enabling progressive data collection from active nodes with path optimization techniques. Simulation experiments confirm that compared to traditional algorithms, EEDGA achieves lower energy consumption and longer network lifetime through its hierarchical node management and intelligent routing strategies.
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