Adaptive algorithm for energy consumption in Internet of Things networks
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This project proposed the design and implementation of an adaptive algorithm to optimize energy consumption in Internet of Things (IoT) networks using the RPL routing protocol. The research addressed the need to improve the efficiency of IoT devices powered by limited batteries, especially in contexts with limited electrical infrastructure, such as the Mocache canton in Ecuador. By integrating metrics such as residual energy, link quality (ETX), and signal strength (RSSI), the algorithm enabled dynamic adjustment of transmission power and the selection of more efficient routes, reducing energy loss without compromising service quality. The methodology was based on controlled simulations in Cooja/Contiki-OS, using a domestic scenario with three nodes (coordinator, sensor, and actuator), running two treatments: standard RPL and the modified RPL with the proposed algorithm. The results demonstrated a 22% reduction in average energy consumption (from 35 mJ to 27 mJ per node), an increase in PDR from 94.5% to 95.2%, and a decrease in parent changes, evidencing greater DODAG stability. The proposal achieves efficiency comparable to previous works while maintaining low computational overhead, operating on microcontrollers with limited resources. It is concluded that the adaptive algorithm represents a viable solution for domestic and rural IoT networks with energy constraints, providing a balance between energy savings and implementation simplicity.
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