Energy and Delay Aware Data Aggregation in Routing Protocol for Internet of Things

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Energy conservation is a critical challenge in Internet of Things (IoT) networks.
• The standard IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) can lead to increased data traffic and frequent path changes in dense networks.

Purpose of the Study:

• To propose an enhanced routing protocol, EDADA-RPL, for IoT networks to address energy conservation and data traffic issues.
• To improve network lifetime, reduce data transmission delay, and enhance packet delivery ratio in IoT environments.

Main Methods:

• The proposed Energy and Delay Aware Data aggregation in Routing Protocol (EDADA-RPL) features two main processes: parent selection and data aggregation.
• Parent selection utilizes the residual energy (RER) metric for optimal parent node choice.
• Data aggregation employs compressed sensing (CS) theory in parent nodes to combine child node data packets before transmission to the sink.

Main Results:

• Simulations conducted using the Contiki COOJA simulator demonstrate EDADA-RPL's effectiveness.
• Performance comparisons with standard RPL and LA-RPL show EDADA-RPL offers superior results.
• Key performance improvements were observed in network lifetime, reduced delay, and increased packet delivery ratio.

Conclusions:

• EDADA-RPL effectively conserves energy and manages data traffic in IoT networks.
• The protocol's approach to parent selection and data aggregation significantly enhances overall network efficiency.
• EDADA-RPL presents a promising solution for optimizing performance in resource-constrained IoT environments.