Dongdong Ren
Papers
2
Total Citations
8
H-Index
2
About
Dongdong Ren is a researcher focused on advancing energy efficiency in the Internet of Things (IoT), with a particular emphasis on mobile edge computing and data service optimization. His work addresses critical challenges in sensory data gathering, where he has pioneered methods to minimize energy consumption while maintaining robust network performance. Ren’s most cited paper, "Energy-efficient sensory data gathering in IoT networks with mobile edge computing" (2021, 5 citations), introduces novel frameworks that leverage edge computing to reduce the power demands of data collection in large-scale IoT deployments. Building on this, his 2022 study "DaaS: Towards Energy-Efficient Data Collection Optimization for Data as a Service in IoT networks" (3 citations) extends these principles by treating sensory data as a service (DaaS), optimizing collection strategies for smart devices, including social robots. Though his citation counts are still growing, Ren’s contributions are foundational for sustainable IoT architectures, directly impacting the design of energy-aware systems in smart cities and robotics. His work stands out for its practical focus on integrating data-as-a-service models with edge computing, offering a blueprint for future research in green IoT and mobile edge networks.
Research Focus
Key Achievements
Top Papers
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