Tuesday 18 February 2025
The rapid growth of Internet of Things (IoT) applications is putting a strain on computing resources and network bandwidth. To address this, service providers are turning to edge-cloud computing, which can improve the quality of their services by processing data closer to where it’s generated.
However, deploying IoT applications in an efficient way remains a challenge. A team of researchers has developed a new approach that breaks down IoT applications into smaller, more manageable parts called nanoservices. Each nanoservice is designed to perform a specific task and can be deployed on local computing nodes, edge nodes or cloud nodes depending on its requirements.
The team’s system uses a concept called semantic slicing, which involves dividing the network infrastructure into virtual networks that can be customized for different applications. This allows IoT applications to be deployed in an energy-efficient way, with tasks being allocated to the most suitable node based on factors such as energy consumption profiles and timing constraints.
For example, if a task requires real-time processing but doesn’t need high bandwidth, it could be deployed on a local computing node that has low power consumption. If the task requires high bandwidth, it could be deployed on an edge node with maximum available GPUs. The system can even use energy forecasting to delay deployment of tasks during periods of high energy prices.
The team’s approach has been tested in simulated and real-world scenarios, and the results show that it can significantly reduce energy consumption while meeting performance requirements. This is particularly important for IoT applications that are often deployed in remote or resource-constrained areas where energy efficiency is critical.
The system also uses a technique called network slicing to divide the network infrastructure into virtual networks that can be customized for different applications. This allows IoT applications to be deployed in an efficient way, with tasks being allocated to the most suitable node based on factors such as bandwidth and latency requirements.
Overall, the team’s approach has the potential to revolutionize the way IoT applications are deployed, making them more energy-efficient, scalable and customizable. As the Internet of Things continues to grow, this technology could play a crucial role in ensuring that these applications can be deployed efficiently and effectively.
Cite this article: “Edge-Cloud Computing: A New Approach to Efficiently Deploying IoT Applications”, The Science Archive, 2025.
Edge-Cloud Computing, Iot, Nanoservices, Semantic Slicing, Network Slicing, Energy Efficiency, Computing Resources, Bandwidth, Internet Of Things, Performance Requirements
