The mathematicians speed up the internet of things with fog

The Internet of Things (IoT) is at the center of many discussions. Mathematicians from RUDN University have proposed a new approach to optimize this network by using flying drones to process data. This proposal could accelerate the network and improve its reliability.

The Internet of Things (IoT) network aims to connect users’ devices with household and professional everyday devices. The current challenge is to find a balance between functionality and energy efficiency. To address this issue, mathematicians at RUDN University have proposed a new network architecture – the fog computing.

The IoT offers promising opportunities. But to deploy and manage such a network, several problems need to be solved. One of the main tasks is to ensure coverage and availability of the 5G/6G network. IoT devices are often limited in resources, especially in terms of power. Therefore, the balance between functionality and energy efficiency must be a delicate compromise. Especially for battery-powered devices or those installed in hard-to-reach places,” said Ammar Muthanna, PhD, Director of the Scientific Center for Modeling 5G Wireless Networks at RUDN University.

Flying fog computing: an innovative solution

The mathematicians have proposed to use flying fog computing. This is an intermediate solution between cloud computing, where all the main work is done in a distant center, and traditional computing on end devices.

In fog architectures, data storage and processing occur in an additional layer between the cloud data center and other network elements. The flying fog computing, proposed by the researchers at RUDN University, is implemented using drones. They move to where the data needs to be processed. As a result, network latency is reduced, and network reliability and speed are improved.

Comparison with the traditional network of the Internet of Things

Mathematicians from RUDN University compared the operation of fog computing on drones with a traditional Internet of Things network. The average latency in both cases depended on the number of network nodes but was always lower in the drone network.

For example, at 500 nodes, the latency was almost cut in half. At 100 nodes, the difference is barely noticeable, but it still favors flying fog computing.

Flying fog computing is a promising solution. We have shown its advantages over traditional schemes. The new data exchange model fully leverages the potential of such a network; it has surpassed traditional static edge computing – reducing average latency,” added Ammar Muthanna, PhD, Director of the Scientific Center for Modeling 5G Wireless Networks at RUDN University.

In summary

The proposal from the mathematicians of RUDN University to use flying fog computing to optimize the Internet of Things network represents a significant advancement. This solution could not only improve the speed and reliability of the network but also solve the challenge of balancing functionality and energy efficiency.

For a better understanding

What is the Internet of Things (IoT)?

The Internet of Things (IoT) is a network that connects users’ devices with household and professional everyday devices.

What is fog computing?

Fog computing is a network architecture that allows for data storage and processing in an additional layer between the cloud data center and other network elements.

What is flying fog computing?

Flying fog computing is a proposal by researchers at RUDN University that uses drones to move to where the data needs to be processed, thus reducing network latency.

What are the benefits of flying fog computing?

Flying fog computing could improve the speed and reliability of the Internet of Things network and help solve the challenge of balancing functionality and energy efficiency.

What are the next steps?

Further research is needed to assess the effectiveness of flying fog computing in real conditions.

References

Article: “Dynamic Offloading in Flying Fog Computing: Optimizing IoT Network Performance with Mobile Drones” – DOI: https://doi.org/10.3390/drones7100622

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