Toward IoT fog computing-enabled system energy consumption modeling and optimization by adaptive TCP/IP protocol

Area of Science:

• Computer Science
• Electrical Engineering
• Networking

Background:

• The proliferation of wireless technologies and delay-sensitive applications necessitates efficient resource management in the Fog of Internet of Things (IoT).
• Energy consumption in wireless IoT networks, particularly for data-intensive applications, is a significant challenge.
• Existing energy efficiency solutions often overlook the impact of the Transmission Control Protocol (TCP) and Maximum Transmission Unit (MTU) size.

Purpose of the Study:

• To investigate the relationship between MTU size and energy consumption in wireless Fog of IoT networks.
• To develop an effective model for reducing energy consumption in these networks.
• To provide insights for optimizing networking and computing resources for energy efficiency.

Main Methods:

• Measured actual energy consumption across different MTU sizes using real traffic data.
• Generalized the model to estimate network-wide energy consumption based on various network parameters.
• Conducted experiments on diverse devices utilizing multiple techniques.

Main Results:

• A clear inverse proportional relationship was observed between MTU size and energy consumption.
• Larger MTU sizes lead to reduced energy usage during data transmission.
• The findings demonstrate a quantifiable method for energy saving in wireless IoT.

Conclusions:

• Optimizing MTU size is a viable strategy for enhancing energy efficiency in Fog of IoT networks.
• The proposed model offers a practical approach to reduce energy consumption in delay-sensitive applications.
• These results can be integrated with existing methods to achieve optimal energy solutions for IoT and wireless networks.