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A Novel Scheme for Controller Selection in Software-Defined Internet-of-Things (SD-IoT).

Jehad Ali^1,2, Byeong-Hee Roh^1,2

¹Department of Computer Engineering, Ajou University, Suwon 16499, Korea.

Sensors (Basel, Switzerland)

|May 20, 2022

Summary

Selecting the optimal controller is crucial for Software-Defined Internet of Things (SD-IoT) performance. An Analytical Network Decision Making Process (ANDP) effectively identifies the best SD-IoT controllers based on features and performance, reducing network delay and improving efficiency.

Keywords:

ANDP OpenFlow SDN controller performance evaluation

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Area of Science:

Computer Science
Network Engineering

Background:

Software-Defined Networking (SDN) decouples network control and data planes, enabling programmability and central management.
Software-Defined Internet of Things (SD-IoT) leverages SDN for enhanced IoT network capabilities.
Controller selection in SD-IoT is critical due to performance degradation and increased flow requests impacting scalability.

Purpose of the Study:

To address the unstudied problem of controller selection in SD-IoT.
To propose and evaluate an Analytical Network Decision Making Process (ANDP)-based technique for optimal SD-IoT controller selection.
To validate the feature-based controller selection strategy in a simulated SD-IoT environment.

Main Methods:

Employed an Analytical Network Decision Making Process (ANDP) for multi-criteria controller selection.
Developed a feature-based controller selection strategy prioritizing features before performance.
Conducted experimental analysis to quantify controller performance and validate the proposed method.

Main Results:

The ANDP-based feature-based selection strategy successfully identified high-weight controllers.
The proposed controller selection method demonstrated superior performance compared to previous schemes.
Optimal controller selection reduced network delay under normal and heavy traffic conditions.

Conclusions:

The ANDP is an effective method for SD-IoT controller selection based on features and performance.
The proposed strategy enhances SD-IoT network throughput and CPU utilization.
Efficient controller selection minimizes network recovery latency during failures.