# Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm

## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Methodology

#### 3.1. Average Execution Time

#### 3.2. Makespan

#### 3.3. Delay Time

#### 3.4. Network Cost

#### 3.5. Virtual Machine Computing Cost

## 4. Improved Version of Seagull Optimization Algorithm

#### 4.1. Seagull Optimization Algorithm (SOA)

#### 4.2. Migration

- -
- The position of the swarms is adjusted depending on an extra parameter (A) to prevent collisions.

- (A)
- Knowledge of the surrounding neighbors: this section simulates the individual moving in the optimal direction based on the knowledge of the surrounding neighbors (good solution).

- (B)
- Proceeding to the best answer side (search agent): this is an update stage for enhancing the best candidates, as shown in:

#### 4.3. Attacking

#### 4.4. The Improved SOA

## 5. Simulation Results

^{®}Core™ i7 laptop, with 8 GB memory.

## 6. Conclusions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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Parameter | Value |
---|---|

$u$ | 1 |

$v$ | 0.002 |

Iteration number | 200 and 1000 |

population | 50 |

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**MDPI and ACS Style**

Al-Khafaji, H.M.R.
Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm. *Future Internet* **2022**, *14*, 281.
https://doi.org/10.3390/fi14100281

**AMA Style**

Al-Khafaji HMR.
Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm. *Future Internet*. 2022; 14(10):281.
https://doi.org/10.3390/fi14100281

**Chicago/Turabian Style**

Al-Khafaji, Hamza Mohammed Ridha.
2022. "Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm" *Future Internet* 14, no. 10: 281.
https://doi.org/10.3390/fi14100281