Principal Component Analysis (PCA)

Decision Trees

K-Nearest Neighbors (KNN)

Linear Regression

To provide real-time monitoring of network traffic between cloud and fog nodes

To optimize the energy consumption of IoT devices in fog computing environments

To determine eligible QoS-, context-, and cost-aware multi-component application deployments to fog infrastructures

To simulate hardware failures in fog nodes for resilience testing

Enforcement of stringent security protocols

Reduction of computational workloads

Use of homogeneous data sources

Deployment of additional cloud resources

The processor is allowed to keep personal data after the end of the provision of services without deleting existing copies.

The processor is not required to assist the controller in ensuring compliance with the obligations under the GDPR.

The processor can apply another processor without any authorization from the controller.

The processor shall act only on instructions from the controller, especially where the transfer of personal data is prohibited.

Consent is valid regardless of the age of the child as long as it is given by the child themselves.

Consent is valid only if the child is at least 16 years old and has given their consent.

Consent is valid if the child is at least 14 years old and has given their consent.

Consent is not required for processing the personal data of children under any circumstances.

Excessive reliance on human experience

Lack of historical data for analysis

Difficulty in handling diverse protocols and data formats in the fog layer

Inability to process real-time data in the cloud

Functionality testing

Enterprise workflow testing

Reliability testing

Energy efficiency testing

Correlated data fusion framework

Disparate data fusion framework

Inconsistent data fusion framework

Imperfect data fusion framework

To allocate hardware resources across fog nodes in real-time

To dynamically simulate changes in network conditions and estimate QoS-assurance for eligible deployments

To optimize the cost of deploying applications by selecting the cheapest VM types

To encrypt and decrypt data during application deployment

Lack of functionality; improve user interface design

Cybersecurity vulnerabilities; establish test beds with cybersecurity measures

High cost; develop cost-effective technologies

Poor energy efficiency; implement advanced energy-saving algorithms