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Merge pull request #49 from CagataySonmez/develop

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docs/Relevant YouTube video links are added to the readme files.
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README.md
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@ -8,10 +8,14 @@ The discussion forum for EdgeCloudSim can be found [here](https://groups.google.
We hope to meet with all interested parties in this forum. We hope to meet with all interested parties in this forum.
Please feel free to join and let us discuss issues, share ideas related to EdgeCloudSim all together. Please feel free to join and let us discuss issues, share ideas related to EdgeCloudSim all together.
## YouTube Channel
The YouTube channel of EdgeCloudSim can be found [here](https://www.youtube.com/channel/UC2gnXTWHHN6h4bk1D5gpcIA).
You can find some videos presenting our works and tutorials on this channel.
Click [here](https://youtu.be/SmQgRANWUts) to watch the video with brief information about EdgeCloudSim.
## Needed Features ## Needed Features
* Mist computing features (executing tasks on mobile device)
* Incorporating cellular access network model into EdgeCloudSim (3G/4G/5G)
* Task migration among the Edge or Cloud VMs * Task migration among the Edge or Cloud VMs
* Energy consumption model for the mobile and edge devices as well as the cloud datacenters * Energy consumption model for the mobile and edge devices as well as the cloud datacenters
* Adding probabilistic network failure model by considering the congestion or other parameters such as the distance between mobile device and the WiFi access point. * Adding probabilistic network failure model by considering the congestion or other parameters such as the distance between mobile device and the WiFi access point.

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This application includes the source code which is used in our paper submitted to IEEE Transactions on Network and Service Management [[1]](https://ieeexplore.ieee.org/abstract/document/8651335/). This application includes the source code which is used in our paper submitted to IEEE Transactions on Network and Service Management [[1]](https://ieeexplore.ieee.org/abstract/document/8651335/).
You can find the presentation of this work on our YouTube channel. Click [here](https://youtu.be/RFP2M0w4NlY) to watch!
## Fuzzy Logic Based Workload Orchestrator ## Fuzzy Logic Based Workload Orchestrator
In this application we introduce a fuzzy logic based workload orchestrator. In our design, two stage fuzzy logic system is used as shown in Figure 1. In the first stage, the most convenient edge server in the edge layer is found. In the second stage, the candidate edge server and the cloud server are compared. As a result of these operations, the proposed fuzzy logic based workload orchestrator finds a target server which can be the local edge server, remote edge server or the cloud server. In this application we introduce a fuzzy logic based workload orchestrator. In our design, two stage fuzzy logic system is used as shown in Figure 1. In the first stage, the most convenient edge server in the edge layer is found. In the second stage, the candidate edge server and the cloud server are compared. As a result of these operations, the proposed fuzzy logic based workload orchestrator finds a target server which can be the local edge server, remote edge server or the cloud server.

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This application includes the source code which is used in our paper submitted to IEEE Transactions on Intelligent Transportation Systems [[1]](https://ieeexplore.ieee.org/abstract/document/9208723/). This application includes the source code which is used in our paper submitted to IEEE Transactions on Intelligent Transportation Systems [[1]](https://ieeexplore.ieee.org/abstract/document/9208723/).
You can find the presentation of this work on our YouTube channel. Click [here](https://youtu.be/mlcLDpDcdw8) to watch!
## Vehicular Edge Computing ## Vehicular Edge Computing
The concept of Internet of Vehicle (IoV), its pioneering applications, and the services for the future smart highways can benefit from the computation offloading concept over a multi-tier architecture consisting of the connected vehicles, road side units (RSUs), and cloud computing elements as shown in Figure 6.1. The vehicles are located in the first tier, which can be considered as the data generation layer. They also have computational resources which are provided by their on board units (OBUs). If required, some of the operations can be executed locally by the OBUs at this tier. The second tier consists of the RSUs that can provide fast access to limited resources. The edge servers are located in this tier. Finally, the third tier includes traditional cloud computing elements. The concept of Internet of Vehicle (IoV), its pioneering applications, and the services for the future smart highways can benefit from the computation offloading concept over a multi-tier architecture consisting of the connected vehicles, road side units (RSUs), and cloud computing elements as shown in Figure 6.1. The vehicles are located in the first tier, which can be considered as the data generation layer. They also have computational resources which are provided by their on board units (OBUs). If required, some of the operations can be executed locally by the OBUs at this tier. The second tier consists of the RSUs that can provide fast access to limited resources. The edge servers are located in this tier. Finally, the third tier includes traditional cloud computing elements.