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A docker-based and Kubernetes-ready synthetic service mesh - Generating CPU, memory, disk, and network-intensive workloads with the ability to link services together

License: MIT License

Dockerfile 0.36% JavaScript 33.08% Shell 52.51% Perl 14.06%
network-intensive-workloads disk-intensive-workloads cpu-intensive-workloads memory-intensive-workloads workload service-mesh service-mesh-performance-benchmark service-chains

sfc-stress's Introduction

Welcome to Michel's GitHub Page! πŸ‘‹

My name is Michel Gokan Khan & I'm a computer science researcher. I'm currently conducting research as a PostDoc at KTH Royal Institute of Technology and AstraZeneca in ML-Driven Optimization of Production in Industry 5.0. I have a PhD in computer science from KAU Sweden πŸ‡ΈπŸ‡ͺ. My focus was optimizing service function chains in the context of cloud native computing with use cases in 5G networks and NFV through deep learning.

IMPORTANT NOTE: Unless otherwise mentioned in the README.md, any contributions or repositories on my account are not affiliated with any organization, company, or institution I am or was affiliated with.

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LIDo_Int

I recieved BSc degree in applied mathematics and continued with MSc in computer engineering @ Iran University of Science and Technology. I started my PhD journey with the Distributed Systems and Communications lab (DISCO) @ Karlstad University (KAU) in Sweden. During my PhD, I worked in Ericsson research and development department as a research intern and directly contributed to the projects related to optimizing both the 4G-LTE and the 5G core.

I have a established publications and inventions record. To know more about me and get access to the most recent information and updates about my research, please visit my Linkedin profile or follow me on Twitter.

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