Cloudslab/DLSF
[TMC'20] Deep Learning based Scheduler for Stochastic Fog-Cloud computing environments
This project offers a real-time task scheduler designed for Internet-of-Things (IoT) applications running across both mobile-edge and cloud resources. It takes in workload data and host parameters, then provides optimized task allocation decisions to improve system performance. Operations engineers, data center managers, or anyone managing distributed IoT infrastructure would find this useful for efficiently utilizing resources.
126 stars. No commits in the last 6 months.
Use this if you need to dynamically schedule IoT application tasks across a decentralized fog-cloud environment and want to minimize energy consumption, response time, and operating costs.
Not ideal if your computing environment is fully centralized or if your scheduling needs are static and don't require real-time adaptation to changing workloads.
Stars
126
Forks
39
Language
Java
License
GPL-3.0
Category
Last pushed
Dec 06, 2022
Commits (30d)
0
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