GitHub / AwadallaAlashkar / SchedMaster
SchedMaster lies in its hybrid approach - combining classical scheduling algorithms with optimization techniques like Greedy Algorithms, Dynamic Programming, and Backtracking. Additionally, it leverages simple ML models to predict process behavior, detect anomalies in resource usage, and recommend the most suitable scheduling strategies.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AwadallaAlashkar%2FSchedMaster
PURL: pkg:github/AwadallaAlashkar/SchedMaster
Stars: 0
Forks: 0
Open issues: 0
License: gpl-3.0
Language: Python
Size: 267 KB
Dependencies parsed at: Pending
Created at: 3 months ago
Updated at: 3 months ago
Pushed at: 3 months ago
Last synced at: 3 months ago
Topics: algorithm-optimization, anomaly-detection, bankers-algorithm, cpu-intensive, cpu-scheduling, disk-scheduling, isolation-forest, machine-learning, optimization, resourse-manager, simulation