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Location-Aware Container Scaling (LACS) in Geo-distributed Clouds

<p>Datasets and code for the problem of location-aware container scaling (LACS) in geo-distributed clouds:</p> <p>Randomly extracted one day&rsquo;s workload from WikiBench and NASA HTTP: AppWorkload.py</p> <p>Facebook subscribers by January 2020 to simulate the distribution of application requests among different user regions: FacebookUserData.csv</p> <p>Sprint IP Network location as 82 user regions from 35 countries on 6 continents: SprintLocation.csv</p> <p>Observation on the network latency matrix among 82 user centres: LatencyMatrix.py</p> <p>Representative code using openAI&#39;s gym environment:&nbsp;deepscale.py</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0