First Name: 
Sashko
Last Name: 
Ristov
Affiliation: 
University of Innsbruck
Job Title: 
Postdoctoral University Assistant
Expertise: 
Distributed Systems, Workflows, Serverless

Datasets & Analysis

Logs from running Monte Carlo simulation as serverless functions on Frankfurt, North Virginia, Tokyo regions of four FaaS systems (AWS, Google, IBM, Alibaba).

Each execution is repeated 5 times (all are warm start). 

The conducted analysis is a part of a submitted manuscript to IEEE TSC. 

Instructions: 

The zip file contains several types of datasets.

1. Logs contain details of each execution on all providers / regions. Each column has a self-descriptive title. The first 1000 functions on AWS, 200 on Alibaba, 100 on Google and 100 on IBM are all executed concurrently. The remaining functions are executed once some of the active functions finish due to concurrency limit of the provider.

2. Functions contain the Monte Carlo functions that are executed (in Python).

Based on these logs, we evaluated our xAFCL service along with our new FaaS model and the scheduler. 

3. Makespan<k> contains measured makespan for each set of experiments for scaling factor k. Experiments are denoted as N/r where N is the number of functions that are distributed across the r regions. N=k*r for weak scaling and N=12*r for strong scaling.

4. Regions are ordered in the file xAFCLModelInputs.csv. 

5. Summary presents the achieved average makespan and maximum throughput for each scaling factor k.

 

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This dataset contains the execution time of running a total of 3000 functions scattered evenly to three regions: AWS Frankfurt, IBM Frankfurt and IBM Tokyo from University of Innsbruck.

Each execution is repeated three times.

Instructions: 

This dataset contains the execution time of running a total of 3000 functions scattered evenly to three regions: AWS Frankfurt, IBM Frankfurt and IBM Tokyo from University of Innsbruck.

The results show how scalable is the execution of no-op function. While the curve of AWS is almost linear starting from 0, IBM curves have a huge jump and then huge period is stable (horizontal).

 

The dataset (excel document) containst four sheets, one for each region and one for summary, including the diagram. 

 

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