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Benchmark for supply chain monitoring properties using BeepBeep

<p>This is an instance of the <a href="https://github.com/liflab/labpal">LabPal</a> experimental environment to benchmark the execution of processor chains for the <a href="https://liflab.github.io/beepbeep-3">BeepBeep</a> event stream engine.</p> <p>The considered use case is related to the concept of <em>hyperconnected logistics</em>. In this model, the entire world can be split at the smallest scale into <em>unit zones</em>, whose size depends on expected demand density. Adjacent unit zones are grouped into local <em>cells</em>, which in turn are gathered into <em>areas</em>, which form <em>regions</em>. Simultaneously, several hub networks are defined to link these different layers: <em>access hubs</em> link unit zones together; <em>local hubs</em> link local cells, and <em>gateway hubs</em> link areas. Different hub levels may exist inside the same physical entity (e.g., a local hub might also be an access hub), thus allowing interactions between the different layers.</p> <p>In a recent work (see citation below), the authors showed how to concretely adapt a hyperlogistics simulation in order to integrate an Ethereum blockchain backend, in such a way that every action made by carriers is publicly stored in transactions on the blockchain itself. The combination of such simulation and blockchain backend allowed us to generate the traces used to monitor a number of properties.</p> <p>The experiments in this benchmark measure the throughput of a variety of BeepBeep processor chains on simulated logs of blockchain events generated on the fly.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

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

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
0
Engagement
4

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