Testbed • Measurements • Real-World Data

The BLOCK VECTOR Testbed: real nodes, real networks, real data.

The ER-Series rack is backed by an active testbed that measures the behavior of full nodes, miners, sensors, and network equipment under real-world conditions. This environment is used for STEM curriculum, grant reporting, and applied research.

Rather than presenting hypothetical charts or simulated loads, the BLOCK VECTOR testbed generates measured datasets that reflect real hardware, realistic workloads, and reproducible procedures. This enables students, labs, and grant evaluators to work with physical systems rather than abstract diagrams.

Compute, storage, and generation nodes

The ER-Series testbed uses a mix of compute, storage, and generation nodes designed to model a small-scale research cluster. These include full nodes, load generators, and modular Pi clusters that students can enable or disable at will.

Raspberry Pi 5 full nodes with dual-NVMe storage for high-throughput blockchain operations.
Structured testing of NVMe throughput, queue depth behavior, and sustained IO under load.
Switch-controlled Raspberry Pi clusters (30–40 units capacity) for network stress testing and distributed systems education.
Students can activate cluster subsets to create variable load profiles and observe switching, routing, and throughput changes in real time.
BitAxe miners and low-power teaching miners as generation nodes for energy-use studies.
Optional service nodes for monitoring, data polling, logging, and telemetry.

This configuration allows educators and grant partners to simulate real-world network and storage workloads using inexpensive, scalable hardware that students can operate directly.

Networking test scenarios

The testbed includes a multi-WAN, VLAN-segmented network built on TP-Link Omada hardware. This enables controlled studies of network resilience and routing behavior.

Multi-WAN routing with fiber primary and secondary ISP failover.
VLAN segmentation for management, nodes, miners, sensors, and test devices.
DHCP, DNS, and routing behavior across isolated broadcast domains.
Controlled outage simulation for teaching network resilience and redundancy.
Live capture of failover time, latency changes, and throughput impact.

Students and researchers can observe network behavior at the protocol level, compare routing strategies, and measure the impact of outages in real time.

Compute & generation nodes

Inside the ER-Series enclosure, the testbed runs a mix of compute and generation nodes that model a small-scale micro data center.

Raspberry Pi 5 full nodes with dual NVMe storage.
BitAxe miners and educational ASIC miners.
Service nodes for monitoring, polling, and metrics collection.
Lightweight containers for teaching distributed system concepts.
Optional expansion nodes for hyperlocal LLM and inference workloads.

Each device contributes to a measurable system that reflects modern computing, networking, and energy-use challenges.

Measurement workflows

All testbed measurements follow a documented workflow so that classes, research assistants, and partner institutions can reproduce experiments with confidence.

Sensor calibration and baseline thermals.
Power measurement under idle, compute, and mining loads.
WAN failover test cycles with timing and route-capture.
Hashrate and efficiency logging for ASIC miners.
Environmental logging during extended workloads.
Export of datasets to CSV/JSON for analysis and classroom labs.

These structured procedures are designed to help grant partners meet reporting requirements while giving students meaningful hands-on data.

Purpose of the testbed

The testbed exists to support reproducible education and research. It provides:

A reference implementation so grantors can evaluate the platform.
Hands-on learning for students in networking, mining, and data science.
Repeatable measurements for formal grant reporting.
A safe environment to explore emerging workloads on extremely low-power hardware.

See how the testbed supports grant outcomes »