01 / ENERGY
Renewable-aware scheduling
When can workloads be shifted or queued to better align with available generation and site energy conditions?
Potential measures: power draw, generation profile, queue time and completed work.Research & Education
Research Program
Applied research into how distributed computing can operate alongside residential renewable energy, storage and real-world infrastructure constraints.
RESEARCH FOCUS
01 Energy-aware workload scheduling
02 Distributed compute orchestration
03 Measurement and utilisation
04 Resilience and resource efficiency
Research priorities, not claims of published findings.
Research Context
Research grounded in working infrastructure
SolarCompute is developing a distributed computing platform that connects participating machines to supported workloads. Its existing residential solar-powered installation provides a practical environment for engineering trials and instrumentation.
The research program aims to turn operating observations into repeatable experiments. Engineering demonstrations and internal tests are not presented as peer-reviewed research or independently verified outcomes.
Test Environment
A practical infrastructure case study
The current installation brings together residential renewable energy, on-site computing equipment, network coordination and energy monitoring. It provides a starting point for studying operational trade-offs.
Renewable supplyRooftop solar and site energy conditions
Compute nodesPhysical machines running approved workloads
Platform controlsHardware matching, dispatch and monitoring
MeasurementPower, workload and reliability observations
The installation is an operational development environment. Performance, emissions and energy savings require defined measurement methods and validation before publication.
Research Priorities
Questions worth testing
Each theme is framed as a research question rather than a predetermined result.
02 / DISTRIBUTION
Distributed workload execution
How do heterogeneous machines affect scheduling, throughput and execution reliability across a changing network?
Potential measures: job success, latency, utilisation and node availability.03 / HARDWARE
Resource efficiency
How should workloads be assigned to approved hardware configurations without overstating capability?
Potential measures: resource usage, runtime, compatibility and failed dispatches.04 / RESILIENCE
Continuity and fallback
What operational policies help preserve service continuity when participating machines are unavailable or busy?
Potential measures: recovery time, queue outcomes and fallback frequency.Research Method
From engineering questions to evidence
01Define
Set the research question, test conditions and success criteria.
02Instrument
Capture relevant energy, machine and workload measurements.
03Test
Run controlled comparisons and document operating conditions.
04Review
Assess limitations, repeatability and potential next experiments.
05Report
Publish findings only when evidence and review support them.
Research Status
Engineering development today. Validated findings as they emerge.
Operational development
Distributed machine registration, workload execution, hardware approval and monitoring are areas of ongoing engineering work.
Research opportunities
Energy-aware scheduling, comparative performance studies and repeatable measurement protocols are candidate investigations.
Publications
No research papers or independently validated findings are listed on this page at present. Approved publications can be added with dates, authors and supporting material.
Collaboration
Explore a research partnership
SolarCompute welcomes enquiries from universities, researchers, educators and technical organisations interested in practical distributed computing and renewable energy research.
Start a discussion
Tell us about your research area, proposed question, methodology or educational project. Access to infrastructure or data would be subject to scope, suitability and agreement.
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