Appendix for Biodegradable Transient Data Centers: A Multi-Objective Optimization Framework for Sustainable Computing in Extreme Environments

This paper develops an integrated optimization framework for biodegradable pop-up data centers intended for temporary or extreme environments where conventional computing infrastructure cannot operate. While prior studies address sustainable materials, energy harvesting, or transient electronics individually, existing literature lacks a unified model that simultaneously captures workload dynamics, renewable energy variability, and degradation-driven end-of-life behavior. To close this gap, the proposed architecture combines biodegradable substrates, ambient solar–thermal energy harvesters, and environmentally triggered dissolution mechanisms into a coordinated system that operates autonomously throughout its lifecycle. The framework formulates transient data center operation as a multi-objective optimization problem linking computational performance, harvested energy availability, and degradation-aware lifecycle control. A Non-dominated Sorting Genetic Algorithm III (NSGA-III) schedules workloads, allocates renewable energy, and regulates dissolution timing under fluctuating environmental and material conditions. This enables the system to maintain balanced operation without external power supply or manual supervision. Simulation results confirm the feasibility of self-powered biodegradable AI and blockchain micro-clusters, demonstrating improved energy utilization under constrained conditions, stable performance across variable workloads, and predictable, residue-free end-of-life dissolution. These findings establish a pathway toward zero-waste, energy-autonomous transient computing systems for disaster response, military missions, and other short-lived deployments.