Designing dynamic load-sharing strategies for IoT devices with severe memory constraints — enabling richer functionality on limited hardware.
Many IoT deployments rely on microcontrollers and embedded systems with kilobytes of RAM and flash storage — far too limited for the complex workloads modern applications demand. Dynamic load sharing offers a path forward: intelligently distributing computation across devices in a network to collectively handle tasks that no single device could manage alone.
Our survey work maps the landscape of existing load-sharing approaches for memory-constrained devices, identifying gaps in current techniques and opportunities for improvement. We examine strategies ranging from task migration to cooperative caching.
Building on this, we design and simulate load-sharing protocols that account for the real-world constraints of IoT environments: intermittent connectivity, heterogeneous hardware, and strict energy budgets — enabling richer functionality without requiring hardware upgrades.