TinyVM: an energy-efficient execution infrastructure for sensor networks

Energy-efficient implementation techniques for virtual machines (VMs) have received little attention yet: conventional wisdom claims that VMs have a diametrical effect on energy consumption and sensor network applications on VMs are therefore short-lived. In this paper we argue that bytecode interpretation is affordable for sensor networks if we synthesize VMs specifically for energy-efficiency. We present TinyVM, an execution infrastructure that seamlessly integrates with nesC/TinyOS and C-based environments. TinyVM achieves high code density through the use of compressed bytecode as the primary program representation. Compressed bytecode allows rapid application deployment with low communication overhead. TinyVM executes compressed byte-code in-place, which eliminates the need for a decompression stage and thereby reduces memory consumption on sensor nodes. Our infrastructure automates the creation of energyefficient application-specific VMs. Applications are partitioned in machine-code, byte-code and VM instruction set extensions. Partitioning is manually controlled and/or fully guided by a discrete optimization problem that produces a partitioning with lowest energy consumption for a given memory space constraint. We provide experimental results for sensor network benchmarks and selected applications on Atmega128-based motes and the Intel iMote2.