Minimal Virtual Machines on IoT Microcontrollers: The Case of Berkeley Packet Filters with rBPF - Archive ouverte HAL Access content directly
Conference Papers Year :

Minimal Virtual Machines on IoT Microcontrollers: The Case of Berkeley Packet Filters with rBPF

(1) , (1)
1

Abstract

Virtual machines (VM) are widely used to host and isolate software modules. However, extremely small memory and low-energy budgets have so far prevented wide use of VMs on typical microcontrollerbased IoT devices. In this paper, we explore the potential of two minimal VM approaches on such lowpower hardware. We design rBPF, a register-based VM based on extended Berkeley Packet Filters (eBPF). We compare it with a stack-based VM based on We-bAssembly (Wasm) adapted for embedded systems. We implement prototypes of each VM, hosted in the IoT operating system RIOT. We perform measurements on commercial off-the-shelf IoT hardware. Unsurprisingly, we observe that both Wasm and rBPF virtual machines yield execution time and memory overhead, compared to not using a VM. We show however that this execution time overhead is tolerable for low-throughput, lowenergy IoT devices. We further show that, while using a VM based on Wasm entails doubling the memory budget for a simple networked IoT application using a 6LoWPAN/CoAP stack, using a VM based on rBPF requires only negligible memory overhead (less than 10% more memory). rBPF is thus a promising approach to host small software modules, isolated from OS software, and updatable on-demand, over low-power networks.
Fichier principal
Vignette du fichier
50727_minimal_virtual_machines_on_iot_microcontrollers.pdf (191.19 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03019639 , version 1 (02-12-2020)

Identifiers

Cite

Koen Zandberg, Emmanuel Baccelli. Minimal Virtual Machines on IoT Microcontrollers: The Case of Berkeley Packet Filters with rBPF. PEMWN 2020 - 9th IFIP/IEEE International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks, Dec 2020, Berlin / Virtual, Germany. ⟨hal-03019639⟩
118 View
139 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More