Challenges and Opportunities for Efficient Serverless Computing at the Edge

Serverless computing frameworks allow users to execute a small application (dedicated to a specific task) without handling operational issues such as server provisioning, resource management, and resource scaling for the increased load. Serverless computing originally emerged as a Cloud computing framework, but might be a perfect match for IoT data processing at the Edge. However, the existing serverless solutions, based on VMs and containers, are too heavy-weight (large memory footprint and high function invocation time) for operating efficiency and elastic scaling at the Edge. Moreover, many novel IoT applications require low-latency data processing and near real-time responses, which makes the current cloud-based serverless solutions unsuitable. Recently, WebAssembly (Wasm) has been proposed as an alternative method for running serverless applications at near-native speeds, while having a small memory footprint and optimized invocation time. In this paper, we discuss some existing serverless solutions, their design details, and unresolved performance challenges for an efficient serverless management at the Edge. We outline our serverless framework, called aWsm, based on the WebAssembly approach, and discuss the opportunities enabled by the aWsm design, including function profiling and SLO-driven performance management of users' functions. Finally, we present an initial assessment of aWsm performance featuring average startup time (12 mu s to 30 mu s) and an economical memory footprint (ranging from 10s to 100s of kB) for a subset of MiBench microbenchmarks used as functions.