@inproceedings{song2026mcptool,author={Song, Moohyun and Kim, Hayoung and Lee, Kyoohyun and Son, Jae Gi and Lee, Kyungyong},title={Orchestrating WASM-based MCP Tool Runtimes for AI Agents across Edge-Cloud Continuum},year={2026},booktitle={Proceedings of the 26th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing},series={CCGrid '26},note={To appear},keywords={international},}
HybridServe: Adaptive WebAssembly-Container Runtime Selection for Edge Serverless Computing
Seokhyeon Kang*, Moohyun Song*, Taeyoon Kim*, Soohyuk Lee, Jaeseob Han, Hyeokman Kim, and Kyungyong Lee
In Proceedings of the 11th International Workshop on Serverless Computing, 2025
Edge serverless environments with limited CPU, memory, and heterogeneous hardware demand efficient execution under resource constraints. A key challenge in serverless computing is cold start, where a function instance is created and initialized from scratch instead of reusing an already initialized (warm) instance, which is particularly severe in edge environments. Container-based platforms exhibit cold start latencies exceeding hundreds of milliseconds with tens of megabyte images, while WebAssembly (WASM) provides less than ten millisecond initialization and compact binaries, but slower execution. We comprehensively analyze multiple WASM runtimes (Wasmtime, Wasmer, WasmEdge) and their compiler backends, revealing that WASM reduces cold start latency by up to 88.1% and image size by up to 99.17%, while exhibiting 36.15% slower execution and 9.26% higher power consumption for compute-intensive workloads. Based on these complementary characteristics, we propose HybridServe, a dynamic runtime selection framework that leverages WASM during container cold starts while preparing containers in the background. Evaluation on Azure Function Trace demonstrates 43.11% average response time reduction versus WASM-only and 91.9% cold start latency reduction versus container-only deployments, effectively mitigating the performance-isolation trade-off in edge serverless computing.
@inproceedings{kang2025hybridserve,author={Kang, Seokhyeon and Song, Moohyun and Kim, Taeyoon and Lee, Soohyuk and Han, Jaeseob and Kim, Hyeokman and Lee, Kyungyong},title={HybridServe: Adaptive WebAssembly-Container Runtime Selection for Edge Serverless Computing},year={2025},isbn={9798400723025},publisher={Association for Computing Machinery},url={https://doi.org/10.1145/3774899.3775011},doi={10.1145/3774899.3775011},booktitle={Proceedings of the 11th International Workshop on Serverless Computing},pages={1--6},numpages={6},series={WoSC11 '25},keywords={international},}
Multi-Node Spot Instances Availability Score Collection System
Sungkyu Cheon*, Kyumin Kim*, Kyunghwan Kim*, Moohyun Song, and Kyungyong Lee
In Proceedings of the 34th International Symposium on High-Performance Parallel and Distributed Computing, 2025
Spot instances let users access unused cloud resources at significantly reduced costs. While cloud vendors offer availability information, existing tools like Spotlake only provide single-node availability data, which falls short for modern distributed applications. This paper highlighted the limitations of single-node availability data and introduced a multi-node availability dataset collection system. We analyzed the collected data and enhanced Spotlake to share these multi-node datasets publicly for broader use.
@inproceedings{cheon2025multinode,author={Cheon, Sungkyu and Kim, Kyumin and Kim, Kyunghwan and Song, Moohyun and Lee, Kyungyong},title={Multi-Node Spot Instances Availability Score Collection System},year={2025},isbn={9798400718694},publisher={Association for Computing Machinery},url={https://doi.org/10.1145/3731545.3735122},doi={10.1145/3731545.3735122},booktitle={Proceedings of the 34th International Symposium on High-Performance Parallel and Distributed Computing},articleno={33},numpages={2},series={HPDC '25},keywords={international},}
