Michio Honda | Searcharxiv

arXiv2024

Designing Transport-Level Encryption for Datacenter Networks

Cloud applications need network data encryption to isolate from other tenants and protect their data from potential eavesdroppers in the network infrastructure. This paper presents SMT, a protocol design for emerging datacenter transport protocols, such as NDP and Homa, to integrate data encryption. SMT integrates TLS-based encryption with a message-based transport protocol that supports efficient Remote Procedure Calls (RPCs), a common workload in datacenters. This architecture enables the use of per-message record sequence number spaces in a secure session, while ensuring unique message identities to prevent replay attacks. It also enables the use of existing NIC offloads designed for TLS over TCP, while being a native transport protocol alongside TCP and UDP. We implement SMT in the Linux kernel by extending Homa/Linux and improve RPC throughput by up to 41 % and latency by up to 35 % in comparison to TLS/TCP.

cs.CR↗

arXiv2024

ParaLog: Consistent Host-side Logging for Parallel Checkpoints

Output-intensive scientific applications are highly sensitive to low storage throughput. While existing scientific application stacks are optimized for traditional High-Performance Computing (HPC) environments with high remote storage and network bandwidth, these assumptions often fail in modern settings like cloud deployment. This is because the existing scientific application I/O stack fails to leverage the available resources. At the same time, scientific applications exhibit special synchronization and data output requirements that are difficult to satisfy using traditional approaches such as block-level or filesystem-level caching. We introduce ParaLog, a distributed host-side logging approach designed to accelerate scientific applications transparently. ParaLog emphasizes deployability, enabling support for unmodified message passing interface (MPI) applications and implementations while preserving crash consistency semantics. We evaluate ParaLog across traditional HPC, cloud HPC, local clusters, and hybrid environments, demonstrating its capability to reduce end-to-end execution time by 13-26% for popular scientific applications in cloud settings.

cs.DC↗