pRnR: A Parallel Record-Replay Framework for Virtual Machines

• Published in: 2020 IEEE 38th International Conference on Computer Design (ICCD) pp. 610 - 618
• Main Authors: Wang, Wei, Cui, Lei, Hao, Zhiyu, Fei, Haiqiang, Wang, Chonghua, Peng, Yaqiong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2020
• Subjects: continuous snapshots; deterministic replay; parallel replay; syscall diagnosis; virtual machine
• ISSN: 2576-6996
• DOI: 10.1109/ICCD50377.2020.00106

The record and replay(RnR) technology of virtual machine(VM) provides the ability to reproduce the past execution of a VM deterministically. It has many promising applications in the cloud environment, including fault tolerance, security analysis, and failure diagnosis. Existing studies in this area pay more effort in optimizing the record method, such as reducing performance penalty and storage costs. However, considering that many practical applications follow the record once, replay many mode, the optimization for the replay is more critical, especially for efficiency. In this paper, we propose pRnR, a novel parallel RnR framework, to support efficient replay. By combining the native RnR framework with an improved continuous snapshots mechanism, pRnR divides the full execution into many independent and complete slices, each of which supports arbitrary replay. In addition, it supports two replay modes to improve replay efficiency, i.e., multi-slice parallel replay and multi-dimension parallel replay. Moreover, we apply our pRnR framework to syscall-based diagnosis to demonstrate its usability. The experimental results show that pRnR is more efficient than existing RnR frameworks.