VXA: A Virtual Architecture for Durable Compressed Archives

TL;DR

VXA is an archival system that stores executable decoders in a virtual machine environment, ensuring long-term accessibility and security while maintaining high performance and reusing existing optimized decoders.

Contribution

VXA introduces a virtual machine-based archival system that preserves decoders in a hardware-independent environment, enabling secure, efficient, and long-term data access.

Findings

Decoders run safely in a virtual machine with less than 15% performance overhead.

Archived decoders are small, typically 30-130KB, and can be shared across multiple files.

VXA effectively preserves access to compressed data over long periods.

Abstract

Data compression algorithms change frequently, and obsolete decoders do not always run on new hardware and operating systems, threatening the long-term usability of content archived using those algorithms. Re-encoding content into new formats is cumbersome, and highly undesirable when lossy compression is involved. Processor architectures, in contrast, have remained comparatively stable over recent decades. VXA, an archival storage system designed around this observation, archives executable decoders along with the encoded content it stores. VXA decoders run in a specialized virtual machine that implements an OS-independent execution environment based on the standard x86 architecture. The VXA virtual machine strictly limits access to host system services, making decoders safe to run even if an archive contains malicious code. VXA's adoption of a "native" processor architecture instead of type-safe language technology allows reuse of existing "hand-optimized" decoders in C and assembly language, and permits decoders access to performance-enhancing architecture features such as vector processing instructions. The performance cost of VXA's virtualization is typically less than 15% compared with the same decoders running natively. The storage cost of archived decoders, typically 30-130KB each, can be amortized across many archived files sharing the same compression method.