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Cited by 406

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The design and implementation of Zap: a system for migrating computing environments

Osman, Steven, Subhraveti, Dinesh, Su, Gong, Nieh, Jason·2002·ACM SIGOPS Operating Systems Review

Abstract

We have created Zap, a novel system for transparent migration of legacy and networked applications. Zap provides a thin virtualization layer on top of the operating system that introduces pods, which are groups of processes that are provided a consistent, virtualized view of the system. This decouples processes in pods from dependencies to the host operating system and other processes on the system. By integrating Zap virtualization with a checkpoint-restart mechanism, Zap can migrate a pod of processes as a unit among machines running independent operating systems without leaving behind any residual state after migration. We have implemented a Zap prototype in Linux that supports transparent migration of unmodified applications without any kernel modifications. We demonstrate that our Linux Zap prototype can provide general-purpose process migration functionality with low overhead. Our experimental results for migrating pods used for running a standard user's X windows desktop computing environment and for running an Apache web server show that these kinds of pods can be migrated with subsecond checkpoint and restart latencies.

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Metadata

Authors
Osman, S., Subhraveti, D., Su, G., & Nieh, J.
Venue
ACM SIGOPS Operating Systems Review
Published
2002-12-31
Volume
36
Issue
SI
Pages
361-376
ISSN
0163-5980 (ISSN-L)
OpenAlex
W2157801087
Cited by
406
References
19
FWCI
19.56
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The design and implementation of Zap: a system for migrating computing environments. https://app.cochat.ai/papers/10.1145/844128.844162
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Osman, S., Subhraveti, D., Su, G., & Nieh, J. (2002). The design and implementation of Zap: a system for migrating computing environments. ACM SIGOPS Operating Systems Review. https://doi.org/10.1145/844128.844162

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.