Simulating a Shared Register in a System that Never Stops Changing
Hagit Attiya, Hyun Chul Chung, Faith Ellen, Saptaparni Kumar and, Jennifer L. Welch

TL;DR
This paper introduces a novel simulation of an atomic read/write register in an asynchronous system that continuously changes size and experiences crash failures, without requiring the system to stop changing for extended periods.
Contribution
It presents the first simulation method for dynamic, crash-prone systems that can change size indefinitely while maintaining atomic register properties.
Findings
Supports continual system size changes with bounded node entry and exit.
Tolerates crash failures proportional to current system size.
Ensures atomicity in highly dynamic environments.
Abstract
Simulating a shared register can mask the intricacies of designing algorithms for asynchronous message-passing systems subject to crash failures, since it allows them to run algorithms designed for the simpler shared-memory model. Typically such simulations replicate the value of the register in multiple servers and require readers and writers to communicate with a majority of servers. The success of this approach for static systems, where the set of nodes (readers, writers, and servers) is fixed, has motivated several similar simulations for dynamic systems, where nodes may enter and leave. However, existing simulations need to assume that the system eventually stops changing for a long enough period or that the system size is bounded. This paper presents the first simulation of an atomic read/write register in a crash-prone asynchronous system that can change size and withstand nodes…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDistributed systems and fault tolerance · Advanced Data Storage Technologies · Parallel Computing and Optimization Techniques
