Benefits of Stabilization versus Rollback in Self-Stabilizing Graph-Based Applications on Eventually Consistent Key-Value Stores

Duong Nguyen and Sandeep S. Kulkarni


In this paper, we evaluate and compare the performance of two approaches, namely self-stabilization and rollback, to handling consistency violating faults (cvfs) that occur when a self-stabilizing distributed graph-based program is executed on an eventually consistent key-value store. Consistency violating faults are caused by reading wrong values due to weaker level of consistency provided by the key-value store. One way to deal with these faults is to utilize rollback whereas another way is to rely on the property of self-stabilization that is expected to provide recovery from arbitrary states. We evaluate both these approaches in different case studies –planar graph coloring, arbitrary graph coloring, and maximal matching– as well as for different problem dimensions such as input data characteristics, workload partition, and network latency. We also consider the effect of executing a non-stabilizing algorithm with rollback with a similar stabilizing algorithm that does not utilize rollback.


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