技术报告：在基于自稳定图的应用程序中稳定化与回滚在最终一致键值存储上的优势
Technical Report: Benefits of Stabilization versus Rollback in Self-Stabilizing Graph-Based Applications on Eventually Consistent Key-Value Stores
摘要：
在本文中，我们评估和比较两种方法的性能，即自稳定和回滚，处理一致性违反故障（\cvf）时发生的自稳定的分布式基于图的程序上执行最终一致的键值存储。违反一致性的错误是由于键值存储提供的一致性级别较低而导致读取错误的值而引起的。处理这些故障的一种方法是利用回滚，而另一种方法是依赖于期望提供从任意状态恢复的自稳定特性。我们评估这两种方法在不同的案例研究-平面图着色，任意图着色，最大匹配-以及不同的问题维度，如输入数据的特点，工作负载分区，和网络延迟。我们还考虑了执行不稳定算法回滚与类似的稳定算法，不利用回滚的效果。
英文摘要：
In this paper, we evaluate and compare the performance of two approaches, namely self-stabilization and rollback, to handling consistency violating faults (\cvf) 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 non-stabilizing algorithm with rollback with a similar stabilizing algorithm that does not utilize rollback.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
