In this paper, we evaluate and compare the performance of two approaches, namely self-stabilization and rollback, to handling consistency violation faults (cvf) that occurred when a distributed program is executed on eventually consistent key-value store. We observe that self-stabilization is usually better than rollbacks in our experiments. Moreover, when we aggressively allow more cvf in exchange of eliminating mechanisms for guaranteeing atomicity requirements of actions, we observe the programs in our case studies achieve a speedup between 2--15 times compared with the standard implementation. We also analyze different factors that contribute to the results. Our results and analysis are useful in helping a system designer choose proper design options for their program.

The last decade has witnessed rapid proliferation of cloud computing. While even the smallest distributed programs (with 3-5 actions) produce many unanticipated error cases due to concurrency involved, it seems short of a miracle these web-services are able to operate at those vast scales. In this paper, we explore the factors that contribute most to the high-availability of cloud computing services and examine where self-stabilization could fit in that picture.The last decade has witnessed rapid proliferation of cloud computing. While even the smallest distributed programs (with 3-5 actions) produce many unanticipated error cases due to concurrency involved, it seems short of a miracle these web-services are able to operate at those vast scales. In this paper, we explore the factors that contribute most to the high-availability of cloud computing services and examine where self-stabilization could fit in that picture.