Monetary Cost-Aware Checkpointing and Migration on Amazon Cloud Spot Instances

摘要

Recently introduced spot instances in the Amazon Elastic Compute Cloud (EC2) offer low resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability tradeoffs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how mechanisms, namely, checkpointing and migration, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive checkpointing schemes in terms of monetary costs and improvement of job completion times. We evaluate schemes that apply predictive methods for spot prices. Furthermore, we also study how work migration can improve task completion in the midst of failures while maintaining low monetary costs. Trace-based simulations show that our schemes can reduce significantly both monetary costs and task completion times of computation on spot instance.