Amelie Chi Zhou

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—Recently, performance and monetary cost optimizations for workflows from various applications in the cloud have become a hot research topic. However, we find that most existing studies adopt ad hoc optimization strategies, which fail to capture the key optimization opportunities for different workloads and cloud offerings (e.g., virtual machines with(More)
—Recently, we have witnessed workflows from science and other data-intensive applications emerging on Infrastructure-as-a-Service (IaaS) clouds, and many workflow service providers offering workflow as a service (WaaS). The major concern of WaaS providers is to minimize the monetary cost of executing workflows in the IaaS cloud. While there have been(More)
In this paper, we propose monetary cost optimizations for MPI-based applications with deadline constraints on Amazon EC2. Particularly, we consider to utilize two kinds of Amazon EC2 instances (on-demand and spot instances). As a spot instance can fail at any time due to out-of-bid events, fault tolerant executions are necessary. Through detailed studies,(More)
Resource provisioning for scientific workflows in Infrastructure-as-a-service (IaaS) clouds is an important and complicated problem for budget and performance optimizations of workflows. Scientists are facing the complexities resulting from severe cloud performance dynamics and various user requirements on performance and cost. To address those complexity(More)
—SSDs (Solid State Drives, or flash disks) have been considered as ideal storage for various data-intensive workloads, because of the low random access latency and the intra-disk multi-chip parallelism. However, due to inherent nature of flash memories, update-intensive workloads cause the flash disk fragmented, and trigger costly internal activities such(More)
—Cloud computing has recently evolved as a popular computing infrastructure for many applications. Scientific computing, which was mainly hosted in private clusters and grids, has started to migrate development and deployment to the public cloud environment. eScience as a service becomes an emerging and promising direction for science computing. We review(More)
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