CSR: Medium: Collaborative Research: Architecting Performance Sensitive Applications for the Cloud

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Cloud computing offers IT organizations the ability to creategeo-distributed, and highly scalable applications while providingattractive cost-saving advantages. Yet, architecting, configuring, andadapting cloud applications (latency-sensitive web applications andbulk data processing applications) to meet their stringent performancerequirements is a challenge given the rich set of configurationoptions, shared multi-tenant nature of cloud platforms, and dynamicsresulting from activities such as planned maintenance.This project is developing novel methodologies, algorithms, andsystems that can enable application architects to (1) judiciouslyarchitect applications across multiple cloud data-centers whileconsidering application performance requirements, cost savingobjectives, and cloud pricing schemes guided by performance and costmodels of cloud components; (2) automatically learn effectiveapplication configurations and configuration-to-performance predictionmodels through statistical machine learning techniques; and (3) createapplications that can adapt to ongoing dynamics in cloud environmentsthrough transaction reassignment over shorter time-scales, andapplication migration over longer time-scales.The impact of this research is multi-fold: (1) Enable IT organizationsto significantly reduce costs by optimally moving their operations tothe cloud; (2) create benchmarks based on operationally deployedapplications and collecting workload traces which will be madeavailable to the research community; (3) make developed algorithms andsystems widely available as open source software; (4) inform thedesign of a nation-wide health-care cloud in Thailand; (4) introducecloud computing related topics in the undergraduate and graduatecurriculum; and (6) train multiple Ph.D., M.S., and undergraduatestudents, with explicit effort to recruit and train students fromunder-represented minority groups.