W28: Workshop on Cloud Computing and AI
Organizers: Rajarshi Das (IBM T.J. Watson Research) and Adam Wierman (CalTech)
Cloud Computing has rapidly emerged as an important paradigm attracting profound interest in both industry and academia. However, Cloud Computing’s dynamic, multi-tiered and distributed nature presents a number of challenges and unique open issues in the monitoring, integration and management of such systems. As Cloud Computing systems grow in size, heterogeneity and complexity, with increasingly dynamic intra-tier and inter-tier interactions and dependencies, one-off solutions for real-time configuration and optimization by expert software developers and system administrators will become impractical in meeting the needs and requirements from diverse range of cloud application domains. On the other hand, the ability to rapidly deploy interacting virtual resources and to monitor and control those deployed resources at different functional levels offer opportunities to employ a spectrum of AI approaches to make Cloud Computing systems more robust, efficient and autonomic. The overall goal of this workshop is to develop an AI research agenda for Cloud Computing. It aims to bring together academic and industrial researchers to identify major problem domains, match mature technologies to current problems, and chart the trajectory of interdisciplinary research techniques that can be applied in Cloud Computing. The workshop will emphasize relatively high-level perspectives, including position talks and surveys of sub-fields and problem domains. The workshop is intended to be accessible to the broader AI community, encourage communication between sub-fields, and focus on important future directions for Cloud Computing.