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Special Issue on Intelligent Resource Management in Cloud Computing and Networking CFP

Aim and Scope:

Cloud computing, as well as cloud-inspired business models, enables on-demand access to a shared pool of resources, namely computing, storage, networks, services, and applications. With the advent of cloud-based systems, cloud operators have been aiming at reliable, secured, privacy-preserving and cost-efficient cloud design and management. As the cloud infrastructure aims at offering various IT resources as services, requirements of cloud applications vary based on the resources which are requested as services. Thus, the resources may refer to heavy computation resources, massive storage resources, and high-capacity network resources and so on. The heterogeneity of cloud applications leads to the challenge of holistic design of a robust cloud system which can oversee and handle the diverse needs of numerous types of applications. On the other hand, these challenges enforce cooperation of various players in the cloud system, each of which focuses on a different segment such as computing, network, applications, and systems.

Regarding the above challenges, the recent success of machine learning in different domains imply the possibility of introducing the machine learning technologies into the cloud resource management. For example, instead of traditional model-based optimizaiton, it is possible to apply reinforcement learning to enable data-driven intelligent resource allocation and management. On the other hand, the machine learning technologies themselves introduce new resource demand characteristics. As a result, the cloud and networking resource provision shall be customized according to the machine learning requirements and characteristics.

Important Dates: Submission deadline: March 31, 2019 Author Notification: May 31, 2019 Final Manuscript: June 30, 2019 Publication: Q4 2019