Challenges and Research Directions in Big Data-driven Cloud Adaptivity

Andreas Tsagkaropoulos, Nikos Papageorgiou, Dimitris Apostolou, Yiannis Verginadis, Gregoris Mentzas
The 9th International Conference on Cloud Computing and Services Science, CLOSER 2019, March 19-21, Portugal


    Mainstream cloud technologies are challenged by real-time, big data processing requirements or emerging applications. This paper surveys recent research efforts on advancing cloud computing virtual infrastructures and real-time big data technologies in order to provide dynamically scalable and distributed architectures over federated clouds. We examine new methods for developing cloud systems operating in a real-time, big data environment that can sense the context of the application environment and can adapt the infrastructure accordingly. We describe research topics linked to the challenge of adaptivity such as situation awareness, context detection, service-level objectives, and the capability to predict extraordinary situations requiring remedying action. We also describe research directions for realising adaptivity in cloud computing and we present a conceptual framework that represents research directions and shows interrelations.

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