International Workshop on Autonomic Systems for Big Data Analytics (ASBDA 2017)
September 18-22, 2017, Tucson, AZ, USA

In the Big Data ecosystem, the velocity and volume at which data arrive for processing represent two challenging issues to be addressed in the design of systems, frameworks and applications. These challenges are exacerbated by increasingly demanding Quality of Service requirements that must be met despite workload variability or changes occurring in the execution environment, which might leverage on multi-clouds or edge computing resources. Due to the presence of multiple layers that compose a data analytics platform, the variable resource requirements across the layers and the intrinsic complexity of each layer, human-assisted control or manual configuration is unrealistic. Autonomic systems enable to rule the complexity of managing data analytics platforms and integrate monitoring, planning, and execution capabilities so to satisfy some utility goal (e.g., maximize performance, reduce power wastage, guarantee reliable processing). The variety and complexity of Big Data systems, that include data centers and cloud managers, distributed storage systems, frameworks for batch, micro-batch and data stream processing, demand for specific autonomic solutions to address the multiple facets and foster novel interdisciplinary approaches. This workshop intends to promote a community-wide discussion to identify and find suitable solutions that enable autonomic features in systems, frameworks, and applications for Big Data analytics.

Papers primarily based on (but not limited to) the following topics are welcome: (Topics include but not limited to)