|Title||Efficient and cost-effective data-intensive computing on multi-clouds: An introduction to the MELODIC project|
|Project(s)||MELODIC: Multi-cloud Execution-ware for Large-scale Optimised Data-Intensive Computing|
|Publication Type||Talks, invited|
|Year of Publication||2017|
|Location of Talk||BioInformatics in Torun (BIT), Toruń, Poland|
Data-intensive computing, often simply referred to as big data, is one of the major current trends in ICT. In areas as diverse as social media, business intelligence, information security, Internet-of-Things, and scientific research, a tremendous amount of data is created or collected at a speed surpassing what we can handle using traditional data management techniques. Life sciences are not different. With the vast amount of biological information available, such as Omics data, unprecedented opportunities for modern research and scientific breakthroughs arise, all depending on the efficient and cost-effective data analysis. Cloud computing, characterized by the paradigm of on-demand network access to computational resources and pay-as-you-go economic model, promises great potential of providing required computational resources for data analytics in Bioinformatics. However, challenges such as lack of data privacy and data-aware cloud federation keeps cloud computing from realizing the full potential for data-intensive applications. At the same time, non-standardized cloud interfaces make it complex to migrate big data applications between platforms thus preventing cloud users from achieving optimal cost-performance ratio for their applications by encouraging vendor lock-in.