Consistency Management for Big Data Applications in the Clouds

Friday, 17th January 2014, 2:30 am (PDCC Meeting Room)
Speaker: Dr. Shadi Ibrahim (INRIA, France)
Title: Consistency Management for Big Data Applications in the Clouds
 
Abstract:

With the emergence of cloud computing, many organizations have moved their data to the cloud in order to provide scalable, reliable and highly available services. To meet ever growing user needs, these services mainly rely on geographically-distributed data replication to guarantee good performance and high availability. However, with replication, consistency comes into question. Service providers in the cloud have the freedom to select the level of consistency according to the access patterns exhibited by the applications. Most optimizations efforts then concentrate on how to provide adequate trade-offs between consistency guarantees and performance.
As cloud is economical-based distributed system and the monetary cost completely relies on the service providers, in this talk we will present our work towards cost-efficient consistency management in the cloud. Specifically, we argue that monetary cost should be taken into consideration when evaluating or selecting a consistency level in the cloud. Accordingly, we define a new metric called consistency-cost efficiency. Based on this metric, we present a simple, yet efficient economical consistency model that adaptively tunes the consistency level at run-time in order to reduce the monetary cost while simultaneously maintaining a low fraction of stale reads. Experimental evaluations show the validity of the metric and demonstrate the effectiveness of the proposed consistency model.


 
Biography:

Shadi Ibrahim is a permanent Inria Research Scientist within the KerData research team. Before that, he was a postdoc researcher within the KerData research team working on scalable Big Data managements on clouds. He obtained his Ph.D. in Computer Science from Huazhong University of Science and Technology in Wuhan of China in 2011. His current research interests are in cloud computing, Big data management, Data-Intensive computing, virtualization technology, and file and storage systems. He has published several research papers in recognized Big Data and cloud computing research journals and conferences including IEEE IPDPS, IEEE Mascots, IEEE/ACM CCGrid, IEEE ICPP, IEEE SCC, IEEE Cluster, and IEEE Cloudcom.