Access-Efficient QoS-Aware Data Replication to Maximize User Satisfaction in Cloud Computing Environments

Abstract

Cloud computing infrastructures capable of providing scalable storage and computing resources can efficiently be used for big data storage and processing. There are growing trends in developing data-intensive (big data) applications in this computing environment that need to access massive datasets. Hence, effective data management such as data availability and efficient accesses has become critical requirements in these applications. This can be achieved by using data replication, which offers reduced data access latency, higher data availability and improved system load balancing. Moreover, different applications may have different quality-of-service (QoS) requirements. To continuously support the QoS requirement of an application, we propose a highly distributed QoS-aware replication technique that computes the optimal data center locations for the replicas so that the overall replication cost is minimized. Further, the replication strategy aims at maximizing QoS satisfaction to improve data availability and reduce access latency. The problem is formulated using dynamic programming. Finally, simulation experiments are performed using widely observed data access patterns to demonstrate the effectiveness of the proposed technique.