Quality of Service (QoS)-driven resource provisioning for large-scale graph processing in cloud computing environments: Graph Processing-as-a-Service (GPaaS)

Abstract

Large-scale graph data is being generated every day through applications and services such as social networks, Internet of Things (IoT) and mobile applications. Traditional processing approaches such as MapReduce are inefficient for processing graph datasets. To overcome this limitation, several exclusive graph processing frameworks have been developed since 2010. However, despite broad accessibility of cloud computing paradigm and its useful features namely as elasticity and pay-as-you-go pricing model, most frameworks are designed for high performance computing infrastructure (HPC). There are few graph processing systems that are developed for cloud environments but similar to their other ..