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Peer-to-Peer networks are gaining increasing attention from both the scientific and the large Internet user community. Popular applications utilizing this new technology offer many attractive features to a growing number of users. At the heart of such networks lies the data retrieval algorithm. Proposed methods either depend on the network-disastrous(More)
The focus of this work is the on-demand resource provisioning in cloud computing, which is commonly referredto as cloud elasticity. Although a lot of effort has been invested in developing systems and mechanisms that enable elasticity, the elasticity decision policies tend to be designed without quantifying or guaranteeing the quality of their operation. We(More)
Peer-to-Peer networks are gaining increasing attention from both the scientific and the large Internet user community. Popular applications utilizing this new technology offer many attractive features to a growing number of users. At the heart of such networks lies the data retrieval algorithm. Proposed methods either depend on the network-disastrous(More)
—The proliferation of data in RDF format calls for efficient and scalable solutions for their management. While scalability in the era of big data is a hard requirement, modern systems fail to adapt based on the complexity of the query. Current approaches do not scale well when faced with substantially complex, non-selective joins, resulting in exponential(More)
In this paper, we present a distributed architecture for indexing and serving large and diverse datasets. It incorporates and extends the functionality of Hadoop, the open source MapReduce framework, and of HBase, a distributed, sparse, NoSQL database, to create a fully parallel indexing system. Experiments with structured, semi-structured and unstructured(More)
Recently, a large number of pay-as-you-go data services are offered over cloud infrastructures. Data service providers need appropriate and flexible query charging mechanisms and query optimization that take into consideration cloud operational expenses, pricing strategies and user preferences. Yet, existing solutions are static and non-configurable. We(More)
This work presents TIRAMOLA, a cloud-enabled, open-source framework to perform automatic resizing of NoSQL clusters according to user-defined policies. Decisions on adding or removing worker VMs from a cluster are modeled as a Markov Decision Process and taken in real-time. The system automatically decides on the most advantageous cluster size according to(More)