Abstract
The sheer volumes of data handled by today's Internet services demand uncompromising scalability from the persistence substrates. Such demands have been successfully addressed by highly decentralized key-value stores invariably governed by a distributed hash table. The availability of these structured overlays rests on the assumption of a moderately stable environment. However, as scale grows with unprecedented numbers of nodes the occurrence of faults and churn becomes the norm rather than the exception, precluding the adoption of rigid control over the network's organization. In this position paper we outline the major ideas of a novel architecture designed to handle today's very large scale demand and its inherent dynamism. The approach rests on the well-known reliability and scalability properties of epidemic protocols to minimize the impact of churn. We identify several challenges that such an approach implies and speculate on possible solutions to ensure data availability and adequate access performance. © 2011 IEEE.

Abstract
The current exponential growth of data calls for massive-scale capabilities of storage and processing. Such large volumes of data tend to disallow their centralized storage and processing making extensive and flexible data partitioning unavoidable. This is being acknowledged by several major Internet players embracing the Cloud computing model and offering first generation remote storage services with simple processing capabilities. In this position paper we present preliminary ideas for the architecture of a flexible, efficient and dependable fully decentralized object store able to manage very large sets of variable size objects and to coordinate in place processing. Our target are local area large computing facilities composed of tens of thousands of nodes under the same administrative domain. The system should be capable of leveraging massive replication of data to balance read scalability and fault tolerance. Copyright 2009 ACM.

Abstract

Abstract