Data replication and update propagation in XML P2P data management systems

XML P2P data management systems are P2P systems that use XML as the underlying data format shared between peers in the network. These systems aim to bring the benefits of XML and P2P systems to the distributed data management field. However, P2P systems are known for their lack of central control and high degree of autonomy. Peers may leave the network at any time at will, increasing the risk of data loss. Despite this, most research in XML P2P systems focus on novel and efficient XML indexing and retrieval techniques. Mechanisms for ensuring data availability in XML P2P systems has received comparatively little attention. This project attempts to address this issue. We design an XML P2P data management framework to improve data availability. This framework includes mechanisms for wide-spread data replication, replica location and update propagation. It allows XML documents to be broken down into fragments. By doing so, we aim to reduce the cost of replicating data by distributing smaller XML fragments throughout the network rather than entire documents. To tackle the data replication problem, we propose a suite of selection and placement algorithms that may be interchanged to form a particular replication strategy. To support the placement of replicas anywhere in the network, we use a Fragment Location Catalogue, a global index that maintains the locations of replicas. We also propose a lazy update propagation algorithm to propagate updates to replicas. Experiments show that the data replication algorithms improve data availability in our experimental network environment. We also find that breaking XML documents into smaller pieces and replicating those instead of whole XML documents considerably reduces the replication cost, but at the price of some loss in data availability. For the update propagation tests, we find that the probability that queries return up-to-date results increases, but improvements to the algorithm are necessary to handle environments with high update rates

A Decentralized, Adaptive Replica Location Mechanism

We describe a decentralized, adaptive mechanism for replica location in wide-area distributed systems. Unlike traditional, hierarchical (e.g, DNS) and more recent (e.g., CAN, Chord, Gnutella) distributed search and indexing schemes, nodes in our location mechanism do not route queries, instead, they organize into an overlay network and distribute location information. We contend that this approach works well in environments where replica location queries are prevalent but the dynamic component of the system (e.g., node and network failures, replica add/delete operations) cannot be neglected. We argue that a replica location mechanism that combines probabilistic representations of replica location information with soft-state protocols and a flat overlay network of nodes brings important benefits: genuine decentralization, low query latency, and flexibility to introduce adaptive communication schedules. We support these claims in two ways. First, we provide a rough resource consumption evaluation: we show that, for environments similar to those encountered in large scientific data analysis projects, generated network traffic is limited and, more importantly, is comparable to the traffic generated by a request routing scheme. Second, we provide encouraging performance data from a prototype implementation. 1