Survey of data replication in P2P systems

Large-scale distributed collaborative applications are getting common as a result of rapid progress in distributed technologies (grid, peer-to-peer, and mobile computing). Peer-to-peer (P2P) systems are particularly interesting for collaborative applications as they can scale without the need for powerful servers. In P2P systems, data storage and processing are distributed across autonomous peers, which can join and leave the network at any time. To provide high data availability in spite of such dynamic behavior, P2P systems rely on data replication. Some replication approaches assume static, read-only data (e.g. music files). Other solutions deal with updates, but they simplify replica management by assuming no update conflicts or single-master replication (i.e. only one copy of the replicated data accepts write operations). P2P advanced applications, which must deal with semantically rich data (e.g. XML documents, relational tables, etc.) using a high-level SQL-like query language, are likely to need more sophisticated capabilities such as multi-master replication (i.e. all replicas accept write operations) and update conflict resolution. These issues are addressed by optimistic replication. Optimistic replication allows asynchronous updating of replicas so that applications can progress even though some nodes are disconnected or have failed. As a result, users can collaborate asynchronously. However, concurrent updates may cause replica divergence and conflicts, which should be reconciled. In this survey, we present an overview of data replication, focusing on the optimistic approach that provides good properties for dynamic environments. We also introduce P2P systems and the replication solutions they implement. In particular, we show that current P2P systems do not provide eventual consistency among replicas in the presence of updates, apart from APPA system, a P2P data management system that we are building

Survey of data replication in P2P systems

Large-scale distributed collaborative applications are getting common as a result of rapid progress in distributed technologies (grid, peer-to-peer, and mobile computing). Peer-to-peer (P2P) systems are particularly interesting for collaborative applications as they can scale without the need for powerful servers. In P2P systems, data storage and processing are distributed across autonomous peers, which can join and leave the network at any time. To provide high data availability in spite of such dynamic behavior, P2P systems rely on data replication. Some replication approaches assume static, read-only data (e.g. music files). Other solutions deal with updates, but they simplify replica management by assuming no update conflicts or single-master replication (i.e. only one copy of the replicated data accepts write operations). P2P advanced applications, which must deal with semantically rich data (e.g. XML documents, relational tables, etc.) using a high-level SQL-like query language, are likely to need more sophisticated capabilities such as multi-master replication (i.e. all replicas accept write operations) and update conflict resolution. These issues are addressed by optimistic replication. Optimistic replication allows asynchronous updating of replicas so that applications can progress even though some nodes are disconnected or have failed. As a result, users can collaborate asynchronously. However, concurrent updates may cause replica divergence and conflicts, which should be reconciled. In this survey, we present an overview of data replication, focusing on the optimistic approach that provides good properties for dynamic environments. We also introduce P2P systems and the replication solutions they implement. In particular, we show that current P2P systems do not provide eventual consistency among replicas in the presence of updates, apart from APPA system, a P2P data management system that we are building

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Scalable XML Collaborative Editing with Undo short paper

Commutative Replicated Data-Type (CRDT) is a new class of algorithms that ensures scalable consistency of replicated data. It has been successfully applied to collaborative editing of texts without complex concurrency control. In this paper, we present a CRDT to edit XML data. Compared to existing approaches for XML collaborative editing, our approach is more scalable and handles all the XML editing aspects : elements, contents, attributes and undo. Indeed, undo is recognized as an important feature for collaborative editing that allows to overcome system complexity through error recovery or collaborative conflict resolution

A FUNCTIONAL SKETCH FOR RESOURCES MANAGEMENT IN COLLABORATIVE SYSTEMS FOR BUSINESS

This paper presents a functional design sketch for the resource management module of a highly scalable collaborative system. Small and medium enterprises require such tools in order to benefit from and develop innovative business ideas and technologies. As computing power is a modern increasing demand and no easy and cheap solutions are defined, especially small companies or emerging business projects abide a more accessible alternative. Our work targets to settle a model for how P2P architecture can be used as infrastructure for a collaborative system that delivers resource access services. We are focused on finding a workable collaborative strategy between peers so that the system offers a cheap, trustable and quality service. Thus, in this phase we are not concerned about solutions for a specific type of task to be executed by peers, but only considering CPU power as resource. This work concerns the resource management module as a part of a larger project in which we aim to build a collaborative system for businesses with important resource demandsresource management, p2p, open-systems, service oriented computing, collaborative systems