Data Discovery Mechanism for a Large Peer-to-Peer Based Scientific Data Grid Environment

Abstract

AbstractData Grid mostly deals with large computational problems and provide geographically distributed resources for large-scale data-intensive applications that generate large data sets. In a modern scientific computing communities, the scientists involves in managing massive amounts of a very large data collections in a geographically distributed environment. Research in the area of grid computing has given us various ideas and solutions to address these requirements. Recently, most of research groups working on the data distribution problems in Data Grids and they are investigating a number of data replication approaches on the data distribution. This leads to a new problem in discovery and access to data in Data Grids environment. Peer-to-peer networks also have become a major research topic over the last few years. In distributed peer-to-peer system, a discovery mechanism is required to locate specific information, applications, or users contained within the system. In this research work, we present our scientific data grid as a large peer-to-peer based distributed system model. By using this model, we study various discovery mechanisms based on peer-to-peer architecture and investigate these mechanisms for our Dynamic Scientific Data Grids Environment Model through our Grid Simulator. In this paper, we illustrate our model and our Grid Simulator. We then analyze the performance of the discovery mechanisms relative to their success rates and bandwidth consumption.KeywordsLarge Hadron ColliderData GridReplication StrategyDiscovery MechanismBandwidth ConsumptionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.