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

Peer-to-peer:is deviant behavior the norm on P2P file-sharing networks?

P2P file-sharing networks such as Kazaa, eDonkey, and Limewire boast millions of users. Because of scalability concerns and legal issues, such networks are moving away from the semicentralized approach that Napster typifies toward more scalable and anonymous decentralized P2P architectures. Because they lack any central authority, these networks provide a new, interesting context for the expression of human social behavior. However, the activities of P2P community members are sometimes at odds with what real-world authorities consider acceptable. One example is the use of P2P networks to distribute illegal pornography. To gauge the form and extent of P2P-based sharing of illegal pornography, we analyzed pornography-related resource-discovery traffic in the Gnutella P2P network. We found that a small yet significant proportion of Gnutella activity relates to illegal pornography: for example, 1.6 percent of searches and 2.4 percent of responses are for this type of material. But does this imply that such activity is widespread in the file-sharing population? On the contrary, our results show that a small yet particularly active subcommunity of users searches for and distributes illegal pornography, but it isn't a behavioral norm

A framework for P2P application development

Although Peer-to-Peer (P2P) computing has become increasingly popular over recent years, there still exist only a very small number of application domains that have exploited it on a large scale. This can be attributed to a number of reasons including the rapid evolution of P2P technologies, coupled with their often-complex nature. This paper describes an implemented abstraction framework that seeks to aid developers in building P2P applications. A selection of example P2P applications that have been developed using this framework are also presented

CloudJet4BigData: Streamlining Big Data via an Accelerated Socket Interface

Big data needs to feed users with fresh processing results and cloud platforms can be used to speed up big data applications. This paper describes a new data communication protocol (CloudJet) for long distance and large volume big data accessing operations to alleviate the large latencies encountered in sharing big data resources in the clouds. It encapsulates a dynamic multi-stream/multi-path engine at the socket level, which conforms to Portable Operating System Interface (POSIX) and thereby can accelerate any POSIX-compatible applications across IP based networks. It was demonstrated that CloudJet accelerates typical big data applications such as very large database (VLDB), data mining, media streaming and office applications by up to tenfold in real-world tests

Distributed storage manager system for synchronized and scalable AV services across networks

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2011 Hindawi Publishing CorporationThis paper provides an innovative solution, namely, the distributed storage manager that opens a new path for highly interactive and personalized services. The distributed storage manager provides an enhancement to the MHP storage management functionality acting as a value added middleware distributed across the network. The distributed storage manager system provides multiple protocol support for initializing and downloading both streamed and file-based content and provides optimum control mechanisms to organize the storing and retrieval of content that are remained accessible to other multiple heterogeneous devices

MADServer: An Architecture for Opportunistic Mobile Advanced Delivery

Rapid increases in cellular data traffic demand creative alternative delivery vectors for data. Despite the conceptual attractiveness of mobile data offloading, no concrete web server architectures integrate intelligent offloading in a production-ready and easily deployable manner without relying on vast infrastructural changes to carriers’ networks. Delay-tolerant networking technology offers the means to do just this. We introduce MADServer, a novel DTN-based architecture for mobile data offloading that splits web con- tent among multiple independent delivery vectors based on user and data context. It enables intelligent data offload- ing, caching, and querying solutions which can be incorporated in a manner that still satisfies user expectations for timely delivery. At the same time, it allows for users who have poor or expensive connections to the cellular network to leverage multi-hop opportunistic routing to send and receive data. We also present a preliminary implementation of MADServer and provide real-world performance evaluations