24,706 research outputs found
Taxonomy of P2P Applications
Peer-to-peer (p2p) networks have gained immense popularity in recent years and the number of services they provide continuously rises. Where p2p-networks were formerly known as file-sharing networks, p2p is now also used for services like VoIP and IPTV. With so many different p2p applications and services the need for a taxonomy framework rises. This paper describes the available p2p applications grouped by the services they provide. A taxonomy framework is proposed to classify old and recent p2p applications based on their characteristics
Sigmoid(x): secure distributed network storage
Secure data storage is a serious problem for computer users today, particularly in enterprise environments. As data requirements grow, traditional approaches of secured silos are showing their limitations. They represent a single – or at least, limited – point of failure, and require significant, and increasing, maintenance and overhead. Such solutions are totally unsuitable for consumers, who want a ‘plug and play’ secure solution for their increasing datasets – something with the ubiquity of access of Facebook or webmail. Network providers can provide centralised solutions, but that returns us to the first problem. Sigmoid(x) takes a completely different approach – a scalable, distributed, secure storage mechanism which shares data storage between the users themselves
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of
application areas and domains that this technology promises to serve.
Typically, fundamental design decisions involved in big data systems design
include choosing appropriate storage and computing infrastructures. In this age
of heterogeneous systems that integrate different technologies for optimized
solution to a specific real world problem, big data system are not an exception
to any such rule. As far as the storage aspect of any big data system is
concerned, the primary facet in this regard is a storage infrastructure and
NoSQL seems to be the right technology that fulfills its requirements. However,
every big data application has variable data characteristics and thus, the
corresponding data fits into a different data model. This paper presents
feature and use case analysis and comparison of the four main data models
namely document oriented, key value, graph and wide column. Moreover, a feature
analysis of 80 NoSQL solutions has been provided, elaborating on the criteria
and points that a developer must consider while making a possible choice.
Typically, big data storage needs to communicate with the execution engine and
other processing and visualization technologies to create a comprehensive
solution. This brings forth second facet of big data storage, big data file
formats, into picture. The second half of the research paper compares the
advantages, shortcomings and possible use cases of available big data file
formats for Hadoop, which is the foundation for most big data computing
technologies. Decentralized storage and blockchain are seen as the next
generation of big data storage and its challenges and future prospects have
also been discussed
Aiming for ultra-scalable ePortfolio distribution using peer-to-peer networks
In this paper the authors discuss how peer-to-peer technology offers a practical solution to building highly scalable Europe-wide and worldwide ePortfolio networks over existing network infrastructures.This solution also offers the effect of empowering individuals through moving the management and storage responsibilities onto the portfolio owners, decoupling users from any single institutional ePortfolio service provider The authors do not present this solution as the single way forward, but as an alternative to what is seen as a mainly client-server and Web-based approach to ePortfolio development, and to encourage developers to explore the possibilities for ePortfolio integration with emerging and relatively immature technologies. A prototype implementation is reported and future developments described
State of The Art and Hot Aspects in Cloud Data Storage Security
Along with the evolution of cloud computing and cloud storage towards matu-
rity, researchers have analyzed an increasing range of cloud computing security
aspects, data security being an important topic in this area. In this paper, we
examine the state of the art in cloud storage security through an overview of
selected peer reviewed publications. We address the question of defining cloud
storage security and its different aspects, as well as enumerate the main vec-
tors of attack on cloud storage. The reviewed papers present techniques for key
management and controlled disclosure of encrypted data in cloud storage, while
novel ideas regarding secure operations on encrypted data and methods for pro-
tection of data in fully virtualized environments provide a glimpse of the toolbox
available for securing cloud storage. Finally, new challenges such as emergent
government regulation call for solutions to problems that did not receive enough
attention in earlier stages of cloud computing, such as for example geographical
location of data. The methods presented in the papers selected for this review
represent only a small fraction of the wide research effort within cloud storage
security. Nevertheless, they serve as an indication of the diversity of problems
that are being addressed
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