![]() To ensure authorized user access three access levels are provided: ownership, distribution rights and read rights. The framework covers the three levels of data security: authorized user access, data encryption and data validation. We evaluate SlickFlow on a prototype implementation based on Open vSwitch and demonstrate its effectiveness in a Mininet emulated scenario for fat-tree, BCube, and DCell topologies.Ī data security and validation framework of a SOA based system for management, storage, processing and visualization of data obtained from scientific experiments is proposed in this paper. Under the presence of failures along a primary path, packets can be rerouted to alternative paths by the switches themselves without involving the controller. A primary and alternative paths are compactly encoded as a sequence of segments written in packet header fields. This paper presents SlickFlow, a resilient source routing approach implemented with OpenFlow that allows fast failure recovery by combining source routing with alternative path information carried in the packet header. ![]() ![]() One major caveat of source routing is network failure events, which require informing the source node and can take at least on the order of one RTT to the controller. In this context, source routing has been proposed as a way to provide scalability, forwarding flexibility and simplicity in the data plane. The architectural split of control and data planes and the new control plane abstractions have been touted as Software-Defined Networking (SDN), where the OpenFlow protocol is one common choice for the standardized programmatic interface to data plane devices. Recent proposals on Data Center Networks (DCN) are based on centralized control and a logical network fabric following a well-controlled baseline topology. Furthermore, the evaluation of the prototype confirms the scalability with respect to different file sizes and also shows that a moderate overhead in terms of storage and processing time is required. The main contribution of this work is to show the feasibility to store arbitrary data in different Cloud services for private use and/or for file sharing. As opposed to P2P file sharing, where data and indices are stored on peers, PiCsMu uses Cloud storage systems for data storage, while maintaining a distributed index. This paper proposes PiCsMu (Platform-independent Cloud Storage System for Multiple Usage), a novel approach exploiting heterogeneous data storage of different Cloud services by building a Cloud storage overlay, which aggregates multiple Cloud storage services, provides enhanced privacy, and offers a distributed file sharing system. ![]() Although both Cloud storage service types have the data storage in common, they present heterogeneous characteristics: different interfaces, accounting and charging schemes, privacy and security levels, functionality and, among the data-specific Cloud storage services, different data type restrictions. ![]() Many Cloud services provide generic (e.g., Amazon S3 or Dropbox) or data-specific Cloud storage (e.g., Google Picasa or SoundCloud). The demonstrator use case shows how a PiCsMu user can upload, download, and share files with other PiCsMu users, especially highlighting: (a) the hybrid approach used by the PiCsMu system, showing that data is stored in CSs and the P2P network acts as a management overlay (b) the PiCsMu social capabilities, showing that PiCsMu users are able to find and share content to existing Online Social Network friends and (c) the fragmentation and data encoding, showing that both processes enable higher privacy levels since data is stored in multiple different CSs and is imperceptible to CSs' data validation. Therefore, PiCsMu (Platform-independent Cloud Storage System for Multiple-Usage) was developed to (1) aggregate multiple CSs' storage despite of the accepted data type, (2) provide enhanced privacy, and (3) enable a Peer-to-Peer (P2P) file sharing network relying on CSs' storage instead of peers' storage. CSs provides data-specific storage when it accepts to store data only represented in specific data types (e.g., Google Picasa, SoundCloud). CSs provide generic storage when it accepts to store data in any data type (e.g., Dropbox, Amazon S3). Despite of the observed Cloud Services' (CS) heterogeneity, e.g., different APIs (Application Programming Interface), different accounting and charging models, and different security and privacy levels, one common aspect is that CSs provide a large amount of storage. ![]()
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