4 research outputs found

    A framework for cascading payment and content exchange within P2P systems

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    Advances in computing technology and the proliferation of broadband in the home have opened up the Internet to wider use. People like the idea of easy access to information at their fingertips, via their personal networked devices. This has been established by the increased popularity of Peer-to-Peer (P2P) file-sharing networks. P2P is a viable and cost effective model for content distribution. Content producers require modest resources by today's standards to act as distributors of their content and P2P technology can assist in further reducing this cost, thus enabling the development of new business models for content distribution to realise market and user needs. However, many other consequences and challenges are introduced; more notably, the issues of copyright violation, free-riding, the lack of participation incentives and the difficulties associated with the provision of payment services within a decentralised heterogeneous and ad hoc environment. Further issues directly relevant to content exchange also arise such as transaction atomicity, non-repudiation and data persistence. We have developed a framework to address these challenges. The novel Cascading Payment Content Exchange (CasPaCE) framework was designed and developed to incorporate the use of cascading payments to overcome the problem of copyright violation and prevent free-riding in P2P file-sharing networks. By incorporating the use of unique identification, copyright mobility and fair compensation for both producers and distributors in the content distribution value chain, the cascading payments model empowers content producers and enables the creation of new business models. The system allows users to manage their content distribution as well as purchasing activities by mobilising payments and automatically gathering royalties on behalf of the producer. The methodology used to conduct this research involved the use of advances in service-oriented architecture development as well as the use of object-oriented analysis and design techniques. These assisted in the development of an open and flexible framework which facilitates equitable digital content exchange without detracting from the advantages of the P2P domain. A prototype of the CasPaCE framework (developed in Java) demonstrates how peer devices can be connected to form a content exchange environment where both producers and distributors benefit from participating in the system. This prototype was successfully evaluated within the bounds of an E-learning Content Exchange (EIConE) case study, which allows students within a large UK university to exchange digital content for compensation enabling the better use of redundant resources in the university

    Distributed Distance Measurement for Large-Scale Networks

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    There is an increasing trend in the Internet that a set of replicated providers are qualified for a service or resource request from a client. In this case, it is advantageous to select the best provider considering some distance measures, such as hop count or path latency. In this paper, we present a Group-based Distance Measurement Service (GDMS), which estimates and disseminates distance information of node-pairs in large-scale wide area networks. GDMS is fully distributed and does not rely on any centralized servers; thus is particularly suitable for the rapidly popularized peer-to-peer applications. The key concept in GDMS is Measurement Groups (MGroups). Nodes are self-organized into MGroups to form a hierarchical structure. A set of algorithms are proposed to handle network dynamics and optimize the group organization to reduce system costs as well as improve estimation accuracy. Moreover, a novel multicast-based algorithm is used for both intra- and inter-group performance measurements. Performance evaluation over different network topologies shows that GDMS is scalable and provides effective distance information to upper-layer applications at a relatively low cost

    Distributed distance measurement for large-scale networks

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