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Title: A peer-to-peer incentives mechanism for sharing small and rare files
Author: Ackemann, T.
ISNI:       0000 0004 2729 5494
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2011
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The peer-to-peer paradigm is an important alternative to the traditional client-server model in computer networks, making up a significant share of the bandwidth used globally. In client-server scenarios there usually is an external reason of why the server provides its service to the clients. But there usually is no external incentive in peer-to-peer networks to share data. In fact there are two good reasons not to. Firstly, providing data to another node consumes bandwidth, which will always be limited and whose use may might incur a cost. Secondly, the process of making data accessible is also costly. The data needs to be obtained, its existence needs to be advertised and individuals need to decide which data to share. An incentive is required for nodes to offer their resources. We propose a generalisation of the BitTorrent incentives mechanism that improves it in two important ways. It works for a broader range of files in terms of size and popularity, enabling a simple BitTorrent-like tit-for-tat incentives mechanism for files that do not work with BitTorrent. At the same time it provides peers with an incentive to share more files. In BitTorrent, peers download pieces of the same file from each other. This is a bartering ring of length 2. Our algorithm extends this idea by allowing pieces of different files to be exchanged and by allowing longer rings with more nodes to be formed. For this, rings need to be identified in an overlay graph that consists of the nodes and potential downloads among them. But no node has knowledge of the graph other than its direct neighbours. For the incentives mechanism to work once rings have been identified, a group consensus needs to be reached to start the downloads. We propose distributed algorithms for these problems and evaluate them experimentally using a simulation. We are able to show that in some cases our incentives algorithm works better for small and rare files than BitTorrent.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available