qBitcoin: A Peer-to-Peer Quantum Cash System

A decentralized online quantum cash system, called qBitcoin, is given. We design the system which has great benefits of quantization in the following sense. Firstly, quantum teleportation technology is used for coin transaction, which prevents from the owner of the coin keeping the original coin data even after sending the coin to another. This was a main problem in a classical circuit and a blockchain was introduced to solve this issue. In qBitcoin, the double-spending problem never happens and its security is guaranteed theoretically by virtue of quantum information theory. Making a block is time consuming and the system of qBitcoin is based on a quantum chain, instead of blocks. Therefore a payment can be completed much faster than Bitcoin. Moreover we employ quantum digital signature so that it naturally inherits properties of peer-to-peer (P2P) cash system as originally proposed in Bitcoin.Comment: 11 pages, 2 figure

Statistical selection algorithm for peer-to-peer system

Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. Loo et. al. (2002) has proposed a statistical selection algorithm with the same objective and run in multicast / broadcast environment that has been proved that it is the best among others in terms of the number of messages needed to complete the searching process. However, this algorithm has a high probability of failure. A few improvements have been done to this original algorithm. This improved algorithm is developed based on the simulation of the real multicast environment. Modifications have been added in the improved algorithm to ensure that the unique pivot that never been used before is selected every time, and to solve problem that involve rank for certain key value that occur in more than one participant. Four performance measures have been conducted for the purpose of performance analysis between original and improved algorithm. These measures include probability of failure, number of messages needed, number of rounds needed and execution time. As a result, the probability of failure for the newly improved algorithm is 3.2% while the original algorithm is 19.2% without much overhead in increasing the number of messages and number of rounds needed

Dante: A Self-Adapting Peer-to-Peer System

In this paper we introduce DANTE, an unstructured P2P system in which the topology of the underlying overlay network can be dynamically adapted to the system conditions. Such an adaption is performed by the peers in an autonomous manner. DANTE uses a simple search mechanism based on random walks that, combined with the topology adaptation, allows it to work in a very efficient way. We have evaluated how DANTE behaves in practice, showing that it adapts very well to varying system conditions

Distributed Reasoning in a Peer-to-Peer Setting: Application to the Semantic Web

In a peer-to-peer inference system, each peer can reason locally but can also solicit some of its acquaintances, which are peers sharing part of its vocabulary. In this paper, we consider peer-to-peer inference systems in which the local theory of each peer is a set of propositional clauses defined upon a local vocabulary. An important characteristic of peer-to-peer inference systems is that the global theory (the union of all peer theories) is not known (as opposed to partition-based reasoning systems). The main contribution of this paper is to provide the first consequence finding algorithm in a peer-to-peer setting: DeCA. It is anytime and computes consequences gradually from the solicited peer to peers that are more and more distant. We exhibit a sufficient condition on the acquaintance graph of the peer-to-peer inference system for guaranteeing the completeness of this algorithm. Another important contribution is to apply this general distributed reasoning setting to the setting of the Semantic Web through the Somewhere semantic peer-to-peer data management system. The last contribution of this paper is to provide an experimental analysis of the scalability of the peer-to-peer infrastructure that we propose, on large networks of 1000 peers

A Peer-to-Peer Normative System to Achieve Social Order

International audienceSocial order in distributed descentralised systems is claimed to be obtained by using social norms and social control. This paper presents a normative P2P architecture to obtain social order in multi-agent systems. We propose the use of two types of norms that coexist: rules and conventions. Rules describe the global normative constraints on autonomous agents, whilst conventions are local norms. Social control is obtained by providing a non-intrusive control infrastructure that helps the agents build reputation values based on their respect of norms. Some experiments are presented that show how communities are dynamically formed and how bad agents are socially excluded