Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Il conflitto fra trasparenza sui mercati finanziari ed esigenza di riservatezza della società

The thesis main topic is the conflict between disclosure in financial markets and the need for confidentiality of the firm. After a recognition of the major dynamics of information production and dissemination in the stock market, the analysis moves to the interactions between the information that a firm is tipically interested in keeping confidential, such as trade secrets or the data usually covered by patent protection, and the countervailing demand for disclosure arising from finacial markets. The analysis demonstrates that despite the seeming divergence between informational contents tipically disclosed to investors and information usually covered by intellectual property protection, the overlapping areas are nonetheless wide and the conflict between transparency in financial markets and the firm’s need for confidentiality arises frequently and sistematically. Indeed, the company’s disclosure policy is based on a continuous trade-off between the costs and the benefits related to the public dissemination of information. Such costs are mainly represented by the competitive harm caused by competitors’ access to sensitive data, while the benefits mainly refer to the lower cost of capital that the firm obtains as a consequence of more disclosure. Secrecy shields the value of costly produced information against third parties’ free riding and constitutes therefore a means to protect the firm’s incentives toward the production of new information and especially toward technological and business innovation. Excessively demanding standards of transparency in financial markets might hinder such set of incentives and thus jeopardize the dynamics of innovation production. Within Italian securities regulation, there are two sets of rules mostly relevant with respect to such an issue: the first one is the rule that mandates issuers to promptly disclose all price-sensitive information to the market on an ongoing basis; the second one is the duty to disclose in the prospectus all the information “necessary to enable investors to make an informed assessment” of the issuers’ financial and economic perspectives. Both rules impose high disclosure standards and have potentially unlimited scope. Yet, they have safe harbours aimed at protecting the issuer need for confidentiality. Despite the structural incompatibility between public dissemination of information and the firm’s need to keep certain data confidential, there are certain ways to convey information to the market while preserving at the same time the firm’s need for confidentality. Such means are insider trading and selective disclosure: both are based on mechanics whereby the process of price reaction to the new information takes place without any corresponding activity of public release of data. Therefore, they offer a solution to the conflict between disclosure and the need for confidentiality that enhances market efficiency and preserves at the same time the private set of incentives toward innovation.