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.

In vitro characterisation and expansion of human regulatory T cells for their in vivo application in the induction of tolerance in haematopoietic stem cell and solid organ transplantation

Solid organ transplantation (SOT) is considered the treatment of choice for many end-stage organ diseases. Thus far, short term results are excellent, with patient survival rates greater than 90% one year post-surgery, but there are several problems with the long term acceptance and use of immunosuppressive drugs. Hematopoietic Stem Cells Transplantation (HSCT) concerns the infusion of haematopoietic stem cells to re-establish acquired and congenital disorders of the hematopoietic system. The main side effect is the Graft versus Host Disease (GvHD) where donor T cells can cause pathology involving the damage of host tissues. Patients undergoing acute or chronic GvHD receive immunosuppressive regimen that is responsible for several side effects. The use of immunosuppressive drugs in the setting of SOT and GvHD has markedly reduced the incidence of acute rejection and the tissue damage in GvHD however, the numerous adverse side effects observed boost the development of alternative strategies to improve the long-term outcome. To this effect, the use of CD4+CD25+FOXP3+ regulatory T cells (Treg) as a cellular therapy is an attractive approach for autoimmunity disease, GvHD and limiting immune responses to allograft after transplantation. Treg have a pivotal role in maintaining peripheral immunological tolerance, by preventing autoimmunity and chronic inflammation. Results of my thesis provide the characterization and cell processing of Tregs from healthy controls and patients in waiting list for liver transplantation, followed by the development of an efficient expansion-protocol and the investigation of the impact of the main immunosuppressive drugs on viability, proliferative capacity and function of expanded cells after expansion. The conclusion is that ex vivo expansion is necessary to infuse a high Treg dose and although many other factors in vivo can contribute to the success of Treg therapy, the infusion of Tregs during the administration of the highest dose of immunosuppressants should be carefully considered.