Trust Estimation in Peer-to-Peer Network Using BLUE

In peer-to-peer networks, free riding is a major problem. Reputation management systems can be used to overcome this problem. Reputation estimation methods generally do not consider the uncertainties in the inputs. We propose a reputation estimation method using BLUE (Best Linear Unbiased estimator) estimator that consider uncertainties in the input variables.Comment: arXiv admin note: substantial text overlap with arXiv:1210.430

A Reputation Based Framework to Avoid Free-riding in Unstructured Peer-to-Peer network

Free riding is a major problem in peer-to-peer networks. Reputation management systems are generally proposed to overcome this problem. In this paper we have discussed a possible way of resource allocation on the basis of reputation management system i.e. probabilistic allocation based on reputation. This seems to be a better way for allocation of resources because in this case nodes that do not have very good reputation about each other, may also serve each other at least some amount of resource with finite probability. This avoids disconnect between them. Algorithms are presented for optimizing the shared capacity, reputation based probabilistic allocation that is optimal for a node, and formation of interest groups on the basis of similarity between interests of nodes

Avoiding Whitewashing in Unstructured Peer-to-Peer Resource Sharing Network

In peer-to-peer file sharing network, it is hard to distinguish between a legitimate newcomer and a whitewasher. This makes whitewashing a big problem in peer-to-peer networks. Although the problem of whitewashing can be solved using permanent identities, it may take away the right of anonymity for users. In this paper, we a have proposed a novel algorithm to avoid this problem when network uses free temporary identities. In this algorithm, the initial reputation is adjusted according to the level of whitewashing in the network

Resource allocation in Peer-to-Peer Networks: A Control-Theoretical Perspective

P2P system rely on voluntary allocation of resources by its members due to absence of any central controlling authority. This resource allocation can be viewed as classical control problem where feedback is the amount of resource received, which controls the output i.e. the amount of resources shared back to the network by the node. The motivation behind the use of control system in resource allocation is to exploit already existing tools in control theory to improve the overall allocation process and thereby solving the problem of freeriding and whitewashing in the network. At the outset, we have derived the transfer function to model the P2P system. Subsequently, through the simulation results we have shown that transfer function was able to provide optimal value of resource sharing for the peers during the normal as well as high degree of overloading in the network. Thereafter we verified the accuracy of the transfer function derived by comparing its output with the simulated P2P network. To demonstrate how control system reduces free riding it has been shown through simulations how the control systems penalizes the nodes indulging in different levels of freeriding. Our proposed control system shows considerable gain over existing state of art algorithm. This improvement is achieved through PI action of controller. Since low reputation peers usually subvert reputation system by whitewashing. We propose and substantiate a technique modifying transfer function such that systems' sluggishness becomes adaptive in such a way that it encourage genuine new comers to enter network and discourages member peers to whitewash