Research On Search Strategy And Trust Mechanism For P2P Networks

A new generation architectures of computer network continues to burgeoning. As a key development in the P2P network architecture, its related technologies are current hotspot. In essence, P2P is an overlay network from the perspective of logical sense. P2P stressed the idea of Peer-to-Peer Computing. In P2P, nodes are equal in status, their rights and obligations are of the same. Each node can access resources, while they also need to provide resources. They are also involved into the network management. To ensure the autonomy of nodes, P2P allows nodes to dynamically join the network, or exit from the network.As P2P which basis is Internet, has a distributed structure, it makes that the resources are not organized. In order to retrieve the necessary resources, nodes must broadcast their requests. Because of using the flooding, it may finally find the resources, but a waste of bandwidth happens. If we can construct a reasonable overlay network, and minimize the routing hops in the network with a distributed architecture, we can quickly reach the target node. Thus, it can improve the search efficiency. Since nodes have the nature of anonymity and autonomy, which led to the fact that the pursuit of the node is to maximize their own interests. In the network, it generated some free-rider phenomenon. Therefore, service becomes unreliable, and even in some cases it may appear the behavior of malicious attacks. Our plan is to establish a reasonable mechanism for the trust, in order to ensure the credibility and security of data. Trust data, they need to be stored in non-fixed and non-stable nodes. The dynamic nature of P2P leads to the fact that the data likely to be lost, or it’s too costly to maintain. For the trust data, we build a reasonable management mechanism in order to effectively preserve the trust data, and effectively manage them, so that it can maintain the dynamic nature of the network and enhance the performance of the system. To this end, we focus on the search strategies and the trust mechanisms, because of their theoretical and practical value.In this thesis, we started our research work on several aspects mentioned earlier.Existing retrieval systems can not fully support the resource organization, the Resource Location is inefficient. This thesis presents a four-layer overlay network structure, we call it "POTM", which consists of the physical network layer, the overlay network layer, trust layer, and management layer of the trust data. This thesis proposes a protocol of data search and resource location, which based on polar coordinates. The multi-dimensional space of CAN protocol is re-mapped to another polar coordinate space. We combines Resource space model with the unified organization of distributed data resources, thus it constitutes an overlay network layer. In this thesis, we use the power series algorithm which extended the subspace, thus we greatly reduces the logical routing hops, and improve the efficiency of data search.Based on evidence theory, we model the trust mechanism. It can integrate multi-information, but can not effectively aggregate conflict. This thesis proposes a new rule of evidence combination, we call it "NECR". We introduce the weight coefficient, and deal with the conflict of evidence, in order to improve the reliability and reasonable of evidence combination. Based on NECR rule, we have created a new trust model. By comparing the degree of support for the proposition of proportion vector, we can get a more accurate and flexible calculation for the trust data, and improve the credibility of the data.The theory of Subjective logic descripts and measures the trust relation from the two views of real space and concept space. However, it did not take into account of impact of time and the negative events for the nodes’trust value, and it also can not eliminate the impact of malicious behavior. This thesis presents a trust model based on subjective logic, we call it NTMBSL. We introduce the forgetting factor and the risk factors, in order to calculate the trust value. The nodes are divided into groups by function. We extend the trust relationship between nodes to the group. Multiple relationships between nodes can increase the confidence in the accuracy of measurement, effectively identify the malicious node, and it prevents cheating collaboration between nodes to improve overall security.We propose a trust model for data management, which manage data by group, so it can complete the integrated management of trust value. We design the corresponding algorithm, it selects the master node, secondary node, and exchange messages within the group or groups, and it provides the nodes’behavior of join and leave. The algorithm can solve the bottleneck problem to some extent, balance the load and reduce network traffic, and improve overall system availability.