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A Novel Cyberinfrastructure for Scientific Computation Based on the P2P Grid

Author: XiaYingJie
Tutor: ZhengYao
School: Zhejiang University
Course: Computer Science and Technology
Keywords: grid computing peer-to-peer computing P2P grid campus grid SW-R2P Bayesian trust network load balance model collaborative application framework
CLC: TP393.02
Type: PhD thesis
Year: 2009
Downloads: 149
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Grid and Peer-to-Peer (P2P) are two state-of-the-art research spots in the area of distributed computing, and they are capable of providing cyberinfrastructures for various applications in high performance computing. Grid technology utilizes the network to integrate geographically distributed resources, supporting the scientific research and engineering applications by large computing cycles. However, the grid network harnesses the nodes over-tightly, which leads to a lower system scalability. In contrast, each peer in P2P network has an equal position, joining and leaving freely, therefore P2P has a much higher scalability and robustness. However, it has less security strategy, which causes to be fragile to malicious attacks.This dissertation specifies a P2P grid model, which integrates the grid technology with P2P network to utilize both their advantages and to avoid their disadvantages. This combined model can be used to implement a low-cost, efficient, stable and secure cyberinfrastructure. The dissertation also introduces how to implement the specified P2P network and grid model to construct this P2P grid architecture, how to optimize the P2P grid to implement the load balance, and how to apply the architecture into the scientific computation and collaborative applications. Through multiple test cases for parallel computing and simulation experiments, the P2P grid cyberinfrastructure is explicitly proved to be more excellent than the traditional P2P, grid and their related applications, in terms of computing performance, security, scalability and robustness. The main creative contributions of the whole research work are listed as follows.(1) The campus grid is constructed by using the hierarchical combination of the middleware GT and SGE, which can make use of both their advantages. GT facilitates the resource transfer and computing tasks between the grid nodes efficiently, while SGE schedules the tasks dynamically based on the node loads. This novel architecture is much excellent in terms of computing performance and security.(2) Stemming from the P2P network with role and reputation based access control policies, we propose a SW-R2P model, which utilizes the zero knowledge interactive proof and Bayesian trust model to construct a trusted small world overlay P2P network. As we know, SW-R2P is the first work to synthesize the Bayesian trust evaluation and small world P2P network topology. This architecture not only keeps the whole network trustability and security, but also uses the topology to improve the resources locating.(3) The P2P grid architecture is implemented based on the SW-R2P network. It inherits the security and stableness of grid, and scalability and flexibility of P2P, to provide a novel cyberinfrastructure for scientific computation. The P2P grid uses the P2P network to group all the peers, and deploys the grid middleware on some of them to construct the upper grid layer. This hierarchical cyberinfrastructure makes full use of the advantages of both network models.(4) The load balance model for the P2P grid can be implemented by adding some kinds of load measurements in the Bayesian trust network. It uses the interactions history to probably predict the load of the candidate peers, therefore affecting the server peers selection. This model facilitates to make full use of P2P grid resources, which keeps the services robust and the whole network stable. This model is an optimization strategy for the P2P grid.Moreover, by using the proposed P2P grid, we are able to improve the traditional campus grid architecture and implement a new collaborative application framework. The experiments show that the P2P grid is capable of significantly improving the performance of the scientific computation in the campus grid and the efficiency of the collaborative applications, and further imply that the architecture has much practicability.

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