| 摘要(英) |
As the evolution of the Internet continues, it is possible to share and integrate resources of computers in several different ways. The Internet aggregates all computers over the world as a whole and creates numerous groups of computers with great computing power. People can use them to solve many complicated problems which were considered too hard to be solved. However, those powerful computing resources are usually dynamic. There are often new arrivals and departures of computing nodes and constant changes of the computing resources on the hosts in the network. As a result, a P2P dynamic reconfiguration approach is more appropriate on such a system to achieve load balancing. Thus we can maximize the utilization of the resources in a self-adaptive manner.
In this thesis, we propose a P2P, runtime reconfiguration model to judge whether or not a computing entity should migrate to improve overall performance on a given distributed computing environment. In addition to computation-intensive applications, the model also considers data-intensive applications which usually spend much time on I/O transmission. We also introduce the concept of “debt” to prevent a computing entity from frequent, unnecessary migrations which usually result from wrong migration decisions on an unstable computing environment. Our model is extensible: it is possible to add new types of resources as new model parameters because of the symmetry of the model parameters.
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| 參考文獻 |
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