基于MAS的动态协作任务求解模型与算法

为提高动态网格资源的利用率，提出了基于多智能体系统博弈协作的任务动态分配和协作求解模型，建立了网格资源调度模型和任务求解算法，证明了资源分配博弈中Nash均衡点的存在性、唯一性和Nash均衡解。该方法能够利用用户智能体的学习和行为能力，使得用户的资源申请和任务调度具有较高的合理性和有效性。进行了供求关系中竞价博弈的模型试验。实验结果表明，资源调度算法不但可以有效减少延迟,而且在响应时间的平滑性、吞吐率及资源利用率方面比类似方法要好。使得整个网格系统供需合理、负载均匀。

Dynamic collaboration tasks based on MAS model and algorithm for solving

Dynamic grid resources scheduling which aims at improving resource utilization and grid application performance is a key concern in grid. Currently, much research can be found about grid scheduling and some algorithms on it were proposed. However, since grid resources are autonomic, distributed and their status change over time, those scheduling algorithms did not fit for the cases well. With MAS(Multi Agent System) coordinated technology and market bidding game rules, a grid resource allocation model based on market economy was introduced, which could show the relation between supply and demand. The model could make full use of the computing and negotiating power of the consumer and could fully consider the consumer behavior. It made the resource application and assignment of the consumer reach the higher rationality and effectiveness. In the meantime the utility function of the consumer was given; the entity and the uniqueness of Nash equilibrium in the resource allocation game and the Nash equilibrium solution were discussed. A grid resource allocation algorithm was designed based on the distilled resource allocation model. Experimental results demonstrate that this approach diminishes latency,contributes to the overall grid load balancing,and significantly improves resource utilization and the response time of tasks, which enables the allocation of the whole grid resource to be more reasonable.