Traditional disk-oriented storage systems can no longer meet the high requirements of applications in latency and bandwidth, for which RAMCloud [4], was proposed to replace the disk with RAM. We consider using the memory of endusers in existing Internet to achieve a similar memory storage system. However the end-users' behavior are not as controllable as the servers in data center, which would lead to a high data loss rate. So how to ensure the data's reliability is the biggest challenge. To improve the reliability, as well as the resource utilization, we present a thought of Contributor scoring, establishing a scoring model according to Contributors' behavior. This model will classify Contributors into certain levels. Moreover, we train the Model with genetic algorithms. Experimental results show that the optimized model can effectively divide the Contributor, ensure certain reliability.It has great significance to this user memory storage system for improving the reliability and resource utilization.
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