In order to reduce makespan and storage consumption in data grids, a node selection model for replica creation is proposed. The model is based on the degree distribution of complex networks. We define two candidate re...In order to reduce makespan and storage consumption in data grids, a node selection model for replica creation is proposed. The model is based on the degree distribution of complex networks. We define two candidate replica nodes: a degree-based candidate pool and a frequency-based candidate pool, through which a degree-based candidate pool is defined in consideration of onsidering the access frequency; a candidate pool-based frequency is also defined. The data replica is copied to the node with the minimum Local cost in the two pools. Further, this paper presents and proves a replica creation theorem. A dynamic multi-replicas creation algorithm (DMRC) is also provided. Simulation results show that the proposed method may simultaneously reduce makespan and data used in space storage consumption.展开更多
基金supported by the National Natural Science Foundation of China (60973139,60773041)the Key Technologies R&D Program of China (2007BAK34B06)the Talent Foundation of Nanjing Universitiy of Posts and Telecommunications (NY208006)
文摘In order to reduce makespan and storage consumption in data grids, a node selection model for replica creation is proposed. The model is based on the degree distribution of complex networks. We define two candidate replica nodes: a degree-based candidate pool and a frequency-based candidate pool, through which a degree-based candidate pool is defined in consideration of onsidering the access frequency; a candidate pool-based frequency is also defined. The data replica is copied to the node with the minimum Local cost in the two pools. Further, this paper presents and proves a replica creation theorem. A dynamic multi-replicas creation algorithm (DMRC) is also provided. Simulation results show that the proposed method may simultaneously reduce makespan and data used in space storage consumption.