面向异构DHT存储的数据与位置解耦算法

分布式哈希表(distributed hash table, DHT)由于其高效的数据寻址方式而被广泛应用于分布式存储.传统DHT必须将数据存放在指定节点中才能实现高效的数据分布式寻址,极大地限制了DHT技术的应用范围.例如,在异构存储网络中,节点的存储空间、带宽、稳定性等均有较大差异,结合数据特征和节点性能差异选择合适的数据存放节点可以很大程度上提高数据的访问效率,而传统DHT数据和存储位置紧耦合的特征导致其难以应用于异构的存储网络中.针对此问题,提出了vRoute算法以实现DHT中数据标识与其存储位置的解耦.通过构建基于Bloom Filter的分布式数据索引, vRoute算法可以在不降低数据寻址效率的基础上允许数据存储在网络中的任意节点.通过扩展Kademlia算法实现了vRoute,并从理论上证明了vRoute算法的有有效性.最后,模拟实验表明vRoute以较低的存储、网络开销实现了和传统的DHT算法接近的数据寻址效率.

Algorithm to Decouple Data from Their Location in DHT-based Heterogeneous P2P Storage

Distributed hash table (DHT) is widely used in distributed storage because of its efficient data addressing. Nevertheless, traditional DHT-based storage has to store data in specified nodes to achieve efficient data addressing, which restricts the application scope of the DHT technology severely. Taking heterogeneous storage networks for example, the storage space, bandwidth, and stability of nodes vary greatly. Choosing appropriate data storage nodes according to data features and the performance differences among the nodes can greatly improve the data access efficiency. However, the tight coupling between data and storage location disqualifies the traditional DHT-based storage from being applied to heterogeneous storage networks. Therefore, this study proposes a vRoute algorithm to decouple the data identifier from storage location in DHT-based storage. By building a distributed data index based on Bloom Filter, the vRoute algorithm allows data to be stored in any node of the network without reducing the efficiency of data addressing. It is implemented by extending the Kademlia algorithm, and its validity is verified theoretically. Finally, the simulation experiments show that vRoute achieves a data addressing efficiency close to that of the traditional DHT algorithm with low storage and network overhead.