An efficient distributed search solution for federated cloud

Federated cloud enables data sharing across different organizations. This paper proposes a distributed search index (DS-index) solution to provide distributed search capability in federated cloud, with the target to support multi-attribute range queries with secondary indexes. DS-index deploys a three-layer architecture with a multi-attribute index overlay, a tree-based P2P network layer, and a federated cloud layer. We present a distributed search algorithm with the three-layer architecture. In order to facilitate distributed search, we propose a dynamic mapping algorithm for DS-index to map between different layers. In addition, a Markov Chain-based cost model is defined to facilitate node selection and mapping. With the dynamic mapping algorithm and cost model, the proposed DS-index solution is more cost-effective than the traditional P2P networks as it can reduce the network cost in terms of index maintenance cost and node selection cost. The experiments demonstrate that, our DS-index solution along with its cost model can save the computation resource and reduce network bandwidth consumption by around 30% comparing to the one without cost model. It can also reduce the number of node splits/merges by around 20% comparing to the state-of-the-art solution.