Bandwidth-Efficient Query Answering in Semantically Heterogeneous Grids

With the rapid growth of grid computing, more and more data are generated and stored across the grid. To fully utilize the data, efficient data search and query answering mechanism is becoming a very important issue. However, the heterogeneity and sheer amount of data poses issues that current technology cannot cope with efficiently. In this paper, we propose novel techniques that can greatly reduce bandwidth cost of distributed query processing while allowing efficient processing of complex queries, over large scale, fully decentralized, and semantically heterogeneous grids. We argue that appropriate overlay topology, semantic query routing path, and view-based caching are of significant importance towards this goal.