Heuristic Geo Query Decomposition and Orchestration in a SOA

SOA is often used today for architectures distributing geo-processing computation tasks. These tasks usually are both data and computationally expensive. A fundamental issue is finding an automated, efficient task distribution and coordination among different services. We propose a language-based approach to this issue. First, the distributed geo-processing problem is written up as a declarative query using the Open Geospatial Consortium (OGC) Web Coverage Processing Service (WCPS) language standard. Second, translate the query is translated into a graph on which a rule-based graph decomposition algorithms generates a task distribution among a subset of the service hosts available. A heuristic cost function, preliminarily based on the data output sizes of each query operator, is used to partition the query and determine the execution hosts of sub-queries. The result is reassembled into a recursively nested query which also performs coordination of its distributed evaluation.