Our aim in request sequencing is to decrease network traffic amongst NetSolve client and server components in order to decrease overall request response time. Our design ensures that i) no unnecessary data is transmitted and ii) all necessary data is transferred. As briefly discussed below, we also reduce execution time by executing computational modules simultaneously when possible. All this is accomplished by performing a detailed analysis of the input and output parameters of every request in the sequence to produce a directed acyclic graph (DAG) that represents the tasks and their execution dependences. This DAG is then sent to a server in the system where it is scheduled for execution.
In order to build the DAG or task graph, we need to analyze every input and output in the sequence of requests. We evaluate two parameters as the same if they share the same reference. We use the size fields and reference pointer of the input parameters to calculate when inputs overlap in the memory space. Only matrices and vectors are checked for recurrences on the premise that these are the only objects that tend to be large enough for the overhead of the analysis to pay dividends. Through this analysis we build a DAG in which the nodes represent computational modules or NetSolve services and the arcs represent data dependencies amongst these modules. The graph is acyclic because looping control structures are not allowed within the sequence, and therefore, a node can never be its own descendant.