A typical enterprise uses a local area network of computers to perform its business. During the off-working hours, the computational capacities of these networked computers are underused or unused. In order to utilize this computational capacity an application has to be recoded to exploit concurrency inherent in a computation which is clearly not possible for legacy applications without any source code. This thesis presents the design an implementation of a distributed middleware which can automatically execute a legacy application on multiple networked computers by parallelizing it. This middleware runs multiple copies of the binary executable code in parallel on different hosts in the network. It wraps up the binary executable code of the legacy application in order to capture the kernel level data access system calls and perform them distributively over multiple computers in a safe and conflict free manner. The middleware also incorporates a dynamic scheduling technique to execute the target application in minimum time by scavenging the available CPU cycles of the hosts in the network. This dynamic scheduling also supports the CPU availability of the hosts to change over time and properly reschedule the replicas performing the computation to minimize the execution time. A prototype implementation of this middleware has been developed as a proof of concept of the design. This implementation has been evaluated with a few typical case studies and the test results confirm that the middleware works as expected.