Big data is one of the great challenges for the future Internet of Things applications. There is a vision to network millions of devices into a comprehensive network, however, currently there are no good solutions for doing this, neither are there feasible methods for exploiting the collected data. Collecting data to servers does not offer exploitation scenarios for the huge amounts of data that can be collected using the billions of sensing devices that may be deployed once the Internet of Things vision becomes a reality. Instead of collecting data to servers, the data could be processed by the devices collecting the data, utilizing the processing results right where they are created and used. Processing fewer data items autonomously in a large number of computing nodes results in much less complexity for a single computing node when compared to a scenario where all data is collected for processing to one capable computing node. However, in case of a distributed scenario the complexity is increased in some other areas such as communication and data validation as we can't assume a synchronous system with a fixed architecture and well defined data paths. The current paper presents an architecture based on the proactive middleware ProWare and some application examples that enable the construction of systems where the computation is distributed among individual computing nodes, thus alleviating the big data problem.