Abstract
A MapReduce-based framework for processing data at nodes on the Internet of Things (IoT) is presented in this paper. Although MapReduce processing and its clones have been designed for high-performance server clusters, the processing itself is simple and generalized, so it should be used in non-high-performance computing environments, e.g., IoT and sensor networks. The proposed framework is unique among the other MapReduce-based processing approaches, because it can locally process the data maintained in nodes on the IoT rather than within high-performance server clusters and data centers. It deploys programs for data processing at the nodes that contain the target data as a map step and executes the programs with the local data. Finally, it aggregates the results of the programs to certain nodes as a reduce step. The architecture of the framework, its basic performance, and its application are also described here.
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