Abstract
Abstract This paper presents a data processing framework for enabling MapReduce approach to be available in pervasive networks, including sensor networks and Internet of Things (IoT). It is unique among other existing MapReduce-based approaches, because it can locally process data maintained on nodes in pervasive networks. It dynamically deploys programs for data processing at the nodes that have 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 paper proposes the architecture of the framework and describes its basic performance and application.
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