Edge computing is a key paradigm to offload thecore network and effectively process massive Internet of Things(IoT) raw data without sending them to the cloud. This paradigmnormally relies on a set of purpose-built and pre-planned servers,which host storage and processing resources to provide IoTservices close to the data sources, thus saving core networkresources and offloading the remote cloud infrastructure.In this paper, we propose to turn the network edge into adynamic, distributed computing environment that supports theprovisioning of IoT services, by exploiting the recent evolution ofNamed Data Networking (NDN), supporting both name-baseddata retrieval and computation. Specific name structure andnovel NDN forwarding mechanisms are designed; a distributedstrategy is also engineered to select the service executor amongedge nodes, with the objectives to (i) limit the raw IoT datatraffic crossing the network, and (ii) allocate the service executionaccording to the nodes’ available processing resources.Numerical analysis shows that the performance of the proposedframework approaches the one of the optimal solution of aformulated Integer Linear Programming problem. System-levelndnSIM simulations confirm that the proposal also outperformsthe considered state-of-the-art benchmark solutions in terms ofservice provisioning time.
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