Abstract

Large amounts of processing resources are required for the sensed raw big data processing during the data generation process. Furthermore, as sensed data are typically privacy sensitive, blockchain technology can be used to ensure the privacy concerns. This study examines a multiuser mobile offloading network that consists of a cloud server located remotely and an edge node. We formulate the offloading problem as the joint optimization of task offloading decision making of all users, the computation resource allocation among the edge executing applications, and the radio resource assignment among all the remote-processing applications. The goal is to minimize the maximum weighted cost of all users. When compared to other benchmark approaches, the simulation results show that the proposed algorithm achieves optimal results in terms of both energy consumption and delay as a result of collaboration. Finally the resource allocation and optimal offloading strategy with 93% efficiency is obtained.

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