With the development of the Internet of Things (IoT) technology, a vast amount of the\nIoT data is generated by mobile applications from mobile devices. Cloudlets provide a paradigm\nthat allows the mobile applications and the generated IoT data to be offloaded from the mobile\ndevices to the cloudlets for processing and storage through the access points (APs) in theWireless\nMetropolitan Area Networks (WMANs). Since most of the IoT data is relevant to personal privacy,\nit is necessary to pay attention to data transmission security. However, it is still a challenge to realize\nthe goal of optimizing the data transmission time, energy consumption and resource utilization with\nthe privacy preservation considered for the cloudlet-enabled WMAN. In this paper, an IoT-oriented\noffloading method, named IOM, with privacy preservation is proposed to solve this problem.\nThe task-offloading strategy with privacy preservation in WMANs is analyzed and modeled as\na constrained multi-objective optimization problem. Then, the Dijkstra algorithm is employed to\nevaluate the shortest path between APs in WMANs, and the nondominated sorting differential\nevolution algorithm (NSDE) is adopted to optimize the proposed multi-objective problem. Finally,\nthe experimental results demonstrate that the proposed method is both effective and efficient.
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