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• W2917483248 abstract "Edge computing is based on the philosophy that the data should be processed within the locality of its source. Edge computing is entering a new phase where it gains wide acceptance from both academia and the industry as the commercial deployments are starting. Edge of the network presents a very dynamic environment with many devices, intermittent traffic, high mobility of the end user, heterogeneous applications and their requirements. In this scene, scalable and efficient management and orchestration remains to be a problem. We focus on the workload orchestration problem in which execution locations for incoming tasks from mobile devices are decided within an edge computing infrastructure, including the global cloud as well. Workload orchestration is an intrinsically hard, online problem. We employ a fuzzy logic-based approach to solve this problem by capturing the intuition of a real-world administrator to get an automated management system. Our approach takes into consideration the properties of the offloaded task as well as the current state of the computational and networking resources. Detailed set of experiments are designed with EdgeCloudSim to demonstrate the competitive performance of our approach for different service classes." @default.
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• W2917483248 date "2019-06-01" @default.
• W2917483248 modified "2023-10-17" @default.
• W2917483248 title "Fuzzy Workload Orchestration for Edge Computing" @default.
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• W2917483248 doi "https://doi.org/10.1109/tnsm.2019.2901346" @default.
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