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所属单位：计算机科学与技术学院/人工智能学院/软件学院
发表刊物：IEEE Glob. Commun. Conf., GLOBECOM - Proc.
摘要：Efficient resource allocation which aims to maximize the network utility under energy neural operation is well known as a key issue in energy harvesting wireless sensor networks (EHWSNs). However, as the energy resource is unstable in practical systems, it's challenging to tackle the uncertainty in harvested energy profile. Instead of designing sophisticated harvested energy prediction model, we directly make uncertainty involved in the resource allocation design. Considering the uncertainty of harvested energy profile, a flexible network utility optimization approach is proposed that can achieve high network utility and robustness against uncertain harvested energy. We firstly formulate the network utility maximization problem subject to energy constraints involving uncertainty. We then introduce a flexible uncertainty model to describe the harvested energy and transform the network utility maximization with uncertainties into a traditional optimization problem. Our experimental results demonstrate the proposed approach is able to provide flexible energy allocation and achieve robustness. © 2018 IEEE.
是否译文：否
发表时间：2018-01-01
合写作者：F70206470,庄毅,Zhang, Baoxian
通讯作者：郝洁