In Body Area Networks (BANs), how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered ...
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In Body Area Networks (BANs), how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered by renewable energy, in which the sensors carried by patient with energy harvesting module can transmit data to a personal device. We do not require any a priori knowledge of the stochastic nature of energy harvesting and energy consumption. We formulate a user utility optimization problem. We use Lyapunov Optimization techniques to decompose the problem into three sub-problems, i.e., battery management, collecting rate control and transmission power allocation. We propose an online resource allocation algorithm to achieve two major goals: (1) balancing sensors' energy harvesting and energy consumption while stabilizing the BANs system;and (2) maximizing the user utility. Performance analysis addresses required battery capacity, bounded data queue length and optimality of the proposed algorithm. Simulation results verify the optimization of algorithm.
Energy harvesting (EH) aided Internet of Things (IoT) network is a promising paradigm to librate IoT network from energy deficiency. Dynamic energy and traffic scheduling in such a scenario is challenging due to tempo...
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Energy harvesting (EH) aided Internet of Things (IoT) network is a promising paradigm to librate IoT network from energy deficiency. Dynamic energy and traffic scheduling in such a scenario is challenging due to temporal correlation of energy constraints and delay requirements of IoT applications. In this paper, joint energy management and sampling rate control to explore the tradeoff between network utility and delay performance are studied while maintaining the energy causality constraint. Taking into account the dynamic characteristics of EH process, channel fading and traffic arrivals, a stochastic optimisation problem is formulated to maximise the network utility. Leveraging the Lyapunov optimisation approach, combined with the idea of weight perturbation, a framework is proposed to decompose the stochastic problem into several deterministic sub-problems that can be solved separately. Based on the framework, an online resource allocation algorithm is developed to achieve two major goals: first, balancing energy consumption and energy harvesting to stabilise their data and energy queues;second, deriving the utility-delay tradeoff by adjusting the control parameter. The stability of data buffer and energy buffer in the proposed network is theoretical verified with performance analysis.
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