Energy efficiency is a fundamental problem due to the fact that numerous tasks are running on mobile devices with limited resources. Mobile cloud computing (MCC) technology can offload computation-intensive tasks from mobile devices onto powerful cloud servers, which can significantly reduce the energy consumption of mobile devices and thus enhance their capabilities. In MCC, mobile devices transmit data through the wireless channel. However, since the state of the channel is dynamic, offloading at a low transmission rate will result in the serious waste of time and energy, which further degrades the quality of service (QoS). To address this problem, this paper proposes an energy-efficient and deadline-aware task offloading strategy based on the channel constraint, with the goal of minimizing the energy consumption of mobile devices while satisfying the deadlines constraints of mobile cloud workflows. Specifically, we first formulate a task offloading decision model that combines the channel state with task attributes such as the workload and the size of the data transmission to determine whether the task needs to be offloaded or not. Afterward, we apply it to a new adaptive inertia weight-based particle swarm optimization (NAIWPSO) algorithm to create our channel constraint-based strategy (CC-NAIWPSO), which can obtain a near-optimal offloading plan that can consume less energy while meeting the deadlines. The experimental results show that our proposed task offloading strategy can outperform other strategies with respect to the energy consumption of mobile devices, the execution time of mobile cloud workflows, and the running time of algorithms.INDEX TERMS Mobile cloud computing, task offloading, channel constraint, energy consumption.XIAO LIU received the master's degree in management science and engineering from the
The neutral-point (NP) potential balance control in three-level neutral-point-clamped (NPC) back-to-back converter is a research nodus. Its current strategies are the same as the strategies of a single three-level NPC converter. But the strategies do not give full play to its advantages that the neutral-point current can only flow through the connected midlines in both sides of the converter but does not flow through the DC-bus capacitors. In this paper, firstly the NP potential model based on the NP current injected is proposed. It overcomes numerous variable constraints and mutual coupling in the conventional model based on the zero-sequence voltage injected. And then on this basis, three NP-potential balance control algorithms, unilateral control, bilateral independent control, and bilateral coordinated control, are proposed according to difference requirements. All of these algorithms use the midlines rather than the DC-bus capacitors to flow the NP current as much as possible. Their control abilities are further quantitatively analyzed and compared. Finally, simulation results verify the validity and effectiveness of these algorithms.
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