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Using Unmanned aerial vehicles (UAVs) to assist mobile edge computing (MEC) network is a promising solution to provide flexible and low-latency computing service for resource limited user equipments (UEs). However, the computing resources that one UAV can provide are often limited and cannot provide computing services for massive mobile users, thus limiting the application of this technology. So, a novel multi-UAV-assisted MEC network is proposed in this paper. The optimization problem is formulated with the aim to make full use of network’s computing resources to reduce the number of failed tasks and energy consumption. To solve this challenging problem, a novel solution is proposed. First, we use a swarm intelligence algorithm to investigate the deployment of UAVs. Second, we offer an efficient matching algorithm to explore the tasks assignments under the given deployment of UAVs. The simulation results show that the proposed solution can effectively reduce the number of failed tasks and energy consumption.
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