In this paper, an ultra-dense mobile edge network is studied, where base stations (BSs) are equipped with computation resources to execute users' offloaded tasks. Although an ultradense BS deployment provides seamless coverage and reduced computation latency of the offloaded tasks, the cost of network power consumption is increased. We formulate an optimization problem to jointly optimize active BSs set, uplink and downlink beamforming vector selection, and computation resource allocation in order to tackle the power consumption and latency tradeoff. To efficiently solve this problem, we propose a sequential solution framework. Specifically, we first select the active BSs based on communication and computation power-aware selection rule. The computation resources and dual-link beamformers are subsequently optimized for the satisfaction of task computation deadline, network energy savings and improved coverage. Simulation results show that the proposed joint optimization framework significantly reduces the network power consumption.