Terminal devices (TDs) connect to networks through access points (APs) integrated into the edge server. This provides a prerequisite for TDs to upload tasks to cloud data centers or offload them to edge servers for execution. In this process, signal coverage, data transmission, and task execution consume energy, and the energy consumption of signal coverage increases sharply as the radius increases. Lower power leads to less energy consumption in a given time segment. Thus, power control for APs is essential for reducing energy consumption. Our objective is to determine the power assignment for each AP with same capacity constraints such that all TDs are covered, and the total power is minimized. We define this problem as a \emph{minimum power capacitated cover } (MPCC) problem and present a \emph{minimum local ratio} (MLR) power control approach for this problem to obtain accurate results in polynomial time. Power assignments are chosen in a sequence of rounds. In each round, we choose the power assignment that minimizes the ratio of its power to the number of currently uncovered TDs it contains. In the event of a tie, we pick an arbitrary power assignment that achieves the minimum ratio. We continue choosing power assignments until all TDs are covered. Finally, various experiments verify that this method can outperform another greedy-based way.
翻译:通过接入点连接网络的终端设备(TDs) 通过连接连接连接网络的接入点(APs) 融入边缘服务器。 这为TDs上传任务到云中数据中心或将其卸载到边缘服务器以供执行提供了一个先决条件。 在此过程中, 信号覆盖、 数据传输和任务执行消耗能源, 以及信号覆盖的能量消耗随着半径的增加而急剧增加。 电力减少导致特定时间段的能源消耗减少。 因此, APs的电力控制是减少能源消耗的关键。 我们的目标是确定每个APs的电力分配, 其能力限制与所有TDs所覆盖的相同, 其总电能限制最小化。 我们将此问题定义为 \ emph{ 最小电源增强的覆盖 } (MPCC) (MPCC) 问题, 并呈现出一个 emph{ minimum 本地比率 (MLRR) 的能量控制方法, 从而在某个时间段里获得准确的结果。 电力分配是按轮排列的顺序来选择的。 我们选择的电力分配, 最大限度地缩小其与目前所暴露的TD 。 我们选择的电量比例, 最后选择一种任意选择一种方法, 我们选择一种方法, 直至最后选择一种可以实现最起码的方法。