Age-of-Information (AoI), or simply age, which measures the data freshness, is essential for real-time Internet-of-Things (IoT) applications. On the other hand, energy saving is urgently required by many energy-constrained IoT devices. This paper studies the energy-age tradeoff for status update from a sensor to a monitor over an error-prone channel. The sensor can sleep, sense and transmit a new update, or retransmit by considering both sensing energy and transmit energy. An infinite-horizon average cost problem is formulated as a Markov decision process (MDP) with the objective of minimizing the weighted sum of average AoI and average energy consumption. By solving the associated discounted cost problem and analyzing the Markov chain under the optimal policy, we prove that there exists a threshold optimal stationary policy with only two thresholds, i.e., one threshold on the AoI at the transmitter (AoIT) and the other on the AoI at the receiver (AoIR). Moreover, the two thresholds can be efficiently found by a line search. Numerical results show the performance of the optimal policies and the tradeoff curves with different parameters. Comparisons with the conventional policies show that considering sensing energy is of significant impact on the policy design, and introducing sleep mode greatly expands the tradeoff range.
翻译:测量数据新鲜度的时代信息(AoI),或简单年龄(AoI),对于实时互联网游戏(IoT)应用至关重要。另一方面,许多受能源限制的IoT装置迫切需要节能。本文研究从传感器到易出错频道监测器更新状态的能源-年龄权衡。传感器可以睡觉、感应和传输新的更新,或者通过考虑遥感能源和传输能源再次传输。无限之平平平均成本问题被设计成一个Markov决策过程(MDP),目的是最大限度地减少平均AoI和平均能源消费的加权和总和。通过解决相关的折扣成本问题和分析最佳政策下的Markov链,我们证明存在着一种最佳的门槛固定政策,只有两个阈值,即发射机AoIT的AoI有一个阈值,接收器AoIR的AoI有一个阈值。此外,通过一条线搜索可以有效地找到两个阈值,目的是最大限度地减少平均AoI和平均能源消耗量的加权总和加权总和平均能源消耗量。通过解决相关的折扣结果,在考虑最优的贸易政策和大幅度的能源政策中进行对比时,将展示最佳贸易政策的汇率。