We consider a single source-destination pair, where information updates arrive at the source at arbitrary time instants. For each update, its size, i.e. the service time required for complete transmission to the destination, is also arbitrary. At any time, age of information (AoI) is equal to the difference between the current time, and the arrival time of the latest update (at the source) that has been completely transmitted (to the destination). AoI quantifies the staleness of the update (information) at the destination. The goal is to find a causal scheduling policy that minimizes the time average of AoI, where the possible decisions at any time are i) whether to preempt the update under transmission upon arrival of a new update, and ii) if no update is under transmission, then choose which update to transmit (among the available updates). In this paper, we propose a causal policy called SRPT$^+$ that at each time, i) preempts the update under transmission if a new update arrives with a smaller size, and ii) if no update is under transmission, then begins to transmit the update for which the ratio of the reduction in AoI upon complete transmission (if not preempted in future) and the remaining size, is maximum. We characterize the performance of SRPT$^+$ using the metric called the competitive ratio, i.e. the ratio of the average AoI of causal policy and the average AoI of an optimal offline policy (that knows the entire input in advance), maximized over all possible inputs. We show that the competitive ratio of SRPT$^+$ is at most $4$. Further, we propose a simpler policy called SRPT$^L$, that i) preempts the update under transmission if a new update arrives with a smaller size, and ii) if no update is under transmission, then begins to transmit the update with the latest arrival time. We show that the competitive ratio of SRPT$^L$ is at most $29$.
翻译:我们考虑的是单一的源-目的地配对, 信息更新在任意的瞬间到达源- 信息更新在源- 源- 目的地的速率。 对于每次更新,其规模( 即完全传输到目的地所需的服务时间) 也是任意的。 在任何时候, 信息的年龄( AoI) 等于当前时间与已完全传输( 目的地) 最新更新( 来源) 的到达时间之间的差数。 AoI 量化了目的地更新( 信息) 的速率( 信息) 。 目标是找到一个因果列表政策, 将AoI 的平均时间( 任何时间中可能决定的美元比率) 降至最低, 是否在新更新时, 是否预先在传输时提前更新( 美元), 我们提议的是, 最高因果政策在每次更新时, i i, 如果新的更新时, 则提前更新 ; 如果更新后, 最晚更新, 则在传输前, 最晚的 i- SR 更新政策( 更新后, 我们继续更新 i- 更新) 将显示业绩 i- 最新 。