信息约束峰值时代下的在线能量最小化

Kumar Saurav;Rahul Vaze
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引用次数: 1

摘要

我们考虑一个节点,其中以任意间隔生成固定大小(inbits)的数据包。节点需要通过传输可能生成的数据包的子集来保持监视器上的峰值信息年龄(AoI)低于阈值。在任何时候,根据数据包的可用性和当前AoI,节点可以选择传输哪个数据包,以及以什么传输速度(以每秒位数为单位)。功耗是传输速度单调递增的凸函数。在本文中,对于任何给定的时间范围,目标是找到一个在满足峰值AoI约束的情况下最小化总能耗的因果策略。我们将竞争率作为性能指标,它被定义为因果策略的预期成本与预先知道输入(数据包生成时间)的最优离线策略的预期成本之比。我们首先根据系统参数(如幂函数、数据包大小和峰值AoI阈值)推导出所有因果策略竞争率的下界,然后提出一个特定的策略,我们表明其竞争率对系统参数的依赖程度与推导出的下界相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Energy Minimization Under a Peak Age of Information Constraint
We consider a node where packets of fixed size (inbits) are generated at arbitrary intervals. The node is required to maintain the peak age of information (AoI) at the monitor below a threshold by transmitting potentially a subset of the generated packets. At any time, depending on the packet availability and the current AoI, the node can choose which packet to transmit, and at what transmission speed (in bits per second). Power consumption is a monotonically increasing convex function of the transmission speed. In this paper, for any given time horizon, the objective is to find a causal policy that minimizes the total energy consumption while satisfying the peak AoI constraint. We consider competitive ratio as the performance metric, that is defined as the ratio of the expected cost of a causal policy, and the expected cost of an optimal offline policy that knows the input (packet generation times) in advance. We first derive a lower bound on the competitive ratio of all causal policies, in terms of the system parameters (such as power function, packet size and peak AoI threshold), and then propose a particular policy for which we show that its competitive ratio has similar order of dependence on the system parameters as the derived lower bound.
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CiteScore
8.20
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