1 research outputs found
Minimizing Age of Information with Power Constraints: Multi-user Opportunistic Scheduling in Multi-State Time-Varying Channels
This work is motivated by the need of collecting fresh data from
power-constrained sensors in the industrial Internet of Things (IIoT) network.
A recently proposed metric, the Age of Information (AoI) is adopted to measure
data freshness from the perspective of the central controller in the IIoT
network. We wonder what is the minimum average AoI the network can achieve and
how to design scheduling algorithms to approach it. To answer these questions
when the channel states of the network are Markov time-varying and scheduling
decisions are restricted to bandwidth constraint, we first decouple the
multi-sensor scheduling problem into a single-sensor constrained Markov
decision process (CMDP) through relaxation of the hard bandwidth constraint.
Next we exploit the threshold structure of the optimal policy for the decoupled
single sensor CMDP and obtain the optimum solution through linear programming
(LP). Finally, an asymptotically optimal truncated policy that can satisfy the
hard bandwidth constraint is built upon the optimal solution to each of the
decoupled single-sensor. Our investigation shows that to obtain a small AoI
performance: (1) The scheduler exploits good channels to schedule sensors
supported by limited power; (2) Sensors equipped with enough transmission power
are updated in a timely manner such that the bandwidth constraint can be
satisfied.Comment: accepted and to appear, IEEE JSAC. arXiv admin note: substantial text
overlap with arXiv:1908.0133