Abstract
In this work, we study age-optimal scheduling with stability constraints in a multiple access channel with two heterogeneous source nodes transmitting to a common destination. The first node is connected to a power grid and it has randomly arriving data packets. Another energy harvesting (EH) sensor monitors a stochastic process and sends status updates to the destination. We formulate an optimization problem that aims at minimizing the average age of information (AoI) of the EH node subject to the queue stability condition of the grid-connected node. First, we consider a Probabilistic Random Access (PRA) policy where both nodes make independent transmission decisions based on some fixed probability distributions. We show that with this policy, the average AoI is equal to the average peak AoI, if the EH node only sends freshly generated samples. In addition, we derive the optimal solution in closed form, which reveals some interesting properties of the considered system. Furthermore, we consider a Drift-Plus-Penalty (DPP) policy and develop AoI-optimal and peak-AoI-optimal scheduling algorithms using the Lyapunov optimization theory. Simulation results show that the DPP policy outperforms the PRA policy in various scenarios, especially when the destination node has low multi-packet reception capabilities.
Highlights
T HE Age of Information (AoI) is a newly emerged metric and tool to capture the timeliness and freshness of data reception [2]–[6]
2) We show that with the Probabilistic Random Access (PRA) policy, the average AoI of the energy harvesting (EH) node is equal to the average peak AoI, which is inversely proportional to the throughput of the EH node
Since our analytical results do not depend on any specific channel model, the success probabilities we use in the simulations are divided into two cases: 1) strong multipacket reception (MPR), p1/1 = 0.95, p1/1,2 = 0.63, p2/2 = 0.924, p2/1,2 = 0.41; 2) weak MPR, p1/1 = 0.924, p1/1,2 = 0.515, p2/2 = 0.882, p2/1,2 = 0.3.7 For the PRA policy, we choose ξ = 0.001
Summary
T HE Age of Information (AoI) is a newly emerged metric and tool to capture the timeliness and freshness of data reception [2]–[6]. Consider a monitored source node which generates time-stamped status updates, and transmits them through a wireless channel or through a network to a destination. Keeping the average AoI small corresponds to having fresh information, which is critical for time-sensitive applications in the Internet of Things (IoT) scenarios and future wireless systems [7], [8]. This notion has been extended to other metrics such as the value of information, cost of update delay, and non-linear AoI [9], [10]. Nodes, especially with the presence of interference in a MAC channel, is a non-trivial task
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