TY - JOUR
T1 - Optimizing Information Freshness in Wireless Networks
T2 - A Stochastic Geometry Approach
AU - Yang, Howard H.
AU - Arafa, Ahmed
AU - Quek, Tony Q.S.
AU - Poor, H. Vincent
N1 - Funding Information:
This work was supported in part by the Singapore University of Technology and Design-Zhejiang University (SUTD-ZJU) Research Collaboration under Grant SUTDZJU/RES/01/2016, and in part by the SUTD-ZJU Research Collaboration under Grant SUTD-ZJU/RES/05/2016. This paper was presented in part at the IEEE Global Communication Conference [1].
Publisher Copyright:
© 2020 IEEE.
PY - 2021/6/1
Y1 - 2021/6/1
N2 - Optimization of information freshness in wireless networks has usually been performed based on queueing analysis that captures only the temporal traffic dynamics associated with the transmitters and receivers. However, the effect of interference, which is mainly dominated by the interferers' geographic locations, is not well understood. In this paper, we leverage a spatiotemporal model, which allows one to characterize the age of information (AoI) from a joint queueing-geometry perspective, for the design of a decentralized scheduling policy that exploits local observation to make transmission decisions that minimize the AoI. To quantify the performance, we also derive accurate and tractable expressions for the peak AoI. Numerical results reveal that: I) the packet arrival rate directly affects the service process due to queueing interactions, ii) the proposed scheme can adapt to traffic variations and largely reduce the peak AoI, and iii) the proposed scheme scales well as the network grows in size. This is done by adaptively adjusting the radio access probability at each transmitter to the change of the ambient environment.
AB - Optimization of information freshness in wireless networks has usually been performed based on queueing analysis that captures only the temporal traffic dynamics associated with the transmitters and receivers. However, the effect of interference, which is mainly dominated by the interferers' geographic locations, is not well understood. In this paper, we leverage a spatiotemporal model, which allows one to characterize the age of information (AoI) from a joint queueing-geometry perspective, for the design of a decentralized scheduling policy that exploits local observation to make transmission decisions that minimize the AoI. To quantify the performance, we also derive accurate and tractable expressions for the peak AoI. Numerical results reveal that: I) the packet arrival rate directly affects the service process due to queueing interactions, ii) the proposed scheme can adapt to traffic variations and largely reduce the peak AoI, and iii) the proposed scheme scales well as the network grows in size. This is done by adaptively adjusting the radio access probability at each transmitter to the change of the ambient environment.
KW - Poisson bipolar network
KW - age of information
KW - scheduling policy
KW - spatiotemporal analysis
KW - stochastic geometry
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U2 - 10.1109/TMC.2020.2977010
DO - 10.1109/TMC.2020.2977010
M3 - Article
AN - SCOPUS:85105569924
SN - 1536-1233
VL - 20
SP - 2269
EP - 2280
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 6
M1 - 9018083
ER -