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Age-Optimal Scheduling Over Hybrid Channels

Published: 09 September 2022 Publication History

Abstract

We consider the problem of minimizing the age of information when a source can transmit status updates over two heterogeneous channels. Our work is motivated by recent developments in 5 G mmWave technology, where transmissions may occur over an unreliable but fast (e.g., mmWave) channel or a slow reliable (e.g., sub-6 GHz) channel. The unreliable channel is modeled as a time-correlated Gilbert-Elliot channel at a high rate when the channel is in the “ON” state. The reliable channel provides a deterministic but lower data rate. The scheduling strategy determines the channel to be used for transmission in each time slot, aiming to minimize the time-average age of information (AoI). The optimal scheduling problem is formulated as a Markov Decision Process (MDP), which is challenging to solve because super-modularity does not hold in a part of the state space. We address this challenge and show that a multi-dimensional threshold-type scheduling policy is optimal for minimizing the age. By exploiting the structure of the MDP and analyzing the discrete time Markov chains (DTMCs) of the threshold-type policy, we devise a low-complexity bisection algorithm to compute the optimal thresholds. We compare different scheduling policies using numerical simulations.

References

[1]
J. Pan, A. M. Bedewy, Y. Sun, and N. B. Shroff, “Minimizing age of information via scheduling over heterogeneous channels,” in Proc. 22nd Int. Symp. Theory Algorithmic Found. Protocol Des. Mobile Netw. Mobile Comput., 2021, pp. 111–120.
[2]
R. D. Yates, Y. Sun, D. R. Brown, S. K. Kaul, E. Modiano, and S. Ulukus, “Age of information: An introduction and survey,” IEEE J. Sel. Areas Commun., vol. 39, no. 5, pp. 1183–1210, May 2021.
[3]
S. Kaul, R. Yates, and M. Gruteser, “Real-time status: How often should one update?,” in Proc. IEEE Int. Conf. Comput. Commun., 2012, pp. 2731–2735.
[4]
M. Costa, M. Codreanu, and A. Ephremides, “On the age of information in status update systems with packet management,” IEEE Trans. Inf. Theory, vol. 62, no. 4, pp. 1897–1910, Apr. 2016.
[5]
Y. Inoue, H. Masuyama, T. Takine, and T. Tanaka, “A general formula for the stationary distribution of the age of information and its application to single-server queues,” IEEE Trans. Inf. Theory, vol. 65, no. 12, pp. 8305–8324, Dec. 2019.
[6]
B. Buyukates and S. Ulukus, “Age of information with Gilbert-Elliot servers and samplers,” in Proc. IEEE 54th Annu. Conf. Inf. Sci. Syst., 2020, pp. 1–6.
[7]
A. M. Bedewy, Y. Sun, and N. B. Shroff, “Minimizing the age of information through queues,” IEEE Trans. Inf. Theory, vol. 65, no. 8, pp. 5215–5232, Aug. 2019.
[8]
A. M. Bedewy, Y. Sun, and N. B. Shroff, “The age of information in multihop networks,” IEEE/ACM Trans. Netw., vol. 27, no. 3, pp. 1248–1257, Jun. 2019.
[9]
Y. Sun, E. Uysal-Biyikoglu, and S. Kompella, “Age-optimal updates of multiple information flows,” in Proc. IEEE Conf. Comput. Commun. Workshops, 2018, pp. 136–141.
[10]
Y. Sun and B. Cyr, “Sampling for data freshness optimization: Non-linear age functions,” J. Commun. Netw., vol. 21, no. 3, pp. 204–219, 2019.
[11]
Y. Sun, Y. Polyanskiy, and E. Uysal, “Sampling of the wiener process for remote estimation over a channel with random delay,” IEEE Trans. Inf. Theory, vol. 66, no. 2, pp. 1118–1135, Feb. 2020.
[12]
A. M. Bedewy, Y. Sun, S. Kompella, and N. B. Shroff, “Optimal sampling and scheduling for timely status updates in multi-source networks,” IEEE Trans. Inf. Theory, vol. 67, no. 6, pp. 4019–4034, Jun. 2021.
[13]
Y. P. Hsu, E. Modiano, and L. Duan, “Scheduling algorithms for minimizing age of information in wireless broadcast networks with random arrivals,” IEEE Trans. Mobile Comput., vol. 19, no. 12, pp. 2903–2915, Dec. 2020.
[14]
R. Talak, S. Karaman, and E. Modiano, “Optimizing information freshness in wireless networks under general interference constraints,” IEEE/ACM Trans. Netw., vol. 28, no. 1, pp. 15–28, Feb. 2020.
[15]
A. M. Bedewy, Y. Sun, R. Singh, and N. B. Shroff, “Low-power status updates via sleep-wake scheduling,” IEEE/ACM Trans. Netw., vol. 29, no. 5, pp. 2129–2141, Oct. 2021.
[16]
C. Joo and A. Eryilmaz, “Wireless scheduling for information freshness and synchrony: Drift-based design and heavy-traffic analysis,” IEEE/ACM Trans. Netw., vol. 26, no. 6, pp. 2556–2568, Dec. 2018.
[17]
N. Lu, B. Ji, and B. Li, “Age-based scheduling: Improving data freshness for wireless real-time traffic,” in Proc. 18th ACM Int. Symp. Mobile Ad Hoc Netw. Comput., 2018, pp. 191–200.
[18]
I. Kadota, A. Sinha, and E. Modiano, “Optimizing age of information in wireless networks with throughput constraints,” in Proc. IEEE Int. Conf. Comput. Commun., 2018, pp. 1844–1852.
[19]
Z. Qian, F. Wu, J. Pan, K. Srinivasan, and N. B. Shroff, “Minimizing age of information in multi-channel time-sensitive information update systems,” in Proc. IEEE Conf. Comput. Commun., 2020, pp. 446–455.
[20]
Q. Liu, H. Zeng, and M. Chen, “Minimizing age-of-information with throughput requirements in multi-path network communication,” in Proc. 20th ACM Int. Symp. Mobile Ad Hoc Netw. Comput., 2019, pp. 41–50.
[21]
T. Z. Ornee and Y. Sun, “Sampling and remote estimation for the ornstein-uhlenbeck process through queues: Age of information and beyond,” IEEE/ACM Trans. Netw., vol. 29, no. 5, pp. 1962–1975, Oct. 2021.
[22]
Y. Sun, E. Uysal-Biyikoglu, R. D. Yates, C. E. Koksal, and N. B. Shroff, “Update or wait: How to keep your data fresh,” IEEE Trans. Inf. Theory, vol. 63, no. 11, pp. 7492–7508, Nov. 2017.
[23]
E. Altman, R. El-Azouzi, D. Menasche, and Y. Xu, “Forever young: Aging control for hybrid networks,” in Proc. 20th ACM Int. Symp. Mobile Ad Hoc Netw. Comput., 2019, pp. 91–100.
[24]
M. Raiss-el-fenni, R. El-Azouzi, D. S. Menasche, and Y. Xu, “Optimal sensing policies for smartphones in hybrid networks: A POMDP approach,” in Proc. 6th IEEE Int. ICST Conf. Perform. Eval. Methodol. Tools, 2012, pp. 89–98.
[25]
R. Talak, S. Karaman, and E. Modiano, “Optimizing age of information in wireless networks with perfect channel state information,” in Proc. IEEE 16th Int. Symp. Model. Optim. Mobile Ad Hoc Wireless Netw., 2018, pp. 1–8.
[27]
T. S. Rappaport et al., “Millimeter wave mobile communications for 5G cellular: It will work!,” IEEE Access, vol. 1, pp. 335–349, 2013.
[29]
A. Narayanan et al., “A first look at commercial 5G performance on smartphones,” in Proc. Web Conf., 2020, pp. 894–905.
[30]
Z. Pi and F. Khan, “An introduction to millimeter-wave mobile broadband systems,” IEEE Commun. Mag., vol. 49, no. 6, pp. 101–107, Jun. 2011.
[31]
Z. Pi and F. Khan, “System design and network architecture for a millimeter-wave mobile broadband (MMB) system,” in Proc. 34th IEEE Sarnoff Symp., 2011, pp. 1–6.
[32]
O. Semiari, W. Saad, M. Bennis, and M. Debbah, “Integrated millimeter wave and sub-6 GHz wireless networks: A roadmap for joint mobile broadband and ultra-reliable low-latency communications,” IEEE Wireless Commun., vol. 26, no. 2, pp. 109–115, Apr. 2019.
[33]
D. Aziz, J. Gebert, A. Ambrosy, H. Bakker, and H. Halbauer, “Architecture approaches for 5G millimetre wave access assisted by 5G low-band using multi-connectivity,” in Proc. IEEE Globecom Workshops, 2016, pp. 1–6.
[34]
J. Deng, O. Tirkkonen, R. Freij-Hollanti, T. Chen, and N. Nikaein, “Resource allocation and interference management for opportunistic relaying in integrated mmWave/sub-6GHz 5G networks,” IEEE Commun. Mag., vol. 55, no. 6, pp. 94–101, Jun. 2017.
[35]
H. Elshaer, M. N. Kulkarni, F. Boccardi, J. G. Andrews, and M. Dohler, “Downlink and uplink cell association with traditional macrocells and millimeter wave small cells,” IEEE Trans. Wireless Commun., vol. 15, no. 9, pp. 6244–6258, Sep. 2016.
[36]
D. M. Topkis, Supermodularity and Complementarity. Princeton, NJ, USA: Princeton Univ. Press, 1998.
[37]
V. Krishnamurthy, Partially Observed Markov Decision Processes. Cambridge, U.K.: Cambridge Univ. Press, 2016.
[38]
M. L. Puterman, “Markov decision processes,” Handbooks Operations Res. Manage. Sci., vol. 2, pp. 331–434, 1990.
[39]
M. H. Ngo and V. Krishnamurthy, “Optimality of threshold policies for transmission scheduling in correlated fading channels,” IEEE Trans. Commun., vol. 57, no. 8, pp. 2474–2483, Aug. 2009.
[40]
G. Yao, M. Hashemi, and N. B. Shroff, “Integrating sub-6 ghz and millimeter wave to combat blockage: Delay-optimal scheduling,” in Proc. IEEE Int. Symp. Model. Optim. Mobile Ad Hoc Wireless Netw., 2019, pp. 1–8.
[41]
M. Shi, K. Yang, Z. Han, and D. Niyato, “Coverage analysis of integrated sub-6ghz-mmwave cellular networks with hotspots,” IEEE Trans. Commun., vol. 67, no. 11, pp. 8151–8164, Nov. 2019.
[42]
M. Zada, I. A. Shah, and H. Yoo, “Integration of sub-6-ghz and mm-Wave bands with a large frequency ratio for future 5G MIMO applications,” IEEE Access, vol. 9, pp. 11241–11251, 2021.
[43]
F. B. Mismar, A. AlAmmouri, A. Alkhateeb, J. G. Andrews, and B. L. Evans, “Deep learning predictive band switching in wireless networks,” IEEE Trans. Wireless Commun., vol. 20, no. 1, pp. 96–109, Jan. 2021.
[44]
S. Islam, M. Zada, and H. Yoo, “Low-pass filter based integrated 5G smartphone antenna for sub-6-GHz and mm-Wave bands,” IEEE Trans. Antennas Propag., vol. 69, no. 9, pp. 5424–5436, Sep. 2021.
[45]
D. P. Bertsekas, Dynamic Programming and Optimal Control. Belmont, MA, USA: Athena Scientific, 1995.
[46]
L. I. Sennott, “Average cost optimal stationary policies in infinite state Markov decision processes with unbounded costs,” Operations Res., vol. 37, no. 4, pp. 626–633, 1989.
[47]
W. Dinkelbach, “On nonlinear fractional programming,” Manage. Sci., vol. 13, no. 7, pp. 492–498, 1967.
[48]
L. I. Sennott, “A new condition for the existence of optimal stationary policies in average cost Markov decision processes,” Operations Res. Lett., vol. 5, no. 1, pp. 17–23, 1986.

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    cover image IEEE Transactions on Mobile Computing
    IEEE Transactions on Mobile Computing  Volume 22, Issue 12
    Dec. 2023
    649 pages

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    IEEE Educational Activities Department

    United States

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    Published: 09 September 2022

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