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An age of information based scheduling algorithm in a shared channel with energy and link capacity constraints

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Abstract

For data collection systems, it is important to rationally allocate link capacity to each source node so that the base station can receive fresh data. In recent years, a metric called age of information (AoI) has appeared to measure the freshness of the received information. In this paper, we build a model in which multiple heterogeneous source nodes with energy constraints transmit samples to a base station via a shared capacity-constrained channel. Then, with the objective of minimizing average weighted AoI in data collection systems, we propose a strategy where each source node has two buffers to store its latest partially transmitted sample and its complete latest collected sample, respectively. We establish the AoI model, sample transmission model and energy consumption model for the two buffers, and design a scheduling algorithm two-buffers strategy algorithm in this strategy. Finally, the proposed algorithm has been compared with the other four scheduling algorithms by simulation. The results show that the proposed algorithm performs better than them in terms of the average weighted AoI.

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The data that support the findings of this study are available on request from the corresponding author.

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The code that support the findings of this study are available on request from the corresponding author.

References

  1. Baggag, A., Abbar, S., Sharma, A., Zanouda, T., Al-Homaid, A., Mohan, A., & Srivastava, J. (2021). Learning spatiotemporal latent factors of traffic via regularized tensor factorization: Imputing missing values and forecasting. IEEE Transactions on Knowledge and Data Engineering, 33(6), 2573–2587. https://doi.org/10.1109/TKDE.2019.2954868

    Article  Google Scholar 

  2. Subramani, J., Maria, A., Rajasekaran, A. S., & Al-Turjman, F. (2022). Lightweight privacy and confidentiality preserving anonymous authentication scheme for WBANs. IEEE Transactions on Industrial Informatics, 18(5), 3484–3491. https://doi.org/10.1109/TII.2021.3097759

    Article  Google Scholar 

  3. Xu, J., Qing, T., Jiang, Z., Zhang, P., & Feng, B. (2021). Graphene oxide-regulated low-background aptasensor for the turn on detection of tetracycline. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 260, 119898. https://doi.org/10.1016/j.saa.2021.119898

    Article  Google Scholar 

  4. Kang, B., Nguyen, P., & Choo, H. (2018). Delay-efficient energy-minimized data collection with dynamic traffic in WSNs. IEEE Sensors Journal, 18(7), 3028–3038. https://doi.org/10.1109/JSEN.2017.2788409

    Article  Google Scholar 

  5. Lin, C.-C., & Chang, C.-Y. (2020). An energy balanced data collection mechanism for maximizing throughput using uncontrolled mobile sink in WSNs. In 2020 IEEE international conference on consumer electronics—Taiwan (ICCE-Taiwan) (pp. 1–2). https://doi.org/10.1109/ICCE-Taiwan49838.2020.9258192.

  6. Kadota, I., Sinha, A., Uysal-Biyikoglu, E., Singh, R., & Modiano, E. (2018). Scheduling policies for minimizing age of information in broadcast wireless networks. IEEE/ACM Transactions on Networking, 26(6), 2637–2650. https://doi.org/10.1109/TNET.2018.2873606

    Article  Google Scholar 

  7. Kaul, S., Gruteser, M., Rai, V., & Kenney, J. (2011). Minimizing age of information in vehicular networks. In 2011 8th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (pp. 350–358). https://doi.org/10.1109/SAHCN.2011.5984917.

  8. Kaul, S., Yates, R., & Gruteser, M. (2012). Real-time status: How often should one update? In 2012 proceedings IEEE INFOCOM (pp. 2731–2735). https://doi.org/10.1109/INFCOM.2012.6195689.

  9. Wang, T., Qiu, L., Sangaiah, A. K., Xu, G., & Liu, A. (2020). Energy-efficient and trustworthy data collection protocol based on mobile fog computing in internet of things. IEEE Transactions on Industrial Informatics, 16(5), 3531–3539. https://doi.org/10.1109/TII.2019.2920277

    Article  Google Scholar 

  10. Li, C., Li, S., & Hou, Y. T. (2019). A general model for minimizing age of information at network edge. In IEEE INFOCOM 2019—IEEE conference on computer communications (pp. 118–126). https://doi.org/10.1109/INFOCOM.2019.8737437.

  11. Ye, H., Hao, W., & Huang, F. (2021). Link resource allocation strategy based on age of information and sample extrusion awareness in dynamic channels. IEEE Access, 9, 88048–88059. https://doi.org/10.1109/ACCESS.2021.3089486

    Article  Google Scholar 

  12. Li, C., Huang, Y., Chen, Y., Jalaian, B., Hou, Y. T., & Lou, W. (2019). Kronos: A 5g scheduler for aoi minimization under dynamic channel conditions. In 2019 IEEE 39th international conference on distributed computing systems (ICDCS) (pp. 1466–1475). https://doi.org/10.1109/ICDCS.2019.00146.

  13. Arafa, A., Yang, J., Ulukus, S., & Poor, H. V. (2020). Age-minimal transmission for energy harvesting sensors with finite batteries: Online policies. IEEE Transactions on Information Theory, 66(1), 534–556. https://doi.org/10.1109/TIT.2019.2938969

    Article  MathSciNet  Google Scholar 

  14. Zheng, X., Zhou, S., Jiang, Z., & Niu, Z. (2019). Closed-form analysis of non-linear age of information in status updates with an energy harvesting transmitter. IEEE Transactions on Wireless Communications, 18(8), 4129–4142. https://doi.org/10.1109/TWC.2019.2921372

    Article  Google Scholar 

  15. Feng, S., & Yang, J. (2018). Minimizing age of information for an energy harvesting source with updating failures. In 2018 IEEE international symposium on information theory (ISIT) (pp. 2431–2435). https://doi.org/10.1109/ISIT.2018.8437547.

  16. Tang, H., Wang, J., Song, L., & Song, J. (2020). Minimizing age of information with power constraints: Multi-user opportunistic scheduling in multi-state time-varying channels. IEEE Journal on Selected Areas in Communications, 38(5), 854–868. https://doi.org/10.1109/JSAC.2020.2980911

    Article  Google Scholar 

  17. Song, M., Yang, H. H., Shan, H., Lee, J., & Quek, T. Q. S. (2023). Age of information in wireless networks: Spatiotemporal analysis and locally adaptive power control. IEEE Transactions on Mobile Computing, 22(6), 3123–3136. https://doi.org/10.1109/TMC.2021.3139666

    Article  Google Scholar 

  18. Mankar, P. D., Abd-Elmagid, M. A., & Dhillon, H. S. (2021). Spatial distribution of the mean peak age of information in wireless networks. IEEE Transactions on Wireless Communications, 20(7), 4465–4479. https://doi.org/10.1109/TWC.2021.3059260

    Article  Google Scholar 

  19. Zou, P., Ozel, O., & Subramaniam, S. (2020). Waiting before serving: A companion to packet management in status update systems. IEEE Transactions on Information Theory, 66(6), 3864–3877. https://doi.org/10.1109/TIT.2019.2963035

    Article  MathSciNet  Google Scholar 

  20. Chen, K., & Huang, L. (2016). Age-of-information in the presence of error. In 2016 IEEE international symposium on information theory (ISIT) (pp. 2579–2583). https://doi.org/10.1109/ISIT.2016.7541765.

  21. Kosta, A., Pappas, N., Ephremides, A., & Angelakis, V. (2021). The age of information in a discrete time queue: Stationary distribution and non-linear age mean analysis. IEEE Journal on Selected Areas in Communications, 39(5), 1352–1364. https://doi.org/10.1109/JSAC.2021.3065045

    Article  Google Scholar 

  22. Talak, R., Karaman, S., & Modiano, E. (2019). When a heavy tailed service minimizes age of information. In 2019 IEEE international symposium on information theory (ISIT) (pp. 345–349). https://doi.org/10.1109/ISIT.2019.8849697.

  23. Farazi, S., Klein, A. G., & Brown, D. R. (2018). Age of information in energy harvesting status update systems: When to preempt in service? In 2018 IEEE international symposium on information theory (ISIT) (pp. 2436–2440). https://doi.org/10.1109/ISIT.2018.8437904.

  24. Kadota, I., Sinha, A., & Modiano, E. (2019). Scheduling algorithms for optimizing age of information in wireless networks with throughput constraints. IEEE/ACM Transactions on Networking, 27(4), 1359–1372. https://doi.org/10.1109/TNET.2019.2918736

    Article  Google Scholar 

  25. Li, C., Li, S., Chen, Y., Thomas Hou, Y., & Lou, W. (2020). Aoi scheduling with maximum thresholds. In IEEE INFOCOM 2020—IEEE conference on computer communications (pp. 436–445). https://doi.org/10.1109/INFOCOM41043.2020.9155514.

  26. Dong, Y., Fan, P., & Letaief, K. B. (2020). Energy harvesting powered sensing in IoT: Timeliness versus distortion. IEEE Internet of Things Journal, 7(11), 10897–10911. https://doi.org/10.1109/JIOT.2020.2990715

    Article  Google Scholar 

  27. Hao, W., Ye, H., & Huang, F. (2022). Data collection algorithm for internet of things based on age of information and sample extrusion awareness. International Journal of Innovative Computing, Information and Control, 18(2), 497–509. https://doi.org/10.24507/ijicic.18.02.497

    Article  Google Scholar 

  28. Yarinezhad, R., & Sabaei, M. (2021). An optimal cluster-based routing algorithm for lifetime maximization of internet of things. Journal of Parallel and Distributed Computing, 156, 7–24. https://doi.org/10.1016/j.jpdc.2021.05.005

    Article  Google Scholar 

  29. Haseeb, K., Ud Din, I., Almogren, A., Ahmed, I., & Guizani, M. (2021). Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things. Sustainable Cities and Society, 68, 102779. https://doi.org/10.1016/j.scs.2021.102779

    Article  Google Scholar 

  30. Yarinezhad, R., & Sabaei, M. (2021). An optimal cluster-based routing algorithm for lifetime maximization of internet of things. Journal of Parallel and Distributed Computing, 156, 7–24. https://doi.org/10.1016/j.jpdc.2021.05.005

    Article  Google Scholar 

  31. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670. https://doi.org/10.1109/TWC.2002.804190

    Article  Google Scholar 

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Acknowledgements

The authors sincerely thank Prof. Hengzhou Ye for his guidance in refining our manuscript and polishing the language. The authors also would like to thank National Natural Science Foundation of China (Grant 62303472) for financial support.

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Authors and Affiliations

  1. College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China

    Wei Hao

  2. National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, 100871, China

    Chen Hou

  3. PKU-Changsha Institute for Computing and Digital Economy, Changsha, 410205, China

    Chen Hou

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  1. Wei Hao
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Correspondence to Chen Hou.

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Hao, W., Hou, C. An age of information based scheduling algorithm in a shared channel with energy and link capacity constraints. Wireless Netw (2024). https://doi.org/10.1007/s11276-024-03740-2

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