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Age of Information in Backscatter Communication

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Part of the Internet of Things book series (ITTCC)

Abstract

Age of Information (AoI) has been introduced to characterize the newness of data which is observed in real time. In other words, it is the measure of time elapsed since the generation of last received update about a process and is a vital metric in networks such as Internet of things (IoTs), especially when the application demands fresh updates. Most of the applications require fresh data e.g., applications related to environmental monitoring, smart agriculture, body area networks etc. On the other hand backscatter communication promises to resolve one of the most challenging issues of IoT devices, i.e., making them capable for communication without the batteries. The importance of AoI in backscatter communication is paramount to gauge performance of backscatter IoT networks. This chapter addresses the significance of AoI in backscatter communication and suggests some techniques to design a communication system with minimum AoI, maximum energy efficiency, and minimum outage.

Keywords

Age of Information (AoI) Backscatter communication Time sensitive IoT applications Wireless powered communication networks Status updates Energy efficiency 

References

  1. 1.
    Da Xu, L., He, W., Li, S.: Internet of Things in industries: a survey. Trans. Ind. Inform. 10(4), 2233–2243 (2014)CrossRefGoogle Scholar
  2. 2.
    Sun, Y., Uysal-Biyikoglu, E., Yates, R.D., Koksal, C.E., Shroff, N.B.: Update or wait: how to keep your data fresh. Trans. Inform. Theory 63(11), 7492–7508 (2017)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Kosta, A., Pappas, N., Angelakis, V., et al.: Age of information: a new concept, metric, and tool. Found. Trends® Netw. 12(3), 162–259 (2017)CrossRefGoogle Scholar
  4. 4.
    Papadimitratos, P., Fortelle, A.L., Evenssen, K., Brignolo, R., Cosenza, S.: Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation. IEEE Commun. Mag. 47(11), 84–95 (2009)CrossRefGoogle Scholar
  5. 5.
    Abd-Elmagid, M.A., Dhillon, H.S.: Average peak age-of-information minimization in UAV-assisted IoT networks. Trans. Veh. Technol. 68(2), 2003–2008 (2019)CrossRefGoogle Scholar
  6. 6.
    Kaul, S., Yates, R., Gruteser, M.: Real-time status: how often should one update? In: Proceedings, pp. 2731–2735 (2012)Google Scholar
  7. 7.
    Kam, C., Kompella S., Ephremides, A.: Experimental evaluation of the age of information via emulation. In: MILCOM Military Communications Conference, pp. 1070–1075 (2015)Google Scholar
  8. 8.
    Kam, C., Kompella, S., Ephremides, A.: Age of information under random updates. In: IEEE International Symposium on Information Theory, vol. 2013, pp. 66–70. IEEE (2013)Google Scholar
  9. 9.
    Huang, L., Modiano, E.: Optimizing age-of-information in a multi-class queueing system. In: IEEE International Symposium on Information Theory (ISIT), vol. 2015, pp. 1681–1685. IEEE (2015)Google Scholar
  10. 10.
    Bedewy, A.M., Sun, Y., Shroff, N.B.: Optimizing data freshness, throughput, and delay in multi-server information-update systems. In: International Symposium on Information Theory (ISIT), pp. 2569–2573 (2016)Google Scholar
  11. 11.
    Kaul, S., Gruteser, M., Rai, V., Kenney, J.: Minimizing age of information in vehicular networks. In: 8th Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 350–358 (2011)Google Scholar
  12. 12.
    Liu, J., Wang, X., Bai, B., Dai, H.: Age-optimal trajectory planning for UAV-assisted data collection. In: INFOCOM Conference on Computer Communications Workshops, pp. 553–558 (2018)Google Scholar
  13. 13.
    Kam, C., Kompella, S., Nguyen, G.D., Wieselthier, J.E., Ephremides, A.: On the age of information with packet deadlines. IEEE Trans. Inform. Theory 64(9), 6419–6428 (2018)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Niyato, D., Kim, D.I., Maso, M., Han, Z.: Wireless powered communication networks: research directions and technological approaches. IEEE Wirel. Commun. 24(6), 88–97 (2017)CrossRefGoogle Scholar
  15. 15.
    Kimionis, J., Tentzeris, M.M.: Pulse shaping: the missing piece of backscatter radio and RFID. IEEE Trans. Microw. Theory Tech. 64(12), 4774–4788 (2016)CrossRefGoogle Scholar
  16. 16.
    Jiang, Z., Krishnamachari, B., Zhou, S., Niu, Z.: Can decentralized status update achieve universally near-optimal age-of-information in wireless multiaccess channels? In: 30th International Teletraffic Congress (ITC 30), vol. 1, pp. 144–152 (2018)Google Scholar
  17. 17.
    Sasikumar, P., Khara, S.: K-means clustering in wireless sensor networks. In: Fourth international conference on computational intelligence and communication networks, vol. 2012, pp. 140–144. IEEE (2012)Google Scholar
  18. 18.
    Shehzad, M.K., Hassan, S.A., Mahmood, A., Gidlund, M.: On the association of small cell base stations with UAVs using unsupervised learning. In: IEEE 89th Vehicular Technology Conference (VTC2019-Spring), vol. 2019, pp. 1–5. IEEE (2019)Google Scholar
  19. 19.
    Zeb, S., Abbas, Q., Hassan, S.A., Mahmood, A., Mumtaz, R., Zaidi, S., Zaidi, S.A.R., Gidlund, M.: NOMA enhanced backscatter communication for green IoT networks. In: 16th International Symposium on Wireless Communication Systems (ISWCS) (2019)Google Scholar

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© Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.School of Electrical Engineering and Computer Science (SEECS)National University of Sciences and Technology (NUST)IslamabadPakistan

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