Skip to main content

Internet of Things Scalability: Communications and Data Management

  • Chapter
  • First Online:
Modern Sensing Technologies

Part of the book series: Smart Sensors, Measurement and Instrumentation ((SSMI,volume 29))

Abstract

Internet of Things (IoT) is becoming more and more pervasive in everyday life and connecting an array of diverse physical objects. It is fast growing and receiving a tremendous amount of research focus. Billions of objects communicate each other with or without human intervention to achieve smart applications. Most of the connected devices are constrained nodes to its ecosystem which have limited memories, CPU capabilities and power sources. Therefore, for implementing autonomous smart systems, efficient energy consumption is imperative. This chapter introduces a novel scheduling algorithm called Long Hop (LH) first to optimize energy usage on a wireless sensor network (WSN) that enables IoT systems. The selected algorithm proposes an optimized solution to the energy efficient for scalable IoT networks. LH technique assigns high priority for packets coming with more hops and longer distances to be served first at the cluster head (CH) nodes. Since these packets require more links and nodes (thus increased energy and bandwidth usage) to reach the ultimate destination if not prioritized. The proposed technique reduces the overall energy usage and minimizes the total number of packets re-transmission and the effective data transmission distances. Thus, this improves the overall system performance and elongates the network lifetime.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. M. Hammoudeh, F. Al-fayez, H. Lloyd, R. Newman, B. Adebisi, System: deployment issues and routing protocols. IEEE Sens. 17(8), 2572–2582 (2017)

    Article  Google Scholar 

  2. W. Stallings, Foundations of Modern Networking: SDN, NFV, QoE, IoT, and Cloud (2015)

    Google Scholar 

  3. H. Ghayvat, S. Mukhopadhyay, X. Gui, N. Suryadevara, WSN- and IOT-based smart homes and their extension to smart buildings. Sensors (Switzerland) 15(5), 10350–10379 (2015)

    Article  Google Scholar 

  4. D.R. Dandekar, P.R. Deshmukh, Energy balancing multiple sink optimal deployment in multi-hop wireless sensor networks, in 2013 3rd IEEE International Advance Computing Conference (IACC) (2013), pp. 408–412

    Google Scholar 

  5. L. Farhan, A.E. Alissa, S.T. Shukur, M. Alrweg, U. Raza, R. Kharel, A survey on the challenges and opportunities of the internet of things (IoT), in International Conference on Sensing Technology (2017)

    Google Scholar 

  6. M.M. Rathore, A. Ahmad, A. Paul, S. Rho, Urban planning and building smart cities based on the internet of things using big data analytics. Comput. Netw. 101(2016), 63–80 (2016)

    Article  Google Scholar 

  7. Project team IEC, Internet of things : wireless sensor networks executive summary, in International Electrotechnical Commission (2014), p. 78

    Google Scholar 

  8. M. Hammoudeh, R. Newman, Adaptive routing in wireless sensor networks: QoS optimisation for enhanced application performance. Inf. Fusion 22, 3–15 (2015)

    Article  Google Scholar 

  9. A. Abuarqoub, M. Hammoudeh, B. Adebisi, S. Jabbar, A. Bounceur, H. Al-Bashar, Dynamic clustering and management of mobile wireless sensor networks. Comput. Netw. 117, 62–72 (2017)

    Article  Google Scholar 

  10. S. Hagen, IPV6 essentials, in Grundlagen—Funktionalität, Integr. 2nd edn. (Sunny ED, 2009)

    Google Scholar 

  11. H. Wang, J. Jin, Z. Wang, L. Shu, On a novel property of the earliest deadline first algorithm, in 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) (2011), pp. 197–201

    Google Scholar 

  12. S. Abdullah, K. Yang, An energy-efficient message scheduling algorithm in internet of things environment, in 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC) (2013), pp. 311–316

    Google Scholar 

  13. L. Karim, N. Nasser, T. Taleb, A. Alqallaf, An efficient priority packet scheduling algorithm for wireless sensor network, in 2012 IEEE International Conference on Communications (ICC) (2012), pp. 334–338

    Google Scholar 

  14. D. Saha, M.R. Yousuf, M.A. Matin, Energy efficient scheduling algorithm for S-mac protocol in wireless sensor network. Int. J. Wirel. Mob. Netw. 3(6), 129–140 (2011)

    Article  Google Scholar 

  15. Z. Wang, Y. Liu, Y. Sun, Y. Li, D. Zhang, H. Yang, An energy-efficient heterogeneous dual-core processor for internet of things, in 2015 IEEE International Symposium on Circuits and Systems (ISCAS) (2015), pp. 2301–2304

    Google Scholar 

  16. W.Y. Lee, Energy-saving DVFS scheduling of multiple periodic real-time tasks on multi-core processors, in 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (2009), pp. 216–223

    Google Scholar 

  17. Z. Vincze, R. Vida, A. Vidacs, Deploying multiple sinks in multi-hop wireless sensor networks, in IEEE International Conference on Pervasive Services (2007), pp. 55–63

    Google Scholar 

  18. XBee Modules, XBee®/XBee-PRO® RF Modules, in Product Manual v1. xEx-802.15.4 Protocol (2009)

    Google Scholar 

  19. L. Farhan, R. Kharel, O. Kaiwartya, M. Hammoudeh, B. Adebisi, Towards green computing for internet of things: energy oriented path and message scheduling approach. Sustain. Cities Soc. 38(July 2017), 195–204 (2018)

    Google Scholar 

  20. Y. Zheng, L. Wan, Z. Sun, S. Mei, A long range DV-Hop localization algorithm with placement strategy in wireless sensor networks, in 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (2008), pp. 1–5

    Google Scholar 

  21. S. Broumi, A. Bakal, M. Talea, F. Smarandache, L. Vladareanu, Applying Dijkstra algorithm for solving neutrosophic shortest path problem, in International Conference on Advanced Mechatronic Systems (ICAMechS) (2016), pp. 412–416

    Google Scholar 

  22. A.M. Ahmed, S.H. Ahmed, O.H. Ahmed, Dijkstra algorithm applied: design and implementation of a framework to find nearest hotels and booking systems in Iraqi, in International Conference on Current Research in Computer Science and Information Technology (ICCIT 2017) (2017), pp. 126–132

    Google Scholar 

  23. N.M.G. Appenzeller, I. Keslassy, Sizing router buffers. SIGCOMM Comput. Commun. 34(4), 281–292 (2004)

    Article  Google Scholar 

  24. D. Raca, A.H. Zahran, C.J. Sreenan, Sizing network buffers : a HTTP adaptive streaming perspective, in The IEEE 6th International Conference on Future Internet of Things and Cloud Work (2016)

    Google Scholar 

  25. L. Farhan, A.E. Alissa, S.T. Shukur, M. Hammoudeh, R. Kharel, An energy efficient long hop (LH) first scheduling algorithm for scalable internet of things (IoT) networks, in 11th International Conference on Sensing Technology (2017)

    Google Scholar 

  26. L. Farhan, L. Alzubaidi, M. Abdulsalam, A.J. Abboud, M. Hammoudeh, R. Kharel, An efficient data packet scheduling scheme for internet of things networks, in Diyala Third International Scientific Conference of Engineering Sciences 2018, 1st Diyala International Scientific Conference of Engineering Sciences 2018

    Google Scholar 

  27. Y.S. Uddin, F. Saremi, T. Abdelzaher, End-to-end delay bound for prioritized data flows in disruption-tolerant networks. In IEEE Real-Time Systems Symposium (2010) https://doi.org/10.1109/RTSS.2010.39

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Laith Farhan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Farhan, L., Kharel, R. (2019). Internet of Things Scalability: Communications and Data Management. In: Mukhopadhyay, S., Jayasundera, K., Postolache, O. (eds) Modern Sensing Technologies . Smart Sensors, Measurement and Instrumentation, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-99540-3_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-99540-3_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99539-7

  • Online ISBN: 978-3-319-99540-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics