Towards Energy-Efficient RF-Enabled Sensor Networks in Internet of Things

  • Shaik Shabana Anjum
  • Ismail Ahmedy
  • Rafidah Md NoorEmail author
  • Mohammad Hossein Anisi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 869)


A crucial conduct norm for a sensor network is to avoid network failures and packet drop. One of the other essential requirements is to effectively manage the energy levels of the nodes according to the states of the operation required for an application. This paper proposes an energy management model with the aim of allowing energy optimization of Radio Frequency (RF) enabled Sensor Networks (RSN) through Energy Harvesting (EH) and Energy Transfer (ET) techniques. The harvested and transferred energy is used by the RSN tags to maintain the energy levels of the network and prevent dead state of a node. It is observed that these Energy Management (EM) techniques are different from the existing solutions in the literature, where managing the energy consumption by the transceivers and the radio is tedious in integrated systems of sensors and tags. Stochastic Backscattering Algorithm (SBA) based on the trade-off between EH rate and transmission range is also proposed. Performance analysis of the proposed EM model is carried out by characterizing the RSN nodes using Semi Markov Decision Process (SMDP). Numerical results show that through RF-based EH and SBA based ET, the lifetime of the network can be improved by around 25%, comparatively to conventional sensor networks. The results are quantified empirically for Internet of Things (IoT) contexts in terms of energy costs, lifetime of sensors and successful packet transmission.


Energy harvesting Energy transfer RSN WSN Energy modelling 



The authors would like to thank the Sustainable Science Cluster, University of Malaya (Grand Challenge Grant UM.0000007/HRU.GC.SS GC002B-15SUS) for their support.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Shaik Shabana Anjum
    • 1
  • Ismail Ahmedy
    • 1
  • Rafidah Md Noor
    • 1
    Email author
  • Mohammad Hossein Anisi
    • 2
  1. 1.Department of Computer System and Technology, Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala LumpurMalaysia
  2. 2.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK

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