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Traffic-aware auto-configuration protocol for service oriented low-power and lossy networks in IoT

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Abstract

Many diversified services can be offered by smart objects, referred to herein by nodes, in low-power and lossy networks (LLNs) contributing to the Internet of Things (IoT). A distributed naming and registration system, complying with the Internet protocol standard, is needed for unique identification of these nodes and their provided services in many areas such as monitoring and remote control. Due to the high expected number of IoT nodes, manual configuration is not practical, and an efficient auto-configuration mechanism is essential. Although the multicast domain name system (mDNS) is the most common distributed naming protocol nowadays, it is not optimized for constrained LLN nodes in IoT. This work proposes enhanced mDNS (E-mDNS) which augments mDNS with three proposed enhancements: the persistent-based selection stage, the simultaneous start-up enhancement, and the announcement suppression mechanism. Using the Cooja emulation platform, we evaluate both the mDNS and E-mDNS for a wide range of conditions and network sizes, and produce a large array of performance figures that includes number of control packets, energy consumption for CPU and radio transmissions, memory footprint, and others. Through the evaluation of the fairness index for a wide range of number of nodes, we demonstrate that E-mDNS provides better load balancing for the collection of nodes in the network relative to mDNS. Furthermore, results indicate that while E-mDNS produces a memory footprint in RAM that is only 4.2% more than that for mDNS, E-mDNS manages to significantly reduce the number of control packets by an average of 34.8% for the considered range of network size. Accordingly, the corresponding reduction in energy consumption for radio transmissions and CPU is 46.7% and 47.5%, respectively. The evaluation shows that these reductions are greater for larger number of nodes.

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Acknowledgements

The authors would like to acknowledge the support provided by King Fahd University of Petroleum and Minerals (KFUPM) and the department of computer engineering.

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  1. Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Kingdom of Saudi Arabia

    Ashraf Mahmoud, Mohammed Mahyoub, Tarek Sheltami & Marwan Abu-Amara

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  1. Ashraf Mahmoud
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Correspondence to Mohammed Mahyoub.

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Mahmoud, A., Mahyoub, M., Sheltami, T. et al. Traffic-aware auto-configuration protocol for service oriented low-power and lossy networks in IoT. Wireless Netw 25, 4231–4246 (2019). https://doi.org/10.1007/s11276-019-02086-4

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