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Network Performance Enhancement of Multi-sink Enabled Low Power Lossy Networks in SDN Based Internet of Things

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Abstract

Software Defined Network (SDN) brought revolution in the network field with the partnership of Academia and Industry. SDN bridges the gap to overcome issues of IoT deployment, optimization and better utilization of network resources. The escalation in resource congestion in Wireless Sensor Networks (WSNs) can usually lead to scalability, data computation or storage, and energy efficiency problems with only a single sink node for data acquisition. Internet of Things (IoT) has resource and energy constraints for WSN devices. Low Power and Lossy Networks (LLNs) ought to be optimized for traffic with multiple sinks. RPL routing has constraints to support this approach. However, RPL inherits the ability to offer features like Auto-Configuration, Self-Healing, Loop avoidance, and detection. These features of RPL can be transformed into the improved performance of a WSN by increasing the number of sinks with a linear increase of data transmitting nodes in the network. Further, to mitigate the escalated computing needs, edge computing has emerged as a new paradigm to resolve SDN-enabled IoT and localized computing needs. This study proposes an SDN-based solution to the interconnectivity of resource constraint LLN devices with edge computing routers in mesh and cluster topological scenario using RPL as IoT routing protocol. Performance evaluation concerning different routing metrics and objective functions: Minimum Rank with Hysteresis Function (MRHOF) and Zero (OF0) are analyzed. COOJA simulator is used for emulation of random as well as linear grid topologies for the creation of WSN static nodes. Simulation results confirm that the gradual increase of a number of nodes from 16, 32, 48, 64 and a simultaneous increase in sinks nodes as 1, 2, 3, 4 respectively in LLN network reflects the desired advantages with the stable network.

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Acknowledgements

This research was financially supported by University of Engineering and Technology Taxila, Pakistan through the Directorate of Advanced Studies, Research and Technological Development (ASR&TD) research grant, for which we indebted.

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Authors and Affiliations

  1. Department of Telecom Engineering, University of Engineering and Technology, Taxila, Pakistan

    Ghulam Shabbir & Adeel Akram

  2. Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan

    Muhammad Munwar Iqbal

  3. Department of Computer Science, National Textile University, Faisalabad, Pakistan

    Sohail Jabbar

  4. Prince Abdullah bin Ghazi Faculty of Information Technology, Al-Balqa Applied University, Salt, Jordan

    Mai Alfawair

  5. College of Security and Intelligence, Embry-Riddle Aeronautical University, Prescott, AZ, USA

    Junaid Chaudhry

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  1. Ghulam Shabbir
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Correspondence to Sohail Jabbar.

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Shabbir, G., Akram, A., Iqbal, M.M. et al. Network Performance Enhancement of Multi-sink Enabled Low Power Lossy Networks in SDN Based Internet of Things. Int J Parallel Prog 48, 367–398 (2020). https://doi.org/10.1007/s10766-018-0620-8

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  • DOI: https://doi.org/10.1007/s10766-018-0620-8

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