Towards a new generation of IoT based on network coding for the Industry 4.0

Abstract

Internet of Things (IoT) is considered to be a disruptive technology that provides intelligent services by connecting objects equipped with sensors, actuators, and processors to networks. It is used in different applications such as smart homes, social life, entertainment, health, fitness, etc. Furthermore, IoT is applied in industrial applications such as transportation, manufacturing, energy, and agriculture, known as the Industrial Internet of Things (IIoT). Factories use IIoT networks for time-critical services, such as anomaly detection, system control, and robot guidance, that require low delays and highly reliable communications. However, IIoT networks use wireless communication and are applied to factories with high levels of noises and interference. As a result, information loss is an inevitable issue in IIoT networks, increasing communication delay and affecting the reliability of the network. In these networks, since packets should be delivered in-order to the application layer, the next packets cannot be delivered to the application layer unless the previous packets are delivered. Thus, information loss is detrimental for the time-critical services that require low delay communications. Recently, Network Coding (NC) has been introduced as a promising technology to recover information loss. Network coding can recover information loss by different methods. In this thesis, we investigate two of the most important network coding methods in order to identify which would be the most suitable to the stringent requirements of IIoT networks. To this end, we compare block-based network coding with sliding network coding methods in a one-hop multicast scenario and study the effects of the various parameters based on their performance. Simulations show that sliding window network coding decodes more packets with a lower in-order delivery delay than that of block-based RLNC. However, sliding window network coding has a maximum in-order delivery delay and decoding complexity and also needs a larger buffer size.

Date	12 Oct 2021
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Pascal Giard (Supervisor) & Georges Kaddoum (Co-supervisor)