Distributed Network Slicing in Large Scale IoT Based on Coalitional Multi-Game Theory

The massive growth of the Internet of Things (IoT) poses important challenges on network operators to support billions of IoT devices connected through the cloud with each having constrained battery life and computational capacity. To support these requirements over long distances, Long Range Wide Area Network (LoRaWAN), is now widely being deployed with the promise to support an all-connected world with numerous IoT applications. In large scale access networks, supporting urgent and reliable communications with their QoS demands becomes more challenging. Hence, network slicing within an SDN-based architecture brings numerous advantages to solve this problem by easily managing network resources and reserving part of the latter for urgent traffic and avoiding its performance degradation due to congestion. In this paper, we tackle the raised questions regarding scalability limitations by proposing a distributed slicing strategy based on coalitional game and matching theory over an SDN-based LoRaWAN architecture. In this context, resource reservation for LoRa slices and configuration optimization are performed closer to the edge at the gateway level. Simulation results performed over NS3 highlight the utility of the distributed slicing strategy in respecting quality of service (QoS) thresholds in terms of delay, throughput, energy consumption and improving reliability while providing complete isolation between LoRa slices.