IoT plays an important role in cellular networks, and its need for global connectivity is driving the rise of Global IoT Providers. These provide service by aggregating multiple mobile providers through roaming, complicating the understanding of the overall mobile ecosystem. This calls for lightweight monitoring solutions, which are crucial to meet the quality demanded by IoT services, and of automatic means to analyze the data, with the final goal to carry out economic and management activities. This paper provides insights from the study of two commercial, widespread IoT providers. We show how monitoring signaling traffic between mobile networks offers a unique opportunity to understand both the IoT customers’ characteristics and the network functioning. Leveraging clustering, we offer the first data-driven methodology to examine large IoT signaling datasets. By analyzing over 1.3 billion signaling dialogues across two providers, we identify common signaling profiles that depend on the specific IoT vertical, likely misconfigured devices, and sudden changes that indicate potential problems. This provides actionable insights for network management decisions and service improvements, and lays the groundwork for future research on IoT traffic modeling.

Untangling IoT Global Connectivity: The Importance of Mobile Signaling Traffic / Geißler, Stefan; Lutu, Andra; Wamser, Florian; Favale, Thomas; Vomhoff, Viktoria; Krolikowski, Michael; Mellia, Marco; Perino, Diego; Hoßfeld, Tobias. - In: IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT. - ISSN 1932-4537. - ELETTRONICO. - 21:4(2024), pp. 4435-4449. [10.1109/tnsm.2024.3414975]

Untangling IoT Global Connectivity: The Importance of Mobile Signaling Traffic

Favale, Thomas;Mellia, Marco;
2024

Abstract

IoT plays an important role in cellular networks, and its need for global connectivity is driving the rise of Global IoT Providers. These provide service by aggregating multiple mobile providers through roaming, complicating the understanding of the overall mobile ecosystem. This calls for lightweight monitoring solutions, which are crucial to meet the quality demanded by IoT services, and of automatic means to analyze the data, with the final goal to carry out economic and management activities. This paper provides insights from the study of two commercial, widespread IoT providers. We show how monitoring signaling traffic between mobile networks offers a unique opportunity to understand both the IoT customers’ characteristics and the network functioning. Leveraging clustering, we offer the first data-driven methodology to examine large IoT signaling datasets. By analyzing over 1.3 billion signaling dialogues across two providers, we identify common signaling profiles that depend on the specific IoT vertical, likely misconfigured devices, and sudden changes that indicate potential problems. This provides actionable insights for network management decisions and service improvements, and lays the groundwork for future research on IoT traffic modeling.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2991901