With the rapid expansion of IoT, there is a growing demand for efficient data processing and network load optimization. Service Function Chaining (SFC) has emerged as a key technology for distributed processing, particularly in edge computing environments. While SFC is traditionally implemented over IP networks, recent research has explored Named Data Networking (NDN) as a more flexible alternative, leveraging its content caching and name-based forwarding. However, NDN's inherent request aggregation and multicast mechanisms introduce unique challenges in applying conventional distributed tracing techniques, which are crucial for SFC applications to understand potential root causes of problems.This paper proposes a distributed tracing method for NDN-based SFC (NDN SFC) that enables packet flow visualization and network latency analysis. Our method introduces logging agents on NDN routers to capture request flows and inter-node delays, which are then formatted using OpenTelemetry for seamless integration with visualization tools such as Grafana® and Jaeger.Our tracing method helps to optimize service chains, to enhance network performance evaluation, and to streamline debugging, making NDN SFC deployment more practical. By offering a more efficient alternative to traditional IP-based SFC, our method supports the practical adoption of NDN SFC in IoT and edge computing environments.

Kobayashi, H., Kanai, K., Nakazato, H., Detti, A. (2025). Distributed tracing for Service Function Chaining in Named Data Networking. In 2025 IEEE 26th International Conference on High Performance Switching and Routing (HPSR) (pp.1-6). New York : IEEE [10.1109/HPSR64165.2025.11038905].

Distributed tracing for Service Function Chaining in Named Data Networking

Detti A.
2025-01-01

Abstract

With the rapid expansion of IoT, there is a growing demand for efficient data processing and network load optimization. Service Function Chaining (SFC) has emerged as a key technology for distributed processing, particularly in edge computing environments. While SFC is traditionally implemented over IP networks, recent research has explored Named Data Networking (NDN) as a more flexible alternative, leveraging its content caching and name-based forwarding. However, NDN's inherent request aggregation and multicast mechanisms introduce unique challenges in applying conventional distributed tracing techniques, which are crucial for SFC applications to understand potential root causes of problems.This paper proposes a distributed tracing method for NDN-based SFC (NDN SFC) that enables packet flow visualization and network latency analysis. Our method introduces logging agents on NDN routers to capture request flows and inter-node delays, which are then formatted using OpenTelemetry for seamless integration with visualization tools such as Grafana® and Jaeger.Our tracing method helps to optimize service chains, to enhance network performance evaluation, and to streamline debugging, making NDN SFC deployment more practical. By offering a more efficient alternative to traditional IP-based SFC, our method supports the practical adoption of NDN SFC in IoT and edge computing environments.
26th IEEE International Conference on High Performance Switching and Routing (HPSR 2025)
Suita, Osaka, Japan
2025
IEEE Communications Society
Rilevanza internazionale
2025
Settore IINF-03/A - Telecomunicazioni
Settore IINF-05/A - Sistemi di elaborazione delle informazioni
English
Distributed Tracing; ICN; Information-Centric Networking; IoT; NDN; Service Function Chaining
Intervento a convegno
Kobayashi, H., Kanai, K., Nakazato, H., Detti, A. (2025). Distributed tracing for Service Function Chaining in Named Data Networking. In 2025 IEEE 26th International Conference on High Performance Switching and Routing (HPSR) (pp.1-6). New York : IEEE [10.1109/HPSR64165.2025.11038905].
Kobayashi, H; Kanai, K; Nakazato, H; Detti, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/436386
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