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MIA-NDN: Microservice-Centric Interest Aggregation in Named Data Networking.

Muhammad Imran1, Muhammad Salah Ud Din2, Muhammad Atif Ur Rehman3

  • 1Department of Software and Communications Engineering, Hongik University, Sejong City 30016, Republic of Korea.

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|February 11, 2023
PubMed
Summary
This summary is machine-generated.

MIA-NDN enhances named data networking by improving microservice-centric interest aggregation and pending interest table (PIT) management. This approach prevents false aggregations and computation losses, boosting overall network performance.

Keywords:
information-centric networkingmicroservice interest aggregationmicroservice-centric computationsnamed data networkingpending interest table

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Area of Science:

  • Computer Science
  • Network Engineering
  • Distributed Systems

Background:

  • Named Data Networking (NDN) faces challenges in microservice-centric in-network computation, specifically with interest aggregation and Pending Interest Table (PIT) lifetime management.
  • Existing NDN aggregation methods, based solely on interest names, can lead to false aggregations due to varying input parameters.
  • Default PIT timers are insufficient for microservice computations with large input sizes, causing potential computation failures and Quality of Service (QoS) degradation.

Purpose of the Study:

  • To introduce MIA-NDN, a novel approach for microservice-centric interest aggregation in Named Data Networking.
  • To address the limitations of vanilla NDN aggregation and PIT lifetime management in microservice-centric environments.
  • To improve the efficiency and reliability of in-network computation for microservices.

Main Methods:

  • Designed microservice-centric interest-naming for name-based communication.
  • Developed a robust interest aggregation mechanism considering interest name, parameter counts, and values.
  • Implemented a dynamic PIT timer mechanism adapting to input size to prevent PIT entry losses.

Main Results:

  • MIA-NDN effectively performs interest aggregation by considering both interest names and their specific input parameters, avoiding false aggregations.
  • The dynamic PIT timer mechanism successfully prevents PIT entry losses for computations exceeding default timer values.
  • Extensive simulations demonstrate MIA-NDN's superior performance in microservice-centric interest aggregation, microservice satisfaction rate, and reduced communication overhead compared to benchmark schemes.

Conclusions:

  • MIA-NDN offers a significant improvement for microservice-centric in-network computation within Named Data Networking.
  • The proposed aggregation and dynamic PIT management strategies enhance reliability and efficiency, upholding application QoS.
  • MIA-NDN presents a viable solution for overcoming current challenges in NDN-based microservice architectures.