Zhuangwei Kang

A Study of Publish/Subscribe Middleware Under Different IoT Traffic Conditions

https://dlnext.acm.org/doi/10.1145/3429881.3430109
Publish/Subscribe (pub/sub) semantics are critical for IoT applications due to their loosely coupled nature. Although OMG DDS, MQTT, and ZeroMQ are mature pub/sub solutions used for IoT, prior studies show that their performance varies significantly under different load conditions and QoS configurations, which makes middleware selection and configuration decisions hard. Moreover, the load conditions and role of QoS settings in prior comparison studies are not comprehensive and well- documented.
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2020
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A Comprehensive Performance Evaluation of Different Kubernetes CNI Plugins for Edge-based and Containerized Publish/Subscribe Applications

The growing number of data- and latency-sensitive Internet of Things (IoT) applications is posing significant challenges for the edge and cloud deployment of publish/subscribe services, which are required by these applications. Two independently developed technologies show promise in addressing these challenges. First, Kubernetes (K8s) provides a de-facto standard for container orchestration that can manage and scale distributed applications in the cloud.

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2021
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PDF icon ic2e_2021_industry_track_compressed.pdf

Performance Evaluation for Kubernetes-based DDS Applications

https://www.isis.vanderbilt.edu/

Kubernetes (K8s) provides a de-facto standard for container orchestration that can manage and scale distributed applications in the cloud. OMG’s Data Distribution Service (DDS), a standardized real-time, data-centric and peerto-peer publish/subscribe middleware, is being used in thousands of critical systems around the world. However, the feasibility of running DDS applications within K8s for latency-sensitive edge computing, and specifically the performance overhead of K8s’ network virtualization on DDS applications is not yet well-understood.

This project research the feasibility of running DDS applications on Kubernetes clusters under various use cases and deployment scenarios. We also evaluate the performance overhead of multiple popular container network interface(CNI) plugins installed on cloud/edge-based Kubernetes clusters.

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