networking | UCSC OSPO

Network Simulation Bridge • Enabling Interactive Network Models

Wed, 28 Jan 2026 00:00:00 +0000

The Network Simulation Bridge – NSB – is a network co-simulation framework that bridges together applications and network simulators. It enables students, researchers, and developers to prototype their applications and systems on simulated networks. It consists of a message server and client endpoint interfaces which together form a bridge, routing application message payloads through the network simulator. NSB is designed to be extensible through modular interfaces that serve to allow users to contribute new features and modules that suit evolving and emerging use cases. NSB is developed to be application-, network simulator-, and platform-agnostic so that users and developers are empowered to integrate any application front-end with any network simulator back-end, providing versatility and flexibility when used alongside other tools in larger systems and applications.

NSB was created in-house by the Inter-Networking Research Group and is now being developed into a more full-featured open-source tool and ecosystem in partnership with the UCSC OSPO and as part of the NSF Pathways to Enable Open-Source Ecosystems program. In this transition to a more polished and feature-rich product, the next phase of NSB development will involve the engineering of new quality-of-life features, testing and iteration of the core tool itself, and user-centric refinement via implementation in interdisciplinary system models.

Develop a User-Centric Website for NSB

Topics: Web Development Dynamic Updates UX
Skills: web development experience, good communicator, (HTML/CSS), (Javascript)
Difficulty: Moderate
Size: Large
Mentors: Harikrishna Kuttivelil

Develop a clean and welcoming landing page and website for the project. The organization needs to reflect the needs of both users and potential project contributors. This website will be the first impression for people new to the project and should

Specific tasks:

Work with mentors on understanding the context of the project and the expected needs of the users.
Port relevant documentation and tutorials from the repository page, ensuring updates in the repository are reflected in the website.
Study existing open source product websites and draw insights to include in our own design.
Design the structure of the website according to best OS, visual design, and accessibility design practices.
Include visual content that showcases NSB integration and testimonials (if applicable).

Improve the User Experience of NSB

Topics: Software Engineering User-Centric Development Visualization UI/UX Documentation
Skills: package management, toolchain implementation, process automation, technical writing, (visualization), (bash), (Python), (C++)
Difficulty: Moderate
Size: Medium
Mentors: Harikrishna Kuttivelil

Our goal has always been to keep NSB streamlined and out of the way of the users and developers. In line with that, we want our tool to be easily available and installable, and we want the experience of using it to feel minimal and non-intrusive while providing sufficient observability of NSB’s internals for those who want it.

Specific tasks:

Work with mentors and potential users on identifying aspects of the user experience that can refined for better quality-of-life experiences.
Verify and iterate on existing software packaging methods for NSB to ensure that tool setup is stress-free.
Refine and update existing documentation and tutorials to reflect improvements in the setup, installation, and usage processes.
Work with mentors and other contributors to work backwards from what the user wants to see to design the user interface.
Work with other contributors (see below) to develop a Network-in-a-Box experience with NSB.

Create a Network-in-a-Box Experience with NSB

Topics: Software Engineering, Simulation, System Modeling, System Design, Visualization, UI/UX
Skills: software integration and interfacing, toolchain implementation, process automation, C++, (visualization), (LLM-enabled code generation), (technical writing)
Difficulty: Challenging
Size: Large
Mentors: Harikrishna Kuttivelil

NSB was originally designed for networking graduate students to interface with application-layer programs. But since then, there’s been more of an appetite for a simpler network-in-a-box approach that would allow users to quickly deploy baseline or generated network simulations that are ready for use with NSB.

Specific tasks:

Learn how to use one of the major open-source network simulators (ns3 or OMNeT++).
Work with mentors in designing a simpler, minimal user experience of operating NSB.
Develop tools to automatically create network simulations given input parameters (type of network, number of nodes, description of infrastructure).
Create documentation aimed at new users.
Implement or embed network visualizations to enrich the user experience.

Implement Networked System Models to Evaluate Quality of NSB

Topics: System Modeling Simulation System Design Software Development Product Testing
Skills: software integration, good communication, qualitative research, (proficiency in Python and/or C++), (processing scientific and technical literature)
Difficulty: Challenging
Size: Large
Mentors: Harikrishna Kuttivelil

NSB is a relatively new tool and has not been extensively tested outside of the core contributors, who know a bit too much about the tool. We need to better understand what external user and contributor experience will be like, and the best way to do that is to start developing with NSB to build models of connected systems, i.e., sensor networks, smart homes, smart farms, etc.

Specific tasks:

Research academic literature and relevant works to identify relevant distributed applications to model.
Work with mentors and collaborators to plan implementation of selected system models.
Track and report issues and concerns in quality-of-life experiences, critical errors, or difficulties.
Work with mentors and contributors to address issues and concerns.
Refine and update existing documentation and tutorials to reflect improvements in the setup, installation, and usage processes.
Work with other contributors (see below) in reviewing and cross-referencing model implementations.

Model Autonomous Vehicle Networks to Drive New Feature Development in NSB

Topics: System Modeling Simulation System Design Software Development
Skills: requirement-based software design, message parsing interfaces, server-client communication, (proficiency in Python and/or C++), (processing scientific and technical literature)
Difficulty: Challenging
Size: Large
Mentors: Harikrishna Kuttivelil

NSB today serves its named purpose – message relaying. However, modeling complex systems can sometimes involving synchronizing other simulation features, like mobility when dealing with vehivle networks. Implementing a generic layer of being able to synchronize user-defined features across endpoints would be a powerful, enabling feature in NSB. In the process, we may also uncover opportunities for improving the NSB developer experience.

Specific tasks:

Research academic literature and relevant works to identify and design potential autonomous vehicle network models.
Work with mentors and collaborators to iterate on system designs to ensure it serves the purpose of furthering NSB development.
Help mentors design and develop the new feature synchronization feature in NSB, driven by the autonomous vehicle system model.
Develop and iterate feature synchronization, using mobility as the synchronized feature.
Create documentation and tutorials to serve as resources for future users, contributors, and developers.
Work with other contributors (see above) in reviewing and cross-referencing model implementations.

Benchmarking the Future: Exploring High-Speed Scientific Data Streaming

Sun, 06 Jul 2025 00:00:00 +0000

Hello! I’m Ankit Kumar, and although I’m a bit late with this introduction post due to a busy period filled with interviews and college formalities, I’m excited to share my journey with the OSRE 2025 program and the fascinating world of scientific data streaming.

About Me

I’m currently pursuing my BTech degree at the Indraprastha Institute of Information Technology Delhi (IIIT Delhi) and am based in New Delhi, India. As I approach graduation, I’m thrilled to be working on a project that perfectly aligns with my interests in systems and networking.

My passion for technology has led me through various experiences:

Software Developer at CloudLabs: I worked at a platform founded by Dr. Sumit J Darak that facilitates remote access to actual FPGA boards on a slot basis, making hardware experimentation accessible to students worldwide.
Data Mining Intern at TaskTracker.in: This experience gave me insights into large-scale data processing and analysis.
Undergraduate Researcher: Currently working under Dr. Mukulika Maity on benchmarking QUIC and TCP protocols across different environments including bare metal, virtual machines, and containers.

I chose this OSRE project because it represents an incredible opportunity to work with some of the best minds in the industry at Argonne National Laboratory (ANL) while diving deep into cutting-edge networking technologies.

My Project: SciStream Performance Analysis

As part of the SciStream project, I’m focusing on two critical aspects of high-performance scientific data streaming:

1. TCP/UDP Performace Benchmarking

I’m conducting comprehensive benchmarking of SSH and TLS tunnels using various open-source tools and parameters. This work is crucial for understanding how different protocols and their overhead impact the performance of real-time scientific data streaming. The goal is to provide researchers with evidence-based recommendations for moving/processing their high-speed data transfers without compromising performance.

2. QUIC Proxy Exploration

I’m exploring different QUIC proxy implementations to understand their potential advantages over traditional TCP+TLS proxies in scientific workflows. QUIC, the protocol that powers modern web applications like YouTube, offers promising features for scientific data streaming, but comprehensive benchmarking is needed to validate its benefits.

Working with Cutting-Edge Testbeds

Currently, I’m conducting experiments using both the FABRIC testbed and ESnet testbed. These platforms provide access to real high-speed network infrastructure, allowing me to test protocols and configurations under realistic conditions that mirror actual scientific computing environments.

The Team Experience

These past two weeks have been incredibly rewarding, working alongside:

Alain Zhang - my project mate from UC San Diego, cool guy.
Flavio Castro - My project mentor and manager, goto person for my issues. currently at anl as a research development software engineer.
Joaquin Chung - Super mentor, brains behind the project. His guidance on the project is super valubale.
Rajkumar Kettimuthu - Lead Scientist in our project whose comments on our paper critique are invaluable.
Seena Vazifedunn - Graduate Research Assistant at University of Chicago. He asks very relevant and important questions during our report presentation and his feedbacks are very insightful.

The collaborative nature of this project has been fantastic, combining perspectives from different institutions and backgrounds to tackle complex networking challenges.

Stay tuned for updates!

This work is part of the SciStream project at Argonne National Laboratory, reimagining how scientific data moves across modern research infrastructure.

Architecting the Future of Scientific Data: Multi-Site Streaming Without Compromise

Mon, 10 Feb 2025 00:00:00 +0000

Data is generated at ever-increasing rates, yet it’s often processed more slowly than it’s collected. Scientific instruments frequently operate below their full capacity or discard valuable data due to network bottlenecks, security domain mismatches, and insufficient real-time processing capabilities.

SciStream reimagines how scientific data moves across modern research infrastructure by providing a framework for high-speed (+100Gbps) memory-to-memory streaming that doesn’t compromise on security. Whether connecting scientific instruments to analysis clusters or bridging across institutional boundaries, SciStream provides the foundation for next-generation scientific workflows.

Building on our published research, we’re now expanding the framework’s capabilities through open-source development and community collaboration. These projects offer an opportunity for students to gain hands-on experience with cutting-edge networking and security technologies used in high-performance computing (HPC), cloud infrastructure, and large-scale scientific experiments.

SciStream-SecureBench: A Framework for Benchmarking Security Protocols in Scientific Data Streaming

Project Idea Description:

Topics: Security Protocols, Network Performance, Data Streaming, Reproducibility, High-throughput Computing
Skills: Python, Scripting, Linux, Network Protocol Analysis, Containers, Benchmarking tools
Difficulty: Medium
Size: Large (350) hours
Mentors: Joaquin Chung, Flavio Castro

Ever wondered why large scientific experiments need to move massive amounts of data securely and quickly? While TLS and SSH are standard for secure data transfer, there’s a surprising lack of benchmarks that evaluate their performance in high-speed scientific workflows. This project aims to fill this gap by developing a benchmarking suite that measures how different security configurations impact real-time scientific data streaming.

Specific Tasks of the Project Include

Developing benchmarking tools that measure key security performance metrics like handshake latency, throughput stability, and computational overhead.
Running real-world experiments on research testbeds (Chameleon, FABRIC) to simulate scientific data patterns.
Automating comparative analysis between TLS and SSH, with focus on streaming-specific metrics like time-to-first-byte and sustained throughput.
Documenting best practices for security protocol selection in high-performance streaming.

Why This Matters for Your Career

Gain expertise in network security and performance analysis, highly valued in cybersecurity, cloud computing, and HPC.
Work on a real research challenge with potential for publication.

SciStream-StreamBench: Comparative Analysis of Scientific Streaming Frameworks

Project Idea Description:

Topics: Data Streaming Protocols, Network Performance, Benchmarking, Distributed Systems, Real-time Computing
Skills: Python, ZeroMQ, EPICS/PVAccess, Linux, Performance Analysis, Visualization
Difficulty: Medium
Size: Large (350) hours
Mentors: Joaquin Chung, Flavio Castro

Scientific experiments generate enormous amounts of streaming data, but how do we choose the best framework for handling it efficiently? Despite the widespread use of ZeroMQ and PVApy, there’s little systematic benchmarking comparing their performance. This project will develop real-world benchmarks to evaluate how different frameworks handle scientific data in high-speed environments.

The Specific Tasks of the Project Include

Designing benchmarking methodologies to assess key performance metrics like synchronization overhead, time-to-first-data, and throughput stability.
Developing a test harness that simulates real-world streaming conditions (network variability, concurrent streams, dynamic data rates).
Running experiments on Chameleon and FABRIC testbeds.
Automating data collection and visualization to highlight performance trends.
Documenting best practices and framework-specific optimizations.

Why This Matters for Your Career

Get hands-on experience with real-time data processing and network performance analysis.
Learn benchmarking techniques useful for distributed systems, cloud computing, and high-performance networking.

SciStream-QUIC: Next-Generation Proxy Architecture for Scientific Data Streaming

Project Idea Description:

Topics: QUIC Protocol, Network Proxies, Performance Analysis, Protocol Design, Hardware Acceleration
Skills: Python/C++, Network Programming, QUIC (quiche/aioquic), Linux, Performance Analysis
Difficulty: Hard
Size: Large (350) hours
Mentors: Joaquin Chung, Flavio Castro

Ever wondered how YouTube loads videos faster than traditional web pages? That’s because of QUIC, a next-generation protocol designed for speed and security. Initial evaluations of federated streaming architectures (INDIS'22 paper) suggest potential benefits of QUIC, but comprehensive benchmarking is needed. This project explores whether QUIC-based proxies can outperform traditional TCP+TLS proxies for scientific data streaming, potentially revolutionizing how researchers move large datasets.

The Specific Tasks of the Project Include

Developing a QUIC-based proxy optimized for scientific workflows.
Running benchmarks to compare QUIC vs. traditional TLS proxies.
Investigating hardware encryption offloading for QUIC and TLS.
Designing reproducible experiments using Chameleon and FABRIC testbeds.
Documenting best practices for deploying QUIC proxies in HPC environments.

Why This Matters for Your Career

Gain experience in cutting-edge networking protocols used in cloud computing (Google, Cloudflare, etc.).
Learn about hardware acceleration and its role in high-speed networking.

SciStream-Auth: Modern Authentication and User Interface for Scientific Data Streaming

Project Idea Description:

Topics: Authentication Systems, UI/UX Design, Security Integration, Scientific Computing
Skills: Python, Web Development (React/Vue), OAuth 2.0/SAML, Security Analysis
Difficulty: Medium
Size: Large (350) hours
Mentors: Joaquin Chung, Flavio Castro

Not a security expert? You can still contribute by designing an interactive front-end!

In today’s scientific computing landscape, authentication and user experience often act as barriers to adoption rather than enabling seamless collaboration. While SciStream excels at high-speed data transfer, its reliance on a single authentication provider and command-line interface limits its accessibility. This project aims to transform SciStream into a more versatile platform by implementing a modular authentication system and developing an intuitive graphical interface.

By expanding beyond Globus Auth to support multiple authentication frameworks, we can enable broader adoption across different scientific communities while maintaining robust security. Coupled with a modern GUI that visualizes real-time streaming activity, this enhancement will make SciStream more accessible to researchers—allowing them to focus on their science rather than wrestling with complex configurations.

This project will design a user-friendly interface that makes secure scientific data streaming as intuitive as using a cloud storage service. You’ll also gain hands-on experience with authentication methods used by industry leaders like Google and Facebook, while directly improving access to scientific data.

The Specific Tasks of the Project Include

Design and implementation of a pluggable authentication system supporting multiple providers (OAuth 2.0, SAML, OpenID Connect, certificate-based auth)
Development of a modern, responsive GUI using web technologies that provides real-time visualization of system status
Creation of comprehensive security testing protocols to validate the authentication implementations
Implementation of session management and secure credential handling within the GUI
Design of an intuitive interface for managing streaming configurations and monitoring data flows
Creation of documentation and examples to help facilities integrate their preferred authentication mechanisms

Evaluating congestion controls past and future

Wed, 21 Feb 2024 00:00:00 +0000

Topics: computer networks, congestion control, reproducibility
Skills: Python, Bash scripting, Linux, computer network performance evaluation
Difficulty: Medium
Size: Large (350 hours)
Mentors: Fraida Fund and Ashutosh Srivastava

Project Idea Description

In computer networks, congestion control protocols play an outsize role in determining our experience with networked applications. New congestion control algorithms are regularly proposed by researchers to improve throughput and latency performance, adapt to new types of networks, and align more closely with the needs of new applications.

However, our understanding of the benefits of a new congestion control protocol depends to a large extent on the evaluation - the network topology, the network delay and throughput, the type of flow, the type of competing traffic - and there is no single standard way to evaluate a congestion control protocol. The Pantheon project (which is no longer supported) sought to fill this gap somewhat and address the problem of reproducibility of congestion control results, but their approach is not easily adapted to evaluation scenarios representative of new types of applications or networks. Nor is it capable of representing the evaluation scenarios in most published results related to congestion control.

The goal of this project, therefore is to create an evaluation suite for congestion control protocols that can be used to reproduce existing congestion control results in the academic literature, and to evaluate new protocols under similar evaluation conditions, and to be easily extended to new scenarios. An “evaluation scenario” includes:

a Python notebook to realize the network topology on the FABRIC and/or Chameleon testbed, and configure the network characteristics,
scripts to generate the data flow(s) needed for the evaluation,
and scripts to capture data from the experiment and visualize the results.

Writing a successful proposal for this project

To write a good proposal for this project, you should review the most influential papers on TCP congestion control, and especially those related to TCP protocols that are available in the Linux kernel.

Use your findings to explain what your proposed evaluation suite will include (what network topologies, what flow generators), and justify this with reference to the academic literature. Also indicate which specific results you expect to be able to reproduce using this suite (e.g. include figures from influential papers showing evaluation results! with citation, of course).

You can also take advantage of existing open source code that reproduces a congestion control result, e.g. Replication: When to Use and When Not to Use BBR, or Some of the Internet may be heading towards BBR dominance: an experimental study.

Github link

There is no pre-existing Git repository for this project - at the beginning of the summer, the contributor will create a new repository for this project.

Project Deliverables

“Packages” of evaluation scenarios that can be used to evaluate a congestion control algorithm implemented in the Linux kernel
Trovi artifacts for realizing each evaluation scenario on Chameleon

Adaptive Load Balancers for Low-latency Multi-hop Networks

Mon, 07 Nov 2022 10:15:56 -0700

This project aims at designing efficient, adaptive link level load balancers for networks that handle different kinds of traffic, in particular networks where flows are heterogeneous in terms of their round trip times. Geo distributed data centers are one such example. With the large-scale deployments of 5G in the near future, there will be even more applications, including more bulk transfers of videos and photos, augmented reality applications and virtual reality applications which take advantage of 5G’s low latency service. With the development and discussion about Web3.0 and Metaverse, the network workloads across data centers are only going to get more varied and challenging. All these add to heavy, bulk of data being sent to the data centers and over the backbone network. These traffic have varying quality of service requirements, like low latency, high throughput and high definition video streaming. Wide area network (WAN) flows are typically data heavy tasks that consist of backup data taken for a particular data center. The interaction of the data center and WAN traffic creates a very interesting scenario with its own challenges to be addressed. WAN and data center traffic are characterized by differences in the link utilizations and round trip times. Based on readings and literature review, there seems to be very little work on load balancers that address the interaction of data center and WAN traffic. This in turn motivates the need for designing load balancers that take into account both WAN and data center traffic in order to create high performance for more realistic scenarios. This work proposes a load balancer that is adaptive to the kind of traffic it encounters by learning from the network conditions and then predicting the optimal route for a given flow.

Through this research we seek to contribute the following :

Designing a load balancer, that is adaptive to datacenter and WAN traffic, and in general can be adapted to varied traffic conditions
Real time learning of the network setup and predicting optimal paths
Low latency, high throughput and increased network utilization deliverables

Adaptive, Dynamic Load Balancing for data center and WAN traffic

Topics: ‘data center networking’, TCP/IP stack’, ‘congestion control’, ’load balancing’
Skills: C++, python, linux ; experience with network simulators would be helpful
Difficulty: moderate/ challenging
Size: Medium or Large (175 or 350 hours)
Mentors: Katia Obraczka,Abdul Kabbani, Lakshmi Krishnaswamy

Specific tasks:

Understanding the OMNeT++ network simulator and creating simple networks and data center topologies to understand the simulation environment.
Implementing existing load balancers on OMNeT++ and exploring the effect of different features of the load balancers with data center traffic and WAN traffic.
Finding and testing out WAN specific traffic that may exist, like video streaming traffic, large database queries etc.
Working with the mentors on developing a learning-based load balancer framework that learns from past sample traffic, network conditions, to adapt dynamically to current network conditions.

Efficient Communication with Key/Value Storage Devices

Sun, 27 Feb 2022 00:00:00 +0000

Network key value stores are used throughout the cloud as a storage backends (eg AWS ShardStore) and are showing up in devices (eg NVMe KV SSD). The KV clients use traditional network sockets and POSIX APIs to communicate with the KV store. An advancement that has occurred in the last 2 years is a new kernel interface that can be used in lieu of the POSIX API, namely io_uring. This new interface uses a set of shared memory queues to provide for kernel-to-user communication and permits zero copy transfer of data. This scheme avoids the overhead of system calls and can improve performance.

Implement `io_uring` communication backend

Topics: performance, I/O, network, key-value, storage
Difficulty: Medium
Size: Medium or large (120 or 150 hours)
Mentors: Philip Kufeldt (Seagate), Aldrin Montana (UC Santa Cruz) Contributor(s): Manank Patel

Seagate has been using a network-based KV HDD as a research vehicle for computational storage. This research vehicle uses open-source user library that implements a KV API by sending network protobuf-based RPCs to a network KV store. Currently it is implemented with the standard socket and POSIX APIs to communicate with the KV backend. This project would implement an io_uring communication backend and compare the results of both implementations.

networking | UCSC OSPO

Network Simulation Bridge • Enabling Interactive Network Models

Develop a User-Centric Website for NSB

Improve the User Experience of NSB

Create a Network-in-a-Box Experience with NSB

Implement Networked System Models to Evaluate Quality of NSB

Model Autonomous Vehicle Networks to Drive New Feature Development in NSB

Benchmarking the Future: Exploring High-Speed Scientific Data Streaming

About Me

My Project: SciStream Performance Analysis

1. TCP/UDP Performace Benchmarking

2. QUIC Proxy Exploration

Working with Cutting-Edge Testbeds

The Team Experience

Architecting the Future of Scientific Data: Multi-Site Streaming Without Compromise

SciStream-SecureBench: A Framework for Benchmarking Security Protocols in Scientific Data Streaming

Specific Tasks of the Project Include

Why This Matters for Your Career

SciStream-StreamBench: Comparative Analysis of Scientific Streaming Frameworks

The Specific Tasks of the Project Include

Why This Matters for Your Career

SciStream-QUIC: Next-Generation Proxy Architecture for Scientific Data Streaming

The Specific Tasks of the Project Include

Why This Matters for Your Career

SciStream-Auth: Modern Authentication and User Interface for Scientific Data Streaming

The Specific Tasks of the Project Include

Evaluating congestion controls past and future

Adaptive Load Balancers for Low-latency Multi-hop Networks

Adaptive, Dynamic Load Balancing for data center and WAN traffic

Efficient Communication with Key/Value Storage Devices

Implement io_uring communication backend

Implement `io_uring` communication backend