Prateek Jain

Prateek Jain

PhD Student in Computer Science | Specializing in Network Layer Protocols

I am a PhD candidate in Computer Science at Boston University, specializing in network communication and data transfer reliability. My research focuses on developing robust and efficient transport layer solutions, including a RINA-based Multi-Layer Error Detection (MLED) model, QUIC protocol evaluation for connection migration, and dynamic operator placement at the edge for real-time stream processing. Currently, I am a Research Intern at Google, working on assessing the performance of QUIC’s connection migration capabilities under diverse network conditions to enhance low-latency and stable communication. My projects, in collaboration with the National Science Foundation (NSF) and Google, aim to push the boundaries of modern networking, transport protocols, and edge computing.

Abraham Matta

Advisor: Dr. Abraham Matta

Dr. Abraham Matta is a Professor of Computer Science at Boston University and currently serves as a Program Director at the NSF. His research focuses on network protocols, architectures, and performance evaluation across various domains, including edge-cloud systems and wireless networks. He has published over 150 papers and received multiple prestigious awards, including the NSF CAREER award and several best-paper honors.

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Attended KNIT 10 held at Raleigh
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Attended IEEE ICNP 2024 held at Charleroi, Belgium
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Presentating MLED at KNIT 9 held at Kansas City
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Poster presentation with MLED team at KNIT 9 held at Kansas City
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Served as judge and mentor at HackMIT'24
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Certificate of mentoring and judging at HackMIT'24
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With MLED team after winning the best poster presentation at KNIT 7 held at Ohio
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Poster presentation at KNIT 7 at Ohio
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Best poster presentation certificate
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Received DG's commendation disc for exemplary work at CRPF
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Received DG's commendation certificate for exemplary work at CRPF
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Conferred with the Sword of Honour and the Home Minister's Cup for being adjudged the Best Trainee Officer during basic training at Central Reserve Police Force (CRPF)

Multi-Level Error Detection (MLED) Framework

MLED is a Recursive Inter-Network Architecture (RINA) based novel approach which utilizes in-network resources to significantly reduce the probability of undetected errors (UEP) during large-scale file transfers.

Learn more about MLED on the MLED Project Page.

Download MLED Programmer's Manual