Grand Challenge on Multi-site Parallel Downloading

This challenge is organised by ByteDance. At ByteDance, we have found that Multi-site Parallel Downloading (MPD) can effectively reduce the cost for video streaming services. Unlike the conventional on-demand streaming solutions that rely on DASH streaming from dedicated CDN servers, MPD tries to take advantage of the low cost computing resources available on the Internet. Such computing resources (i.e., set top boxes, smart home devices, idle servers, etc.), also called data nodes in our MPD system, usually offer adequate storage space, varying network bandwidth, limited computing capability, and unreliable availability. Even though one single data node cannot replace the dedicated CDN server to offer video streaming at the same quality and reliability, allowing the downloading program to connect simultaneously to multiple data nodes can potentially make up the performance gap. Therefore, tuning up the performance of MPD transport can help offload more traffic from CDN servers to less expensive MPD nodes and significantly bring down the overall streaming cost.

In this grand challenge, we provide the platform for contestants to design an MPD transport algorithm and test the algorithm performance in the real world network environment. For simplicity, we provide APIs for querying, connecting, downloading data from available data nodes. The contestants can focus on the design and implementation of the core transport algorithm, which is, in summary, to determine which data chunk should be requested from which data node at what time. The goal is to maximize the video downloading speed while minimizing the overall bandwidth usage. We have built a testing platform with over 5000 data node instances for performance evaluation. All data node instances run on the same computing devices that are actively used in the commercial ByteDance MPD streaming system serving Chinese customers. All submissions will be evaluated and ranked based on the actual performance score of downloading video content on our MPD test platform.

At the end of the Challenge, all teams will be ranked based on the evaluation metric score described on the grand challenge webpages. The top three performing teams will publish their algorithm in the conference proceedings and receive award certificates as well as cash prizes during the MMSys conference:

• First Prize: $3000
• Second Prize: $1300
• Third Prize: $700

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Submission Information:

• Challenge: Website URL
• Challenge release: Jan 31, 2023
• Code and local test platform release: Feb 15, 2023
• Final submission deadline: Apr 4, 2023 (hard deadline)
• Final results notification: Apr 10, 2023
• Paper camera-ready (for winning teams): Apr 17, 2023 (hard deadline)

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Organizing team (ByteDance):

• Shu Shi
• Haiping Wang
• Zhichen Xue
• Zhenhua Yu
• Yajie Peng
• Xiaofei Pang

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