Before moving to Princeton I was a member of the University of Southern California's Networked Systems Lab.
I received a B.A. in Mathematical Sciences from Rutgers University - Camden in 2016.
I am interested in distributed systems , including distributed databases, consistency, replicated state machines, fault tolerance, scalability, and networking in general.
I am actively seeking positions! Resume and email: chrischodsdon at gmail com.
Some recent services use a sequencer to simplify ordering operations on sharded data. The sequencer assigns each operation a multi-sequence number which explicitly orders the operation on each shard it accesses. Existing sequencers have two shortcomings. First, failures can result in some multi-sequence numbers never being assigned, exposing a noncontiguous multi-sequence, which requires complex scaffolding to handle. Second, existing implementations use single-machine sequencers, limiting service throughput to the ordering throughput of one machine.
We make two contributions. First, we posit that sequencers should expose our new contiguous multi-sequence abstraction. Contiguity guarantees every sequence number is assigned an operation, simplifying the abstraction. Second, we design and implement MASON, the first system to expose the contiguous multi-sequence abstraction and the first to provide a scalable multi-sequence. MASON is thus an ideal building block for consistent, scalable services. Our evaluation shows MASON unlocks scalable throughput for two strongly-consistent services built on it.
Scalable storage systems where data is sharded across many machines are now the norm for Web services as their data has grown beyond what a single machine can handle. Consistently reading data across different shards requires transactional isolation for the reads. Yet a Web service may read from its data store hundreds or thousands of times for a single page load and must minimize read latency to keep response times low. Examining the read-only transaction algorithms for many recent academic and industrial scalable storage systems suggests there is a tradeoff between their power—expressed as the consistency they provide and their compatibility with other types of transactions—and their latency.
We show that this tradeoff is fundamental by proving the SNOW Theorem, an impossibility result that states that no read-only transaction algorithm can provide both the lowest latency and the highest power. We then use the tight boundary from the theorem to guide the design of new read-only transaction algorithms for two scalable storage systems, COPS and Rococo. We implement our new algorithms and then evaluate them to demonstrate they provide lower latency for read-only transactions and to understand their impact on overall throughput.
"Stronger Abstractions and Performance Guarantees for Building Strongly Consistent Distributed Services"
Ph.D. Dissertation, Princeton University, May 2023.
Haonan Lu, Christopher Hodsdon, Khiem Ngo, Shuai Mu, Wyatt Lloyd. "The SNOW Theorem and Latency-Optimal Read-Only Transactions"
OSDI 2016, Savannah, GA, November 2-4, 2016.
[paper] [slides] [talk (Haonan Lu)]
e-mail: chrischodsdon at gmail com