Distributed Systems are commonly built using a set of standard assumptions: we assume that message delays are unbounded, that any packet can be lost in the network, and that clocks cannot be closely synchronized. On the one hand, these conservative assumptions result in robust systems that can operate reliably in a wide variety of conditions. On the other hand, they also force the system to do a lot of complex ad-hoc coordination and thus limit the performance it can achieve. In this paper, we take a look at what lies beyond this standard model. We observe that, on modern hardware in a single-tenant data center, distributed systems are able to closely coordinate and essentially “run like clockwork” with very little effort. If we are willing to additionally rule out some worst-case failure scenarios, this results in a large performance improvement, both in practice and even in theory. We demonstrate this effect using state-machine replication (SMR) as a case study: our SMR protocol, Watchmaker, exceeds the throughput of state-of-the-art algorithms by two orders of magnitude, and it requires only half as many replicas to tolerate the same number of faults.
@article{lu2026nineswatch,title={Running Distributed Systems Like Clockwork},author={Newatia, Karan and Gifford, Robert and Lu, Qingjie and Haeberlen, Andreas and Phan, Linh Thi Xuan},journal={Proceedings of the 1st New Ideas in Networked Systems: (NiNES '26)},year={2026},doi={10.4230/OASIcs.NINeS.2026.26}}
2025
HotNets ’25
Modeling Metastability
Ali
Farahbakhsh, Andreas
Haeberlen, Qingjie
Lu, and
3 more authors
Proceedings of the 24th ACM Workshop on Hot Topics in Networks (HotNets ’25), 2025
Recently, there has been increasing concern about a new failure mode in data-center systems: when there is an external shock, such as a sudden load spike or some machine failures, systems will sometimes respond with reduced throughput - but, in contrast to a traditional overload situation, the throughput does not recover once the external shock disappears, and remains permanently degraded. This phenomenon has been called a metastable failure. In this paper, we sketch a simple model that could help to explain how and why metastability arises. We also show how our model can be used to predict the presence or absence of metastable states in a given system.
@article{lu2025modeling,title={Modeling Metastability},author={Farahbakhsh, Ali and Haeberlen, Andreas and Lu, Qingjie and Alvisi, Lorenzo and van Renesse, Robbert and Gahtan, Shir Cohen},journal={Proceedings of the 24th ACM Workshop on Hot Topics in Networks (HotNets '25)},year={2025},doi={10.1145/3772356.3772426},note={<b>Author Names in Alphabetic Order</b>}}
2022
ISET
Neural Network-Based Approaches for Aspect-Based Sentiment Analysis
Qingjie
Lu
Highlights in Science, Engineering and Technology, 2022
Proceedings of the 4th International Conference on Information Science and Electronic Technology
The research of Aspect-based Sentiment Analysis which is a process that has a more specific focus than general sentiment analysis is trending upwards in numbers. Stemming from Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs), novel approaches introduced new components like Graph Convolutional Networks (GCNs) and Transformers that improved the overall accuracy dramatically. Along with summarizing the models, the focus of this survey will be on comparing the several novel methods. Although this paper found that Dependency graph enhanced dual-transformer network (DGEDT) coupled with Bidirectional Encoder Representations from Transformers (BERT) is the best performing model thus far, this paper also identified challenges that needed to be addressed in order to better evaluate current and future models.
@article{lu2022aspectbased,title={Neural Network-Based Approaches for Aspect-Based Sentiment Analysis},author={Lu, Qingjie},journal={Highlights in Science, Engineering and Technology},volume={12},pages={222--229},year={2022},doi={10.54097/hset.v12i.1457},url={https://drpress.org/ojs/index.php/HSET/article/view/1457},note={Proceedings of the 4th International Conference on Information Science and Electronic Technology}}