This paper presents an N-ary Gaussian Model for predicting endpoint distributions in pointing tasks across task scenarios. Built on the foundational principles of the Ternary Gaussian model series, our model framework allows researchers to define parameter constraints and automatically refine model combinations, eliminating the need for predefined equations based on data analysis. We utilize the Bayesian Information Criterion (BIC) for model selection, ensuring simplicity while maintaining predictive accuracy. We conducted a comparative analysis against published baselines across 7 diverse datasets, covering 1D, 2D, and 3D tasks, different input modalities, different display devices, and time-constrained scenarios, demonstrating the robustness and generalization of the N-ary Gaussian Model. The N-ary Gaussion model offers an automated solution for modeling pointing uncertainty, and also incorporates cross output device, input modality, and temporal constraint factors into spatial pointing uncertainty modeling for the first time.

Virtual reality (VR) allows users to observe and manipulate 3D geometry from multiple viewpoints. Most VR selection work, however, optimizes techniques for selecting entire objects. Selecting a single face on a polyhedron remains underexplored and is more challenging because the interaction must act on a local component while preserving the object's global structure. We introduce a design space tailored to this task with three dimensions: viewing strategy, disambiguation consistency, and interaction metaphor. Guided by this space, we design eight freehand techniques for polyhedral face selection. A within-subjects study with 16 participants evaluates these techniques across polyhedral complexity (two radii; face counts 4, 6, and 12). The results identify three complementary top techniques, reveal tradeoffs between viewing choices and geometric preservation, and yield concrete guidelines for matching techniques to target geometry and task demands. A follow-up study with complex, realistic models confirms the robustness and practical usability of the three techniques. Together, these contributions shift attention from whole object selection to precise component selection in VR and provide actionable methods for 3D modeling, assembly, and texturing.

Piloting requires users to control and navigate the aircraft within a designated pathway, with a controller that utilizes two joysticks to control the aircraft. This task is representative of various daily and gaming scenarios, such as controlling the aircraft to capture the photo or navigating an object in a game from the start position to the end via a trajectory. In this work, we explore a model (based on the Steering Law) that predicts the piloting time required in spatial-constrained environments. Thus, two user studies are conducted to help us understand the relationship between path complexity (curvature) and spatial constraints (width and height). According to the results, we propose a model that can achieve $52.6 \%$ and $60.6 \%$ improvement in R-square and the Akaike Information Criterion (AIC), respectively. Next, an additional study was conducted to further verify the performance and efficiency of our proposed model with the change of movement direction and orientation. Our model and experimental results can benefit both game and interface designers of applications that require controlling moving objects along specific trajectories in virtual reality environments.

This paper introduces Natto, a geo-distributed database system that supports transaction prioritization. Instead of having each shard process transactions in their arrival order, Natto leverages network measurements to estimate the transaction arrival time at each shard, and assigns a timestamp to the transaction based on its arrival time to the furthest shard. These timestamps establish a global ordering of transactions, and introduces opportunities to selectively abort pending low-priority transactions that conflict with a high-priority transaction, or even preempt transactions that are already partially prepared. Our experiments on both Microsoft Azure and a local cluster show that Natto's tail latency for high-priority transactions are significantly lower than the tail latencies of Carousel and TAPIR, which are the current state-of-the-art in geo-distributed transaction processing systems.

This paper introduces Domino, a low-latency state machine replication protocol for wide-area networks. Domino uses network measurements to predict the expected arrival time of a client request to each of its replicas, and assigns a future timestamp to the request indicating when the last replica from the supermajority quorum should have received the request. With accurate arrival time predictions and in the absence of failures, Domino can always commit a request in a single network roundtrip using a Fast Paxos-like protocol by ordering the requests based on their timestamps.

In this paper we introduce SpecRPC, a speculative execution framework that allows applications to concurrently execute dependent operations both locally and through remote procedure calls. The framework tracks dependencies among non-speculative and speculative operations and ensures that incorrect speculations do not affect the correctness of applications that follow our suggested design pattern. By using speculation to parallelize dependent operations, SpecRPC can significantly reduce application latency even if only a fraction of the results can be correctly speculated. We evaluate SpecRPC by using it to implement Replicated Commit, a low-latency distributed transaction commit protocol for geo-replicated database systems. Our evaluation results show that, compared to RPC frameworks that sequentially execute dependent operations, SpecRPC can reduce the average transaction completion time of Replicated Commit by 58%.

The trend towards global applications and services has created an increasing demand for transaction processing on globally-distributed data. Many database systems, such as Spanner and CockroachDB, support distributed transactions but require a large number of wide-area network roundtrips to commit each transaction and ensure the transaction's state is durably replicated across multiple datacenters. This can significantly increase transaction completion time, resulting in developers replacing database-level transactions with their own error-prone application-level solutions.