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Xuehai Zhang

Publications and source records attributed to Xuehai Zhang.

3 recordsLinked to original sources

ImmerseGen: Agent-Guided Immersive World Generation with Alpha-Textured Proxies

Automating immersive VR scene creation remains a primary research challenge. Existing methods typically rely on complex geometry with post-simplification, resulting in inefficient pipelines or limited realism. In this paper, we introduce ImmerseGen, a novel agent-guided framework for compact and photorealistic world generation that decouples realism from exhaustive geometric modeling. ImmerseGen represents scenes as hierarchical compositions of lightweight geometric proxies with synthesized RGBA textures, facilitating real-time rendering on mobile VR headsets. We propose terrain-conditioned texturing for base world generation, combined with context-aware texturing for scenery, to produce diverse and visually coherent worlds. VLM-based agents employ semantic grid-based analysis for precise asset placement and enrich scenes with multimodal enhancements such as visual dynamics and ambient sound. Experiments and real-time VR applications demonstrate that ImmerseGen achieves superior photorealism, spatial coherence, and rendering efficiency compared to existing methods.

cs.GR

Performance Analysis of the Globus Toolkit Monitoring and Discovery Service, MDS2

Monitoring and information services form a key component of a distributed system, or Grid. A quantitative study of such services can aid in understanding the performance limitations, advise in the deployment of the monitoring system, and help evaluate future development work. To this end, we examined the performance of the Globus Toolkit(reg. trdmrk) Monitoring and Discovery Service (MDS2) by instrumenting its main services using NetLogger. Our study shows a strong advantage to caching or prefetching the data, as well as the need to have primary components at well-connected sites.

cs.DC

A Performance Study of Monitoring and Information Services for Distributed Systems

Monitoring and information services form a key component of a distributed system, or Grid. A quantitative study of such services can aid in understanding the performance limitations, advise in the deployment of the systems, and help evaluate future development work. To this end, we study the performance of three monitoring and information services for distributed systems: the Globus Toolkit's Monitoring and Discovery Service (MDS), the European Data Grid Relational Grid Monitoring Architecture (R-GMA), and Hawkeye, part of the Condor project. We perform experiments to test their scalability with respect to number of users, number of resources, and amount of data collected. Our study shows that each approach has different behaviors, often due to their different design goals. In the four sets of experiments we conducted to evaluate the performance of the service components under different circumstances, we found a strong advantage to caching or prefetching the data, as well as the need to have primary components at well connected sites due to high load seen by all systems.

cs.PF