{"title":"分布式虚拟现实负载仿真与度量框架","authors":"H. Singh, D. Gračanin, K. Matkovič","doi":"10.1109/VR.2008.4480804","DOIUrl":null,"url":null,"abstract":"We describe a simple load-measure-model method for analyzing the scalability of distributed virtual environments (DVEs). We use a load simulator and three metrics to measure a DVE's engine with varying numbers of simulated users. Our load simulator logs in as a remote client and plays according to how users played during the conducted user study. Two quality of virtuality metrics, fidelity and consistency, describe the user's experience in the DVE. One engine performance metric provides the cycle time of the engine's primary loop. Simulation results (up to 420 users) are discussed.","PeriodicalId":173744,"journal":{"name":"2008 IEEE Virtual Reality Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Load Simulation and Metrics Framework for Distributed Virtual Reality\",\"authors\":\"H. Singh, D. Gračanin, K. Matkovič\",\"doi\":\"10.1109/VR.2008.4480804\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We describe a simple load-measure-model method for analyzing the scalability of distributed virtual environments (DVEs). We use a load simulator and three metrics to measure a DVE's engine with varying numbers of simulated users. Our load simulator logs in as a remote client and plays according to how users played during the conducted user study. Two quality of virtuality metrics, fidelity and consistency, describe the user's experience in the DVE. One engine performance metric provides the cycle time of the engine's primary loop. Simulation results (up to 420 users) are discussed.\",\"PeriodicalId\":173744,\"journal\":{\"name\":\"2008 IEEE Virtual Reality Conference\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE Virtual Reality Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VR.2008.4480804\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Virtual Reality Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VR.2008.4480804","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Load Simulation and Metrics Framework for Distributed Virtual Reality
We describe a simple load-measure-model method for analyzing the scalability of distributed virtual environments (DVEs). We use a load simulator and three metrics to measure a DVE's engine with varying numbers of simulated users. Our load simulator logs in as a remote client and plays according to how users played during the conducted user study. Two quality of virtuality metrics, fidelity and consistency, describe the user's experience in the DVE. One engine performance metric provides the cycle time of the engine's primary loop. Simulation results (up to 420 users) are discussed.