Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/9014
Title: | Comparative analysis of graphic contents rendering techniques in a multi-view system through agent-mediator based communication |
Authors: | Fahad Dr. AZHAR Muhammad Sajjad, Muhammad Mehmood, Irfan Kwon, Soon II Lee, Jong Weon Baik, Sung Wook |
Issue Date: | 2014 |
Source: | Fahad, Azhar, Muhammad., Sajjad, Muhammad., Mehmood, Irfan., Kwon, Soon II., Lee, Jong-Weon. & Baik, Sung-Wook (2014). Comparative analysis of graphic contents rendering techniques in a multi-view system through agent-mediator based communication. In Jeong, Young Sik, Park, Young Ho, Hsu, Ching Hsien (Robert), Park, James J. (Jong Hyuk) (Eds.). Ubiquitous information technologies and applications. CUTE 2013, Danang, Vietnam (pp. 573-579). Springer, Berlin, Heidelberg. |
Conference: | The 8th International Conference on Ubiquitous Information Technologies and Applications |
Abstract: | One of the major issues in mixed reality multi-agent systems is synchronization of display, which can adversely affect system performance and hinder user interaction. Real time response from the system cannot be achieved because of the aforementioned issues. If the content displayed on agents is complex and cannot be feasibly rendered on a single agent, then a better strategy is to divide the contents among multiple agents. In this way, only a fraction of the entire contents is rendered by each agent. In this paper, two alternative techniques for multi-agent based content management are proposed, namely, full contents on agents (FCOA) and partial contents on agents (PCOA). In FCOA, each agent in the multi-agent system renders all the contents and only a specific part of the contents is displayed depending upon the usage scenario. In PCOA the agents receive partial contents from the mediator. A comparative study has been presented in this paper to identify the pros and cons of each method |
Type: | Conference Paper |
URI: | http://hdl.handle.net/20.500.11861/9014 |
ISBN: | 9783642416705 9783642416712 |
DOI: | https://doi.org/10.1007/978-3-642-41671-2_73 |
Appears in Collections: | Applied Data Science - Publication |
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