Future Generation Computer Systems
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We propose NetICE9, a novel landmark-less method for embedding RTTs into virtual spaces. NetICE9 is inspired by VIVALDI, the most commonly used landmark-less approach. VIVALDI chooses its neighbors randomly and optimizes only towards one neighbor at a time. With NetICE9, we propose a solution to those drawbacks. NetICE9 significantly improves both the stability of the simulation and the precision of how RTTs are embedded into a virtual space. Our evaluation based on RTTs measured in the Internet show that NetICE9 significantly outperforms VIVALDI in terms of stability and precision of RTT prediction. NetICE9 improves RTT prediction also in comparison to GNP.