科研之友
微信
新浪微博
Facebook
分享链接
摘要
Recent trends in science applications call for long-range and large-scale collaboration among laboratories and super-computing sites. Long gone are the days of entering data manually into a spreadsheet on a local workstation. The world's most powerful and ground-breaking experiments generate exabytes of information, which must be distributed to multiple labs for analysis and interpretation. Such trends reveal the unwavering importance of new communication paradigms, like multicasting and manycasting, which provide point-to-multipoint data transfers. Typically, these all-important mechanisms are provided at the optical layer, where split-capable cross-connects split input signals into multiple output signals all-optically. Unfortunately, some of the world's largest and most powerful networks do not have the hardware infrastructure to support such functionality, but allow for point-to-point communication exclusively. In such split-incapable (SI) networks, multicast and manycast must be provided as a logical overlay to the pre-existing and limited unicast infrastructure. In this paper, we present two overlay models for providing manycast support in SI networks: Manycasting with Drop at Member Node (MA-DMN) and Manycasting with Drop at Any Node (MA-DAN). Through the development of integer linear programs (ILPs) and heuristics, we evaluate these models in terms of both optimal solutions and efficient approximations for both small-scale and large-scale networks and consider both static and dynamic traffic scenarios. Our results demonstrate that despite a small tradeoff in additional complexity and delay from signal conversion to the optical domain, our models provide efficient utilization of network resources and greatly surpass the standard naive approach of establishing paths to every destination.
- 出版日期2016-2
