## 1 Introduction  
Academic backbone networks have to address the particular requirements inherent in big scientific applications [1; 2; 3]. The amounts of data involved in big scientific research such as astronomy, high-energy physics, and nuclear fusion research are much larger than those of other research and educational applications, and networks must have huge bandwidths to carry it all. For instance, one very long baseline interferometry (eVLBI) project [4] needs an assured bandwidth of more than 2 Gbps per radio telescope in order to transfer the data from the telescopes to a central analysis device. Furthermore, it needs to use as geographically distant as possible radio telescopes in order to enhance the detection range, which means that it has a nationwide impact on network resource usage. The use of more radio telescopes and data collection in the very near future will require a bandwidth of more than 8 Gbps for this project. Another example is the ATLAS experiment [5] at the Large Hadron Collider (LHC) at Conseil European pour la Recherche Nucleaire (CERN). It must transfer huge amounts of data from Switzerland to Japan through GEANT2 and SINET3's international line. As of late 2009, this experimental data occupied 2 to 4 Gbps of bandwidth. The stored data in Japan will be selectively copied and transferred to fifteen domestic universities and research institutions over SINET3. In another development, nuclear fusion researchers have recently started an experiment on huge data transfers from France, where the International Thermonuclear Experimental Reactor (ITER) will be built. So far, they have found that they can transfer data from France to Japan at a rate of 4 Gbps [6]. The data from ITER will be transferred to Rokkasho Mura and then distributed to several domestic universities and research institutions. The issue we face today is how to assign network resources to a growing number of big scientific research projects and at the same time maintain normal services for research and academia.  
Our network supports many research and educational applications that are sensitive to network performance issues such as delay variance and packet loss. For example, remote lectures using high-definition videos, which require assured bandwidth of tens of Mbps, have been getting very popular because of the expansion of the credit transfer system between universities and the spread of inexpensive high-definition video systems. Moreover, live video multicasts of surgeries, especially those involving rare cases and procedures, have become popular among surgeons [7] as a way of sharing their experiences and knowledge. Remote control of mechanical devices by video is another application sensitive to network performance. Video-based applications like these are carried out between university access circuits that also carry download traffic from the Internet and whose usage rates are usually high. Therefore, control of the quality of service for video-based applications, especially at the access points to SINET3, is a very important issue.  
This paper describes dynamic resource allocation and QoS capabilities that can accommodate the data-intensive applications of big science and the performance-sensitive applications of other research and educational fields. Note that as we have already described the basic design and technologies of SINET3 in reference [3], this paper focuses on the resource allocation capabilities and implementation of typical services developed for data-intensive applications, _i.e._, layer-1 bandwidth on demand (BoD) services. The remainder of this paper is organized as follows. Section 2 overviews the network architecture and technologies used in SINET3 and shows usage examples of resource allocation and QoS control. Section 3 shows how layer-1 BoD services are implemented in terms of the user interface, control interface to layer-1 devices, and resource management functions. Section 4 describes a performance evaluation from the perspective of resource allocation time. Section 5 is the conclusion.