| Internet-Draft | DES Problem Statement | March 2024 |
| Du, et al. | Expires 3 September 2024 | [Page] |
This document describes use cases and problem statement of Online Data Express Service.¶
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As the rapid development of digital technologies, transporting a bulk of data conveniently between two places has become a fundamental requirement for the Internet. However, the user experience of transferring a large file is not always that satisfying. For example, although we can connect to a cloud service anywhere now, sometimes the file upload experience is slow and troublesome. Alternatively, we can post a hard disk to others for this big data transferring.¶
The Online Data Express Service (ODES) mentioned in this document is a convenient online service, which can transfer a large file or a bundle of files between different entities within a time limitation. The file size may be at GB, TB level, or even bigger. The time limitation may be several hours, one day or two days.¶
The target approach in ODES should be more flexible and convenient than the manual hard disk express, and can be quicker than the approach of transferring by using the Internet directly.¶
The ODES use cases include inter-cloud backup and disaster recovery, film and television editing, scientific computing, cooperation of intelligent computing centers, etc. This document also analyzes the problems that need to be considered for ODES. A gap analysis document can be found in [I-D.zhao-tsvwg-odes-gap-analysis].¶
With the development of cloud computing industry, cloud data centers bear various enterprise IT services. The storage, transmission, and protection of the massive growth data bring new challenges. Disaster recovery of core application data is necessary to ensure enterprise data security and business continuity. Taking the disaster recovery of operator traffic data as an example, the daily data backup volume of a single IT cloud resource pool is at the TB level. The primary and backup data centers are normally built in different locations, with long data transmission distances and large amounts of data. However, they do not have high requirements for data transmission timeliness. By utilizing the tidal effect of the network, we can use idle bandwidth at night for transmission, so as to improve data transmission efficiency and reduce the data transmission cost.¶
The shooting materials for films and television variety shows need to be edited and rendered by a post-production company. Due to the uncertain shooting location, the shooting materials need to be transferred in bulk to the post-production company's site according to the shooting and production cycle. The raw material data volume of a large-scale variety show or film and television program is at the PB level, with a single transmission of approximately 10TB to 100TB of data. The manual hard disk express method involves two data copies (source upload, destination download) and manual handling (taking an airplane or a high-speed rail to transport the disk array). Each trip takes 2-3 days and requires dedicated personnel to operate, resulting in poor timeliness and low efficiency. How to fully utilize network capabilities and provide convenient online data movement services for the audio and video industry through online transmission while meeting timeliness and reducing labor investment costs poses new challenges to the network.¶
In the development of intelligent computing and supercomputing, the import and export of big data from intelligent computing and supercomputing centers is required. However, it lacks efficient and low-cost solutions, especially in supporting scientific computing scenarios such as astronomy and meteorology. Taking the calculation of FAST astronomical data of China as an example, FAST has approximately 200 observation projects per year, with a single project generating observation data of TB~PB magnitude and an annual output of approximately 15PB. If the data export is done manually, the data export application may be delayed for several months due to the lack of dedicated personnel responsible for data copy operations. In addition, data transmission and destination data import operations are very time-consuming, significantly affecting the timeliness of data acquisition. There is an urgent need for an efficient and economical online data transmission solution for large-scale data migration scenarios in scientific computing.¶
Gene sequencing technology is becoming increasingly mature, significantly shortening the sequencing time and promoting its application comprehensively. It can provide various gene sequencing and data analysis services to scientific research institutions, medical service institutions, or individuals. Traditional gene sequencing mainly relies on local laboratory analysis, and its timeliness and scale are constrained by local computing resources, making it difficult to improve. Cloud-based gene sequencing data have gradually become an industry trend. A domestic gene company has a gene sequencing data volume of 100PB/year, with a cloud data volume of approximately TB~100TB/time. The gene sequencing data source and supercomputing cloud data center are connected through a fixed bandwidth dedicated line, which is expensive and lacks cost-effective solutions.¶
With the vigorous development of industrial digitalization and cloud computing, the demand for high-capacity data transmission in different places is increasing. At the same time, scenarios such as multi-cloud data backup and data on remote cloud in different places put forward higher requirements on the throughput of online data transmission. There is an urgent need to achieve high-throughput transmission of massive data in WAN.¶
By analyzing and summarizing the above typical application scenarios, we obtain the following common features.¶
Large amount of data transmitted in a single time: TB~PB.¶
High flow transmission frequency: There is a demand for regular or irregular data transmission, with high peak bandwidth requirements.¶
Low real-time requirements: Mainly warm and cold data, not strongly real-time hot data, but the faster the transmission completion time, the better.¶
Cost-sensitive: Customers do not want to pay for high bandwidth dedicated lines separately because the transmission frequency is variable, which leads to low network utilization and cost-effectiveness.¶
To support differentiated data delivery services and create task-based data delivery services, the target ODES system should meet the following challenges and requirements.¶
High throughput in WAN is an important goal of data express service. Technologies such as wide-area RDMA and Elephant flow load balancing could be utilized to achieve high throughput network data transmission.¶
Compared with using fixed bandwidth of traditional dedicated lines for data transmission, data express supports the bandwidth elastic expansion and contraction function, providing users with plug and play, stop after use and highly elastic services.¶
Data, as the core asset of users, enterprises, social organizations, etc., are related to the interests of all parties, so we must attach great importance to data security. On the basis of providing efficient transmission services, data express strictly guarantees the security of user data and ensures that user data will not be stolen or tampered with.¶
The data express business has the characteristics of large amount of data and long transmission distance. In order to better meet the business requirements, it is needed to ensure that the data can be transmitted to the destination in a time as short as possible if necessary, so that the flow completion time can be shorten.¶
TBD.¶
TBD.¶