# A Scalable Parallel Architecture Based on Many-Core Processors for Generating HTTP Traffic
## 2 Background and Challenges
### Challenges  
Generating high-volume, stable, realistic test traffic is crucial for assessing the performance of network devices in a reliable way and under different stress conditions. In this paper, we borrow from the hierarchical architecture design [22] in that it separates control plans and perform plans, and exposes the functions' interface to higher layers to deal with the dynamics of the network.  
Two main technical challenges should be considered. First, its realistic replication is a challenging task over the large scale of time. The multidimensional heterogeneity of the current internet exacerbates the seriousness of the problem. However, the existing schemes can only reflect a period of time or the previous characteristics of the network. To address this issue, we need to generate the background traffic with the characteristics of a real network over a long and large time scale according to Internet users' access time data in different scenarios. Therefore, we present a method based on the cubic spline interpolation of the user control method to simulate the characteristics of a real network. Meanwhile, we generate a realistic network workload by accessing the real server.  
Second, existing schedules have mostly been low-efficient due to the limited hardware resources and inefficient process. To better improve the scalability of the system and satisfy the required flow rate, the support for high-performance and configurable experiments is greatly needed in such context. Furthermore, in large-scale networks, tests have to be performed automatically because the size of the system under test may prevent the manual performance of activities on each and every host involved in the experiment. Even though existing traffic generators are quite useful, nonetheless, most of them suffer from the following: (1) It may need special equipment which is expensive or not commonly used. For example, MoonGen [23] is a flexible high-speed packet generator. A key feature is the measurement of latency with sub-microsecond precision and accuracy by using hardware timestamp capabilities of modern commodity NICs (Network Interface Cards); (2) It is not trivial to generate traffic data in arbitrary spatial regions using existing traffic generators. For example, DPDK (Data Plane Development Kit) is a set of libraries and drivers for fast packet processing, which is widely used in the field of traffic generators, such as MoonGen [23], TRex [24]. However, it can only capture the packet at the data link layer instead of dealing with it at the application layer. In order to generate real web traffic, the packet must enter the kernel protocol stack. The availability of generic many-core architectures with tens to hundreds of cores per processor which have the features of low-cost and feature-rich, is offering new opportunities for parallelization and extensibility. Taking advantage of the efficient network architecture, a schedule should be designed, which can efficiently address the challenges of high-performance and improve the efficiency to leverage the Many-Core processors.