# Balloon: An Elastic Data Management Strategy for Interlaced Magnetic Recording
## 5 Performance Evaluation  
### Evaluation Setup  
In this section, the effectiveness of the proposed Balloon translation layer is evaluated and the related evaluation results are reported. Since IMR is a very new technology, there are no IMR disks in the market yet. Therefore, we simulate the characteristics of an IMRdisk based on a real CMR disk (model ST500 DM002 [23]). The track size of the simulated IMR disk is set to 2 MB, which is set concerning recent studies [10; 11; 15; 24]. The prototype system of the proposed strategy provides a block interface for the upper layer to replay I/O requests from block-level trace files. Specifically, all I/O requests are submitted to the simulated device through read and write functions provided by the open-source library libaio [25]. To improve the accuracy of the evaluation, all replayed read and write requests are direct I/O, bypassing the kernel buffer, and the on-disk cache is disabled. In addition, the capacity of the IMR disks was not set to a fixed value but determined by the unique track count written in the currently replayed trace to evaluate the performance of Balloon and competitors under different space utilization. All evaluations are performed on an AMD workstation with EPYC 7302 CPU 3.0 GHz and 128 GB RAM. The operating system is Ubuntu 20.04.1 based on the Linux 5.15.0 kernel.  
Our goal is to narrow the performance gap between IMR disks and CMR disks to make them suitable for traditional server application scenarios. To achieve this, we selected a set of write-intensive tracks from the MSR collection [17; 18], since read-intensive workloads may not result in track rewrites. The write requests in the selected trace exhibit various characteristics, including temporal and spatial locality, as well as random and sequential nature. Table 1 provides details about these characteristics. Throughout this study, our focus has been on evaluating the performance of the proposed strategy under high space utilization. Therefore, the number of available tracks is dynamically adjusted based on the footprint (total number of unique tracks written) of the selected trace. For example, at 100% space utilization, the total number of available tracks is equal to the total number of unique tracks written in the selected trace. Similarly, at 50% space utilization, the total number of available tracks is twice the number of unique tracks written.  
In addition to the CMR disks used as a baseline, state-of-the-art ITL designs are carefully selected as Balloon competitors. These competitors include three-phase write management (Seagate) [12; 13], selective track caching (STC) [15], dynamic track mapping (DTM) [15], MOM [11], and MAGIC [10], and their fundamentals are described in the related work in Section 2. We also included a variant of Balloon in the evaluation, called Balloon-MS, which disables the WIF-PB and allows only merge and swap operations. This variant helps us observe the extent of performance improvement on IMR disks with limited disk resources. To ensure a fair evaluation, the parameters of all competitors are strictly set according to the source paper. Specifically, the update frequency of the selective track caching and dynamic track mapping policies is set to 20 K, with the persistent buffer size of the former set to 1% of the disk capacity (see the settings of the latest SMR disks), similar to the settings of the Balloon and MAGIC, while the latter has a hot/cold threshold of 50 and includes 256 pseudotracks per zone. For MAGIC, we use the default region size of 64 MB as suggested in the original paper. In Balloon, referencing studies [19; 20], the TMBF is configured with N = 8 and \(p\) = 2048, and the oldest BF is reset every 256 update requests for different tracks to decay the records in the TMBF. All these settings ensure a fair and comprehensive comparison between the ITL designs.