ACM Transactions on Computer Systems (TOCS)
On-line extraction of SCSI disk drive parameters
Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Temporally determinate disk access (extended abstract): an experimental approach
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
A Comprehensive Analytical Performance Model for Disk Devices under Random Workloads
IEEE Transactions on Knowledge and Data Engineering
Track-Aligned Extents: Matching Access Patterns to Disk Drive Characteristics
FAST '02 Proceedings of the Conference on File and Storage Technologies
Bridging the Information Gap in Storage Protocol Stacks
ATEC '02 Proceedings of the General Track of the annual conference on USENIX Annual Technical Conference
Monitoring hard disks with smart
Linux Journal
More Than an Interface---SCSI vs. ATA
FAST '03 Proceedings of the 2nd USENIX Conference on File and Storage Technologies
Atropos: A Disk Array Volume Manager for Orchestrated Use of Disks
FAST '04 Proceedings of the 3rd USENIX Conference on File and Storage Technologies
Intelligent storage: Cross-layer optimization for soft real-time workload
ACM Transactions on Storage (TOS)
On multidimensional data and modern disks
FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
Towards higher disk head utilization: extracting free bandwidth from busy disk drives
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
An analysis of latent sector errors in disk drives
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Partial Disk Failures: Using Software to Analyze Physical Damage
MSST '07 Proceedings of the 24th IEEE Conference on Mass Storage Systems and Technologies
DiskSeen: exploiting disk layout and access history to enhance I/O prefetch
ATC'07 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference
An analysis of data corruption in the storage stack
FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
Hard Disk Drive for HD Quality Multimedia Home Appliance
ICCSA '08 Proceedings of the 2008 International Conference on Computational Sciences and Its Applications
Shedding Light in the Black-Box: Structural Modeling of Modern Disk Drives
MASCOTS '07 Proceedings of the 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
DIG: Rapid Characterization of Modern Hard Disk Drive and Its Performance Implication
SNAPI '08 Proceedings of the 2008 Fifth IEEE International Workshop on Storage Network Architecture and Parallel I/Os
HDD characterization for A/V streaming applications
IEEE Transactions on Consumer Electronics
SSD characterization: from energy consumption's perspective
HotStorage'11 Proceedings of the 3rd USENIX conference on Hot topics in storage and file systems
High-throughput low-latency fine-grained disk logging
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
Onion and pizza: new disk partitioning schemes for virtualization systems
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Fourier-assisted machine learning of hard disk drive access time models
PDSW '13 Proceedings of the 8th Parallel Data Storage Workshop
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The modern hard disk drive is a complex and complicated device. It consists of 2--4 heads, thousands of sectors per track, several hundred thousands of tracks, and tens of zones. The beginnings of adjacent tracks are placed with a certain angular offset. Sectors are placed on the tracks and accessed in some order. Angular offset and sector placement order vary widely subject to vendors and models. The success of an efficient file and storage subsystem design relies on the proper understanding of the underlying storage device characteristics. The characterization of hard disk drives has been a subject of intense research for more than a decade. The scale and complexity of state-of-the-art hard disk drive technology calls for a new way of extracting and analyzing the characteristics of the hard disk drive. In this work, we develop a novel disk characterization suite, DIG (Disk Geometry Analyzer), which allows us to rapidly extract and characterize the key performance metrics of the modern hard disk drive. Development of this tool is accompanied by thorough examination of four off-the-shelf hard disk drives. DIG consists of three key ingredients: O(1) a track boundary detection algorithm; O(log n) a zone boundary detection algorithm; and hybrid sampling based seek time profiling. We particularly focus on addressing the scalability aspect of disk characterization. With DIG, we are able to extract key metrics of hard disk drives, for example, track sizes, zone information, sector geometry and so on, within 3--20 minutes. DIG allows us to determine the sector layout mechanism of the underlying hard disk drive, for example, hybrid serpentine, cylinder serpentine, and surface serpentine, and to a build complete sector map from LBN to the three dimensional space of (Cylinder, Head, Sector). Examining the hard disk drives with DIG, we made a number of important observations. In modern hard disk drives, head switch overhead is far greater than track switch overhead. It seems that hard disk drive vendors put greater emphasis on reducing the number of head switches for data access. Most disk vendors use surface serpentine, cylinder serpentine, or hybrid serpentine schemes in laying sectors on the platters. The legacy seek time model, which takes the form of a+b&sqrt;d leaves much to be desired for use in modern hard disk drives especially for short seeks (less than 5000 tracks). We compare the performance of the DIG against the existing state-of-the-art disk profiling algorithm. Compared to the existing state-of-the-art disk characterization algorithm, the DIG algorithm significantly decreases the time to extract comprehensive sector geometry information from 1920 minutes to 7 minutes and 1927 minutes to 180 minutes in best and worst case scenarios, respectively.