Scheduling algorithms for modern disk drives
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Modeling and performance of MEMS-based storage devices
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Designing computer systems with MEMS-based storage
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Towards Optimal I/O Scheduling for MEMS-Based Storage
MSS '03 Proceedings of the 20 th IEEE/11 th NASA Goddard Conference on Mass Storage Systems and Technologies (MSS'03)
MEMS-based Storage Devices and Standard Disk Interfaces: A Square Peg in a Round Hole?
FAST '04 Proceedings of the 3rd USENIX Conference on File and Storage Technologies
Parallelism-Aware Request Scheduling for MEMS-based Storage Devices
MASCOTS '06 Proceedings of the 14th IEEE International Symposium on Modeling, Analysis, and Simulation
Operating system management of MEMS-based storage devices
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Tabular placement of relational data on MEMS-based storage devices
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Effects of scheduling on file memory operations
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
The "Millipede": more than one thousand tips for future AFM data storage
IBM Journal of Research and Development
Moneta: A High-Performance Storage Array Architecture for Next-Generation, Non-volatile Memories
MICRO '43 Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture
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MEMS-based storage is one of the leading candidates as tomorrow's storage medium due to its salient characteristics such as high-parallelism, high density, and low-power consumption. Because physical structures of MEMS-based storage is different from those of hard disks, new software management techniques for MEMS-based storage are needed. Specifically, MEMS-based storage has thousands of parallel-activating heads, which requires parallelism-aware request scheduling algorithms to maximize the performance of the storage media. In this paper, we compare various versions of I/O scheduling algorithms that exploit high-parallelism of MEMS-based storage devices. Trace-driven simulations show that parallelism-aware algorithms can be effectively used for high capacity mass storage servers because they perform better than other algorithms in terms of the average response time when the workload intensity becomes heavy.