Name
Abstract | ||
|---|---|---|
MEMS-based storage is an emerging nonvolatile secondary storage technology. It promises high performance, high storage density, and low power consumption. With fundamentally different architectural designs from magnetic disk, MEMS-based storage exhibits unique two-dimensional positioning behaviors and efficient power state transitions. We model these low-level, device-specific properties of MEMS-based storage and present request scheduling algorithms and power management strategies that exploit the full potential of these devices. Our simulations show that MEMS-specific device management policies can significantly improve system performance and reduce power consumption. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1145/1149976.1149978 | TOS |
Keywords | Field | DocType |
power management,general terms: algorithms,request scheduling,efficient power state transition,mems-based storage,low power consumption,power consumption,mems-specific device management policy,nonvolatile secondary storage technology,device modeling,power management strategy,system performance,computer system,performance additional key words and phrases: mems-based storage,high performance,high storage density,management,scheduling algorithm,state transition | Power management,Converged storage,Microelectromechanical systems,Computer science,Scheduling (computing),Exploit,Real-time computing,Computer hardware,Auxiliary memory,Power consumption,Embedded system | Journal |
Volume | Issue | Citations |
2 | 2 | 7 |
PageRank | References | Authors |
0.60 | 15 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo Hong | 1 | 54 | 4.35 |
| Scott A. Brandt | 2 | 1663 | 94.81 |
| Darrell D. E. Long | 3 | 3111 | 536.40 |
| Ethan L. Miller | 4 | 2870 | 281.96 |
| Ying Lin | 5 | 7 | 0.60 |